Question: Transporting you back in time: Automatically creating event chronicles relevant to specific topics.

This paper explores methodologies for generating chronological summaries of news topics, enabling users to track shifts in media coverage over time. A chronological summary is defined as selecting a representative sentence from each significant event within a news topic, presented sequentially. Before moving on to the next event, sentences within the same event are ranked. We outline an evaluation framework and present an evaluation dataset we have constructed for this purpose. Additionally, we introduce various techniques for creating such chronological summaries and assess their performance against baseline methods. Our findings reveal that straightforward approaches can be surprisingly effective, yet the challenge of producing high-quality chronological news summaries remains largely unresolved.

This paper presents results of an extensive long-term click-stream study of Web browser usage. Focusing on character and challenges of page revisitation, previous findings from seven to thirteen years ago are updated. The term page re-visit had to be differentiated, since the recurrence rate--the key measure for the share of page revisits--turns out to strongly depend on interpretation. We identify different types of revisitation that allow assessing the quality of current user support and developing concepts for new tools.
 Individual navigation strategies differ dramatically and are strongly influenced by personal habits and type of site visited. Based on user action logs and interviews, we distinguished short-term revisits (backtrack or undo) from medium-term (re-utilize or observe) and long-term revisits (rediscover). We analyze current problems and provide suggestions for improving support for different revisitation types.

Researchers and scientists increasingly find themselves in the position of having to quickly understand large amounts of technical material. Our goal is to effectively serve this need by using bibliometric text mining and summarization techniques to generate summaries of scientific literature. We show how we can use citations to produce automatically generated, readily consumable, technical extractive summaries. We first propose C-LexRank, a model for summarizing single scientific articles based on citations, which employs community detection and extracts salient information-rich sentences. Next, we further extend our experiments to summarize a set of papers, which cover the same scientific topic. We generate extractive summaries of a set of Question Answering (QA) and Dependency Parsing (DP) papers, their abstracts, and their citation sentences and show that citations have unique information amenable to creating a summary.

Topic modeling has been commonly used to discover topics from document collections. However, unsupervised models can generate many incoherent topics. To address this problem, several knowledge-based topic models have been proposed to incorporate prior domain knowledge from the user. This work advances this research much further and shows that without any user input, we can mine the prior knowledge automatically and dynamically from topics already found from a large number of domains. This paper first proposes a novel method to mine such prior knowledge dynamically in the modeling process, and then a new topic model to use the knowledge to guide the model inference. What is also interesting is that this approach offers a novel lifelong learning algorithm for topic discovery, which exploits the big (past) data and knowledge gained from such data for subsequent modeling. Our experimental results using product reviews from 50 domains demonstrate the effectiveness of the proposed approach.

We consider incorporating topic information into a sequenceto-sequence framework to generate informative and interesting responses for chatbots. To this end, we propose a topic aware sequence-to-sequence (TA-Seq2Seq) model. The model utilizes topics to simulate prior human knowledge that guides them to form informative and interesting responses in conversation, and leverages topic information in generation by a joint attention mechanism and a biased generation probability. The joint attention mechanism summarizes the hidden vectors of an input message as context vectors by message attention and synthesizes topic vectors by topic attention from the topic words of the message obtained from a pre-trained LDA model, with these vectors jointly affecting the generation of words in decoding. To increase the possibility of topic words appearing in responses, the model modifies the generation probability of topic words by adding an extra probability item to bias the overall distribution. Empirical studies on both automatic evaluation metrics and human annotations show that TA-Seq2Seq can generate more informative and interesting responses, significantly outperforming state-of-theart response generation models.

We consider the problem of learning to summarize images by text and visualize text utilizing images, which we call Mutual-Summarization. We divide the web image-text data space into three subspaces, namely pure image space (PIS), pure text space (PTS) and image-text joint space (ITJS). Naturally, we treat the ITJS as a knowledge base.
 For summarizing images by sentence issue, we map images from PIS to ITJS via image classification models and use text summarization on the corresponding texts in ITJS to summarize images. For text visualization problem, we map texts from PTS to ITJS via text categorization models and generate the visualization by choosing the semantic related images from ITJS, where the selected images are ranked by their confidence. In above approaches images are represented by color histograms, dense visual words and feature descriptors at different levels of spatial pyramid; and the texts are generated according to the Latent Dirichlet Allocation (LDA) topic model. Multiple Kernel (MK) methodologies are used to learn classifiers for image and text respectively. We show the Mutual-Summarization results on our newly collected dataset of six big events ("Gulf Oil Spill", "Haiti Earthquake", etc.) as well as demonstrate improved cross-media retrieval performance over existing methods in terms of MAP, Precision and Recall.

Written development communication (e.g. mailing lists, issue trackers) constitutes a precious source of information to build recommenders for software engineers, for example aimed at suggesting experts, or at redocumenting existing source code. In this paper we propose a novel, semi-supervised approach named DECA (Development Emails Content Analyzer) that uses Natural Language Parsing to classify the content of development emails according to their purpose (e.g. feature request, opinion asking, problem discovery, solution proposal, information giving etc), identifying email elements that can be used for specific tasks. A study based on data from Qt and Ubuntu, highlights a high precision (90%) and recall (70%) of DECA in classifying email content, outperforming traditional machine learning strategies. Moreover, we successfully used DECA for re-documenting source code of Eclipse and Lucene, improving the recall, while keeping high precision, of a previous approach based on ad-hoc heuristics.

Recently, microblogging sites such as Twitter have garnered a great deal of attention as an advanced form of location-aware social network services, whereby individuals can easily and instantly share their most recent updates from any place. In this study, we aim to develop a geo-social event detection system by monitoring crowd behaviors indirectly via Twitter. In particular, we attempt to find out the occurrence of local events such as local festivals; a considerable number of Twitter users probably write many posts about these events. To detect such unusual geo-social events, we depend on geographical regularities deduced from the usual behavior patterns of crowds with geo-tagged microblogs. By comparing these regularities with the estimated ones, we decide whether there are any unusual events happening in the monitored geographical area. Finally, we describe the experimental results to evaluate the proposed unusuality detection method on the basis of geographical regularities obtained from a large number of geo-tagged tweets around Japan via Twitter.

The goal of TDT Topic Detection and Tracking is to develop aut omatic methods of identifying topically related stories wit hin a stream of news media. We describe approaches for both detection and tr cking based on the well-known idf -weighted cosine coefficient similarity metric. The surprising outcome of this research is th at we achieved very competitive results for tracking using a very simple method of feature selection, without word stemming and with ou a score normalization scheme. The detection task results wer e not as encouraging though we attribute this more to the clustering algorithm than the underlying similarity metric. 1. The Tracking Task The goal of the topic tracking task for TDT2 is to identify new s stories on a particular event defined by a small number ( Nt) of positive training examples and a greater number of negative examples . All stories in the news stream subsequent to the final positive ex ample are to be classified as on-topic if they pertain to the event or off-topic if they do not. Although the task is similar to IR routing and fi ltering tasks, the definition of event leads to at least one significan t difference. An event is defined as an occurrence at a given place and t ime covered by the news media. Stories are on-topic if they cover th event itself or any outcome (strictly-defined in [2]) of the e vent. By this definition, all stories prior to the occurrence are offt pic, which contrary to the IR tasks mentioned, theoretically provides for unlimited off-topic training material (assuming retrospective corpora are available). We expected to be able to take advantage of these unlimited negative examples but in our final implementation did so only to the extent that we used a retrospective corpus to improve t erm statistics of our database. 1.1. idf-Weighted Cosine Coefficient As the basis for our approach we used the idf -weighted cosine coefficient described in [1] often referred to as tf idf . Using this metric, the tracking task becomes two-fold. Firstly, choosing an op timal set of features to represent topics, i.e. feature selection. Th e approach must choose features from a single story as well as from multi ple stories (forNt > 1). Secondly, determining a threshold (potentially one per topic) which optimizes the miss and false alarm proba bilities for a particular cost function, effectively normalizing th e similarity scores across topics. The cosine coefficient is a document similarity metric which has been investigated extensively. Here documents (and querie s) ar represented as vectors in an n-dimensional space, where n is the number of unique terms in the database. The coefficients of th e vector for a given document are the term frequencies ( tf ) for that dimension. The resulting vectors are extremely sparse and t ypically high frequency words (mostly closed class) are ignored. The cosine of the angle between two vectors is an indication of vector si milarity and is equal to the dot-product of the vectors normalized by the product of the vector lengths. cos( ) = ~ A ~ B k ~ Akk ~ Bk tf idf (term frequency times inverse document frequency) weighting is an ad-hoc modification to the cosine coefficient calcul tion which weights words according to their usefulness in discriminating documents. Words that appear in few documents are more usefu l than words that appear in many documents. This is captured in the equation for the inverse document frequency of a word: idf(w) = log10 N df(w) Wheredf(w) is the number of documents in a collection which contain wordw andN is the total number of documents in the collection. For our implementation we weighted only the topic vector by idf and left the story vector under test unchanged. This allows u s to calculate and fix anidf -scaled topic vector immediately after training on the last positive example story for a topic. The resulting calculation for the similarity measure becomes: sim(a; b) = Pnw=1 tfa(w) tfb(w) idf(w) pPnw=1 tf2 a (w) pPnw=1 tf2 b (w) 1.2. UPENN System Attributes To facilitate testing, the stories were loaded into a simple document processing system. Once in the system, stories are proc ssed in chronological order testing all topics simultaneously w ith a single pass over the data 1 at a rate of approximately 6000 stories per minute on a Pentium 266 MHz machine. The system tokenizer delimits on white space and punctuation (and discards it), col lapses case, but provides no stemming. A list of 179 stop words consi sti g almost entirely of close classed words was also employed. In order to improve word statistics, particularly for the beginning of the test set, we prepended a retrospective corpus (the TDT Pilot Data [3]) of approximately 16 thousand stories. 1In accordance with the evaluation specification for this pro ject [2] no information is shared across topics. 1.3. Feature Selection Thechoice as well asnumber of features (words) used to represent a topic has a direct effect on the trade-off between miss and f lse alarm probabilities. We investigated four methods of produ cing lists of features sorted by their effectiveness in discriminatin g a topic. This then allowed us to easily vary the number of those featur s for the topic vectors 2. 1. Keep all features except those words belonging to the stop word list. 2. Relative to training stories, sort words by document coun t, keepn most frequent. This approach has the advantage of finding those words which are common across training stories, an d therefore are more general to the topic area, but has the disa dvantage of extending poorly from the Nt = 16 case to the Nt = 1 case. 3. For each story, sort by word count ( tf ), keepn most frequent. While this approach tends to ignore low count words which occur in multiple training documents, it generalizes well f rom theNt = 16 to theNt = 1 case. 4. As a variant on the previous method we tried adding to the initial n features using a simple greedy algorithm. Against a database containing all stories up to and including the Nt-th training story, we queried the database with the n f atures plus the next most frequent term. If the separation of on-topic an d off-topic stories increased, we kept the term, if not we igno red it and tested the next term in the list. We defined separation as the difference between the average on-topic scores and th e average of the 20 highest scoring off-topic documents. Of the feature selection methods we tried the forth one yield ed the best results across varying values of Nt, although only slightly better than the much simpler third method. Occam’s Razor prompt ed us to omit this complication from the algorithm. The DET curves 3 in Figure 1. show the effect of varying the number of features (o btained from method 3) on the miss and false alarm probabilities. The upper right most curve results from choosing the single most fr equent feature. Downward to the left, in order are the curves for 5, 1 0, 50, 150 and 300 features. After examining similar plots from the pilot, training4, and development-test data sets, we set the number of features for our system to 50. It can be seen that there is limited benefit in adding features after this point. 1.4. Normalization / Threshold Selection With a method of feature selection in place, a threshold for t he similarity score must be determined above which stories will be d e med on-topic, and below which they will not. Since each topic is r epresented by its own unique vector it cannot be expected that the same threshold value will be optimal across all topics unless the scores are normalized. We tried two approaches for normalizing the topic similarity scores. For the first approach we calculated the similarity of a rando m sample of several hundred off-topic documents in order to estim a e an 2We did not employ feature selection on the story under test bu t used the text in entirety. 3See [5] for detailed description of DET curves. 4The first two month period of TDT2 data is called the training s et, not to be confused with training data. 1 2 5 10 20 40 60 80 90 .01 .02 .05 .1 .2 .5 1 2 5 10 20 40 60 80 90 M is s pr ob ab ili ty ( in % ) False Alarms probability (in %) random performance num_features=1 num_features=5 num_features=10 num_features=50 num_features=150 num_features=300 Figure 1: DET curve for varying number of features. (Nt=4, TD T2 evaluation data set, newswire and ASR transcripts) average off-topic score relative to the topic vector. The no rmalized score is then a function of the average on-topic 5 and off-topic scores and the off-topic standard deviation 6. The second approach looked at only thehighest scoringoff-topic stories returned from a query of the topic vector against a retrospective database with th e score normalized in a similar fashion to the first approach. Both attempts reduced the story-weighted miss probability by approximately 10 percent at low false alarm probability relat ive. However, this results was achieved at the expense of higher miss probability at higher false alarm probability, and a higher cost a t the operating point defined by the cost function for the task 7. Ctrack = Cmiss P (miss) Ptopic +Cfa P (fa) (1 Ptopic) where Cmiss = 1: (the cost of a miss) Cfa = 1: (the cost of a false alarm) Ptopic = 0:02: (thea priori probability of a story being on a given topic was chosen based on the TDT2 training topics and traini ng corpus.) Because of the less optimal trade-off between error probabi lities at the point defined by the cost function, we choose to ignore nor malization and look directly at cost as a function of a single thr es old value across all topics. We plotted tf idf score against story and topic-weighted cost for the training and development-test data sets. As our global threshold we averaged the scores at which story and topic-weighted cost were minimized. This is depicted in figu re 2. Figure 3 shows the same curves for the evaluation data set. Th e threshold resulting from the traini

Nowadays there is an important need by journalists and media monitoring companies to cluster news in large amounts of web articles, in order to ensure fast access to their topics or events of interest. Our aim in this work is to identify groups of news articles that share a common topic or event, without a priori knowledge of the number of clusters. The estimation of the correct number of topics is a challenging issue, due to the existence of “noise”, i.e. news articles which are irrelevant to all other topics. In this context, we introduce a novel density-based news clustering framework, in which the assignment of news articles to topics is done by the well-established Latent Dirichlet Allocation, but the estimation of the number of clusters is performed by our novel method, called “DBSCAN-Martingale”, which allows for extracting noise from the dataset and progressively extracts clusters from an OPTICS reachability plot. We evaluate our framework and the DBSCAN-Martingale on the 20newsgroups-mini dataset and on 220 web news articles, which are references to specific Wikipedia pages. Among twenty methods for news clustering, without knowing the number of clusters k, the framework of DBSCAN-Martingale provides the correct number of clusters and the highest Normalized Mutual Information.

With the popularity of social media (e.g., Facebook and Flicker), users can easily share their check-in records and photos during their trips. In view of the huge number of user historical mobility records in social media, we aim to discover travel experiences to facilitate trip planning. When planning a trip, users always have specific preferences regarding their trips. Instead of restricting users to limited query options such as locations, activities, or time periods, we consider arbitrary text descriptions as keywords about personalized requirements. Moreover, a diverse and representative set of recommended travel routes is needed. Prior works have elaborated on mining and ranking existing routes from check-in data. To meet the need for automatic trip organization, we claim that more features of Places of Interest (POIs) should be extracted. Therefore, in this paper, we propose an efficient Keyword-aware Representative Travel Route framework that uses knowledge extraction from users’ historical mobility records and social interactions. Explicitly, we have designed a keyword extraction module to classify the POI-related tags, for effective matching with query keywords. We have further designed a route reconstruction algorithm to construct route candidates that fulfill the requirements. To provide befitting query results, we explore Representative Skyline concepts, that is, the Skyline routes which best describe the trade-offs among different POI features. To evaluate the effectiveness and efficiency of the proposed algorithms, we have conducted extensive experiments on real location-based social network datasets, and the experiment results show that our methods do indeed demonstrate good performance compared to state-of-the-art works.


Question: Agile team views on elements impacting productivity.

This paper outlines a set of provisional research guidelines aimed at enhancing the quality and transparency of empirical research in software engineering. Recognizing the need for improved methodologies and reporting standards, these guidelines are designed to provoke critical dialogue among software engineering researchers. Inspired by established protocols for medical research and informed by our collective experience in conducting and assessing software engineering studies, these guidelines offer a framework for researchers, reviewers, and meta-analysts to optimize the design, execution, and evaluation of empirical investigations. They are intended to serve as a resource for enhancing the rigor of research, facilitating more effective peer review, and guiding the development of policies by editorial boards of software engineering journals regarding the conduct, data gathering, analysis, and dissemination of empirical research findings.

The overall goal of our Software Engineering Teamwork Assessment and Prediction (SETAP) project is to develop effective machine-learning-based methods for assessment and early prediction of student learning effectiveness in software engineering teamwork. Specifically, we use the Random Forest (RF) machine learning (ML) method to predict the effectiveness of software engineering teamwork learning based on data collected during student team project development. These data include over 100 objective and quantitative Team Activity Measures (TAM) obtained from monitoring and measuring activities of student teams during the creation of their final class project in our joint software engineering classes which ran concurrently at San Francisco State University (SFSU), Fulda University (Fulda) and Florida Atlantic University (FAU). In this paper we provide the first RF analysis results done at SFSU on our full data set covering four years of our joint SE classes. These data include 74 student teams with over 380 students, totaling over 30000 discrete data points. These data are grouped into 11 time intervals, each measuring important phases of project development during the class (e.g. early requirement gathering and design, development, testing and delivery). We briefly elaborate on the methods of data collection and describe the data itself. We then show prediction results of the RF analysis applied to this full data set. Results show that we are able to detect student teams who are bound to fail or need attention in early class time with good (about 70%) accuracy. Moreover, the variable importance analysis shows that the features (TAM measures) with high predictive power make intuitive sense, such as late delivery/late responses, time used to help each other, and surprisingly statistics on commit messages to the code repository, etc. In summary, we believe we demonstrate the viability of using ML on objective and quantitative team activity measures to predict student learning of software engineering teamwork, and point to easy-to-measure factors that can be used to guide educators and software engineering managers to implement early intervention for teams bound to fail. Details about the project and the complete ML training database are downloadable from the project web site.

Editor’s note The authors of this paper presented an All-academy session at the 2008 Academy of Management annual meeting in Anaheim, California. We were excited by the dynamic nature of the debate and felt that it related closely to critical issues in the areas of operations management, strategy, product development and international business. We thus invited the authors to write an article offering their individual and joint views on the productivity dilemma. We trust you will find it to be stimulating and thought provoking. We invite you to add your voice to the discussion by commenting on this article at the Operations and Supply Chain (OSM) Forum at http://www.journaloperationsmanagement.org/OSM.asp. – Kenneth K. Boyer and Morgan L. Swink

Individual and work characteristics are used in telecommuting plans; however, their impact on telecommuting success is not well known. We studied how employee tenure, work experience, communication skills, task interdependence, work output measurability, and task variety impact telecommuter productivity, performance, and satisfaction after taking into account the impact of communication technologies. Data collected from 89 North American telecommuters suggest that in addition to the richness of the media, work experience, communication skills, and task interdependence impact telecommuting success. These characteristics are practically identifiable and measurable; therefore, we expect our findings to help managers convert increasing telecommuting adoption rates to well-defined and measurable gains.

This article presents projects as powerful strategic weapons, initiated to create economic value and competitive advantage. It suggests that project managers are the new strategic leaders, who must take on total responsibility for project business results. Defining and assessing project success is therefore a strategic management concept, which should help align project efforts with the shortand long-term goals of the organization. While this concept seems simple and intuitive, there is very little agreement in previous studies as to what really constitutes project success. Traditionally, projects were perceived as successful when they met time, budget, and performance goals. However, many would agree that there is more to project success than meeting time and budget. The object of this study was to develop a multidimensional framework for assessing project success, showing how different dimensions mean different things to different stakeholders at different times and for different projects. Given the complexity of this question, a combination of qualitative and quantitative methods and two data sets were used. The analysis identified four major distinct success dimensions: (1) project efficiency, (2) impact on the customer, (3) direct business and organizational success, and (4) preparing for the future. The importance of the dimensions varies according to time and the level of technological uncertainty involved in the project. The article demonstrates how these dimensions should be addressed during the project’s definition, planning, and execution phases, and provides a set of guidelines for project managers and senior managers, as well as suggestions for further research. c 2002 Elsevier Science Ltd. All rights reserved.

It is difficult to understand, let alone improve, the quality of software without the knowledge of its software development process and software products. There must be some measurement process to predict the software development, and to evaluate the software products. This thesis provides a brief view on Software Quality, Software Metrics, and Software Metrics methods that will predict and measure the specified quality factors of software. It further discusses about the Quality as given by the standards such as ISO, principal elements required for the Software Quality and Software Metrics as the measurement technique to predict the Software Quality. This thesis was performed by evaluating a source code developed in Java, using Software Metrics, such as Size Metrics, Complexity Metrics, and Defect Metrics. Results show that, the quality of software can be analyzed, studied and improved by the usage of software metrics.

This paper provides an overview of the latest version of the Capability Maturity Model for Software, CMM v1.1. Based on over six years of experience with software process improvement and the contributions of hundreds of reviewers, CMM v1.1 describes the software engineering and management practices that characterize organizations as they mature their processes for developing and maintaining software. This paper stresses the need for a process maturity framework to prioritize improvement actions, describes the process maturity framework of five maturity levels and the associated structural components, and discusses future directions for the CMM.

Companies are moving towards quickly providing better customer-centric products and services improve market share and market size with continuously growing revenue. As such, the effective collaboration among customers, developers, suppliers, and manufacturers throughout the entire product lifecycle is becoming much more important for the most advanced competitiveness. To address this need, a framework for product lifecycle collaboration is proposed in this study. The details of these collaboration models throughout the entire product lifecycle are depicted. As one of the key elements in product lifecycle collaboration, technology to support collaborative product manufacturing is proposed, developed and implemented in this study. It is hoped that the developed technology for collaborative product manufacturing will lay a frontier basis for further research and development in product lifecycle management. # 2007 Elsevier B.V. All rights reserved.

Software traceability is a sought-after, yet often elusive quality in software-intensive systems. Required in safety-critical systems by many certifying bodies, such as the USA Federal Aviation Authority, software traceability is an essential element of the software development process. In practice, traceability is often conducted in an ad-hoc, after-the-fact manner and, therefore, its benefits are not always fully realized. Over the past decade, researchers have focused on specific areas of the traceability problem, developing more sophisticated tooling, promoting strategic planning, applying information retrieval techniques capable of semi-automating the trace creation and maintenance process, developing new trace query languages and visualization techniques that use trace links, and applying traceability in specific domains such as Model Driven Development, product line systems, and agile project environments. In this paper, we build upon a prior body of work to highlight the state-of-the-art in software traceability, and to present compelling areas of research that need to be addressed.

Using IT in ways that can trigger major organizational changes creates high-risk, potentially high-reward, situations that I call technochange (for technology-driven organizational change). Technochange differs from typical IT projects and from typical organizational change programs and therefore requires a different approach. One major risk in technochange—that people will not use information technology and related work practices—is not thoroughly addressed by the discipline of IT project management, which focuses on project cost, project schedule, and solution functionality. Organizational change management approaches are also generally not effective on their own, because they take as a given the IT ‘‘solutions’’ developed by a technical team. Consequently, the potential for the IT ‘‘solution’’ to be misaligned with important organizational characteristics, such as culture or incentives, is great. Merely combining IT project management and organizational change management approaches does not produce the best results, for two reasons. First, the additive approach does not effectively address the many failure-threatening problems that can arise over the lengthy sequential process of the typical technochange lifecycle. Second, the additive approach is not structured to produce the characteristics of a good technochange solution: a complete intervention consisting of IT and complementary organizational changes, an implementable solution with minimal misfits with the existing organization, and an organization primed to appropriate the potential bene¢ts of the technochange solution. With hard work and care, the combined IT project management plus organizational change approach can be made to work. However, an iterative, incremental approach to implementing technochange can be a better strategy in many situations. The essential characteristic of the technochange prototyping approach is that each phase involves both new IT functionality and related organizational changes, such as redesigned business processes, new performance metrics, and training. Journal of Information Technology (2004) 19, 4–20. doi:10.1057/palgrave.jit.2000002

Most IT experts agree that software failures occur far more often than they should despite the fact that, for the most part, they are predictable and avoidable. It is unfortunate that most organizations don't see preventing failure as an urgent matter, even though that view risks harming the organization and maybe even destroying it. Because software failure has tremendous implications for business and society, it is important to understand why this attitude persists.


Question: Agile team perspectives on elements influencing productivity.

This paper presents a systematic map and review of studies aimed at measuring and predicting software productivity, a critical aspect for controlling and enhancing the performance of software development processes. The study identifies role models, such as successful projects, individuals, and tasks, by comparing productivity data. Prediction methods are essential for determining when corrective actions are required and for selecting the most effective improvement strategies. The objective of this research is to identify and analyze studies on software productivity prediction and measurement. To achieve this, the authors employ systematic mapping and review methods to systematically gather and evaluate evidence from various productivity measurement and prediction approaches. A total of 38 studies were identified, which led to the creation of a classification scheme for empirical research on software productivity. The mapping process allowed the researchers to assess the quality of evidence for different productivity approaches. The detailed analysis and synthesis of the studies provided valuable insights and recommendations for practitioners. The findings highlight the risks associated with simplistic ratio-based measurement approaches. In contrast, data envelopment analysis emerges as a robust method for capturing multivariate productivity measures and identifying reference projects for comparison with less efficient projects. Regarding simulation, no universal prediction model was found, but simulation and statistical process control are deemed promising methods for software productivity prediction. However, the study emphasizes the need for further evidence to make stronger claims and recommendations. Specifically, discussions of validity threats should be a standard practice, and models should be compared against each other to enhance their reliability and effectiveness.

Since 2009, DevOps, the combination of development and operation, has been adopted within organizations in industry, such as Netflix, Flickr, and Fotopedia. Configuration management tools have been used to support DevOps. However, in this paper we investigate which Knowledge, Skills, and Abilities (KSA) have been employed in developing and deploying modern web applications and how these KSAs support DevOps. By applying a qualitative analysis approach, namely grounded theory, to three web application development projects, we discover that the KSAs for both Software Development and IT Operator practitioners support the four perspectives of DevOps: collaboration culture, automation, measurement, and sharing.

Requirements (re)prioritization is an essential mechanism of agile development approaches to maximize the value for the clients and to accommodate changing requirements. Yet, in the agile Requirements Engineering (RE) literature, very little is known about how agile (re)prioritization happens in practice. Conceptual models about this process are missing, which, in turn, makes it difficult for both practitioners and researchers to reason about requirements decision-making at inter-iteration time. We did a multiple case study on agile requirements prioritization methods to yield a conceptual model for understanding the inter-iteration prioritization process. The model is derived by using interview data from practitioners in 8 development organizations. Such a model makes explicit the concepts that are used tacitly in the agile requirements prioritization practice and can be used for structuring future empirical investigations about this topic, and for analyzing, supporting, and improving the process in real-life projects.

A description is given of a software-process maturity framework that has been developed to provide the US Department of Defense with a means to characterize the capabilities of software-development organizations. This software-development process-maturity model reasonably represents the actual ways in which software-development organizations improve. It provides a framework for assessing these organizations and identifying the priority areas for immediate improvement. It also helps identify those places where advanced technology can be most valuable in improving the software-development process. The framework can be used by any software organization to assess its own capabilities and identify the most important areas for improvement.<<ETX>>

People working collaboratively must establish and maintain awareness of one another’s intentions, actions and results. Notification systems typically support awareness of the presence, tasks and actions of collaborators, but they do not adequately support awareness of persistent and complex activities. We analysed awareness breakdowns in use of our Virtual School system—stemming from problems related to the collaborative situation, group, task and tool support—to motivate the concept of activity awareness. Activity awareness builds on prior conceptions of social and action awareness, but emphasizes the importance of activity context factors like planning and coordination. This work suggests design strategies for notification systems to better support collaborative activity. r 2003 Elsevier Science Ltd. All rights reserved.

Software inspections, reviews, and walkthroughs have become a standard process component in many software development domains. Maturity level 3 of the CMM-I requires establishment of peer reviews [12] and substantial sustained improvements in quality and productivity have been reported as a result of using reviews ([16], [21], [22], [27]). The NSF Impact project identifies the degree to which these industrial success cases have been instigated and improved by research in software engineering.
 This research identifies that there is widespread adoption of inspections, reviews or walkthroughs but that companies do not generally exploit their full potential. However there exist sustained industrial success cases with respect to the wide-spread and measurably successful application of them. It also identifies research in software engineering that can be credibly documented as having influenced the industrial success cases. Credible documentation may exist in the form of publications or documented reports by witnesses. Due to the semi-formal nature of inspections, reviews, and walkthroughs, a specific focus is given to empirical research results as motivators for adoption. Through the examination of one detailed case study, it is shown that software engineering research has had a significant impact on practice and that the impact can be traced in this case from research to that practice. The case study chosen provides evidence of both success and failure regarding sustained application in practice.
 Thus the analysis of historic impact chains of research reveals a clear impact of software engineering research on sustained industrial success for inspections, reviews and walkthroughs. More importantly, in impact chains where the empirical results have not been established, we conclude that success has not been achieved or has not been sustained.
 The paper closes with (1) lessons learned for creating the sustained use and impact of semi-formal software engineering processes, (2) a request for researchers and practitioners to further consider how their work can improve the effectiveness of research and practice, and (3) a request to contribute additional success cases and impact factors to the authors database for future enhancements of this paper.

This case focuses on the applicability of the Scaled Agile Framework (SAFe) founded by Dean Leffingwell. Modern organizations often work with agile software engineering teams using traditional single team-level methods like Scrum, but multiple teams and the program or portfolio level are not part of methods like Scrum. SAFe tries to apply agile methodologies to the whole organisation. The real world example focuses on a key element of SAFe, the Program Increment (PI) planning meeting and how it can improve multiple team collaboration.

Computational Thinking (CT) has been recognized as one of the fundamental skills that all graduates should acquire. For this reason, motivational concerns need to be addressed at an early age of a child, and reaching students who do not consider themselves candidates for science, technology, engineering, and mathematics disciplines is important as well if the broadest audience possible is to be engaged. This article describes a framework for teaching and assessing CT in the context of K-12 education. The framework is based on Agile software engineering methods, which rely on a set of principles and practices that can be mapped to the activities of CT. The article presents as well the results of an experiment applying this framework in two sixth-grade classes, with 42 participants in total. The results show that Agile software engineering methods are effective at teaching CT in middle schools, after the addition of some tasks to allow students to explore, project, and experience the potential product before using the software tools at hand. Moreover, according to the teachers’ feedback, the students reached all the educational objectives of the topics involved in the multidisciplinary activities. This result can be taken as an indicator that it is possible to use computing as a medium for teaching other subjects, besides computer science.

Background: Noise, dened as an unwanted sound, is one of the commonest factors that could aect people’s performance in their daily work activities. e soware engineering research community has marginally investigated the eects of noise on soware engineers’ performance. Aims: We studied if noise aects soware engineers’ performance in: (i) comprehending functional requirements and (ii) xing faults in source code. Method: We conducted two experiments with nal-year undergraduate students in Computer Science. In the rst experiment, we asked 55 students to comprehend functional requirements exposing them or not to noise, while in the second experiment 42 students were asked to x faults in Java code. Results: e participants in the second experiment, when exposed to noise, had signicantly worse performance in xing faults in source code. On the other hand, we did not observe any statistically signicant dierence in the rst experiment. Conclusions: Fixing faults in source code seems to be more vulnerable to noise than comprehending functional requirements.

Gamification is the use of game design elements in non-game context platforms such as services and marketing to motivate people to participate in planned activities to increase engagement and loyalty to achieve goals.
 Gamification has been applied to academic fields including software engineering in recent years. Some studies show that gamification can motivate engineers in Software Engineering (SE) if applied appropriately. However, most gamification implementations are lacking well-defined frameworks or models.
 This paper develops a software gamification model (SGM) with a well-defined framework that provides a robust process for implementing gamification for SE. This model also contains elements from applied psychology, Social Software Engineering (SSE), and the Capability Maturity Model (CMM). Having those elements ensures that the model has a solid foundation in gamification and SE disciplines. The model is further tailored for cross-cultural software development teams (CCSDT).
 CCSDT have been popular in recent years due to the fact that software development has become a global business. However, as more and more CCSDT are formed, many challenges and issues have been raised in those cross-cultural environments stemming from miscommunication, misunderstanding, cultural differences and conflicts. This paper uses the SGM to help resolve the issues.

Context: Continuous deployment (CD) is an emerging software development process with organisations such as Facebook, Microsoft, and IBM successfully implementing and using the process. The CD process aims to immediately deploy software to customers as soon as new code is developed, and can result in a number of benefits for organizations, such as: new business opportunities, reduced risk for each release, and prevent development of wasted software. There is little academic literature on the challenges organisations face when adopting the CD process, however there are many anecdotal challenges that organisations have voiced on their online blogs. Objective: The aim of this research is to examine the challenges faced by organisations when adopting CD as well as the strategies to mitigate these challenges. Method: An explorative case study technique that involves in-depth interviews with software practitioners in an organisation that has adopted CD was conducted to identify these challenges. Results: This study found a total of 20 technical and social adoption challenges that organisations may face when adopting the CD process. The results are discussed to gain a deeper understanding of the strategies employed by organisations to mitigate the impacts of these challenges. Conclusion: While a number of individual technical and social adoption challenges were uncovered by the case study in this research, most challenges were not faced in isolation. The severity of these challenges were reduced by a number of mitigation strategies employed by the case study organization. It is concluded that organisations need to be well prepared to handle technical and social adoption challenges with their existing expertise, processes and tools before adopting the CD


Question: Agile team perspectives on the determinants of productivity.

This paper offers an in-depth exploration of the productivity factors and strategies pertinent to software development, addressing the longstanding challenge that has preoccupied both academic circles and the software industry since the late 1970s. Despite extensive research, software organizations often struggle to identify the most impactful factors and devise effective responses. Many studies provide a cursory analysis of these factors, some focus solely on the relevant ones, while others delve into a single factor in isolation. Moreover, the actions to address these factors are scattered and often not systematically mapped. By conducting a comprehensive literature review, this paper synthesizes the predominant factors that have influenced productivity throughout the years, along with contemporary strategies to tackle them. The objective of this research is to assist the software development industry in choosing the most suitable strategies to enhance productivity by amplifying positive factors and mitigating or preventing the adverse effects of negative ones. This approach aims to provide a holistic perspective that can guide organizations in optimizing their productivity enhancement efforts.

0950-5849/$ see front matter 2010 Elsevier B.V. A doi:10.1016/j.infsof.2010.03.009 * Corresponding author. E-mail addresses: rafaelp@pucrs.br (R. Prikladnicki) Context: Distributed Software Development (DSD) has recently become an active research area. Although considerable research effort has been made in this area, as yet, no agreement has been reached as to an appropriate process model for DSD. Purpose: This paper is intended to identify and synthesize papers that describe process models for distributed software development in the context of overseas outsourcing, i.e. ‘‘offshoring”. Method: We used a systematic review methodology to search seven digital libraries and one topic-specific conference. Results: We found 27 primary studies describing stage-related DSD process models. Only five of such studies looked into outsourcing to a subsidiary company (i.e. ‘‘internal offshoring”). Nineteen primary studies addressed the need for DSD process models. Eight primary studies and three literature surveys described stage-based DSD process models, but only three of such models were empirically evaluated. Conclusion: We need more research aimed at internal offshoring. Furthermore, proposed models need to be empirically validated. 2010 Elsevier B.V. All rights reserved.

Gamification is the use of game design elements in non-game context platforms such as services and marketing to motivate people to participate in planned activities to increase engagement and loyalty to achieve goals.
 Gamification has been applied to academic fields including software engineering in recent years. Some studies show that gamification can motivate engineers in Software Engineering (SE) if applied appropriately. However, most gamification implementations are lacking well-defined frameworks or models.
 This paper develops a software gamification model (SGM) with a well-defined framework that provides a robust process for implementing gamification for SE. This model also contains elements from applied psychology, Social Software Engineering (SSE), and the Capability Maturity Model (CMM). Having those elements ensures that the model has a solid foundation in gamification and SE disciplines. The model is further tailored for cross-cultural software development teams (CCSDT).
 CCSDT have been popular in recent years due to the fact that software development has become a global business. However, as more and more CCSDT are formed, many challenges and issues have been raised in those cross-cultural environments stemming from miscommunication, misunderstanding, cultural differences and conflicts. This paper uses the SGM to help resolve the issues.

Meeting stakeholders requirements and expectations becomes one of the critical aspects on which any software organization in market-driven environment focus on, and pays a lot of efforts and expenses to maximize the satisfaction of their stakeholders. Therefore identifying the software product release contents becomes one of the critical decisions for software product success. Requirements prioritization refers to that activity through which product releases contents that maximize stakeholder satisfaction can be identified. This makes it one of the most important component of software requirement decision support in incremental software development [8]. This paper illustrates the Criteria-Based requirement prioritization approach for software product management. The technique proposed on this paper designed based on the Hierarchical Cumulative Voting (HCV) and Value-Oriented Prioritization (VOP) techniques. The proposed technique, Value-Oriented HCV (VOHCV) can select the best candidate requirements for each release based on the stakeholders input values for each requirement. These values reflect the importance of each requirement in terms of associated anticipated cost, technical risk, relative impact, market-related aspects and perceived value to the stakeholder. The VOHCV inherits the strengths of the HCV and VOP techniques. It also provides a mechanism that takes different stakeholders’ aspects into account while selecting the best candidate release requirement, to maximize stakeholders’ value and satisfaction [11].

Team SA involves a common perspective between two or more individuals regarding current environmental events, their meaning, and projected future status. Team SA has been theorized to be important for resuscitation team effectiveness. Accordingly, multidimensional frameworks of observable behaviors relevant to resuscitation teams are needed to understand more deeply the nature of team SA, its implications for team effectiveness, and whether it can be trained. A seven-dimension team resuscitation SA framework was developed following a literature review and consensus process using a modified Delphi approach with a group of content experts. We applied a pre-post design within a day-long team training program involving four video-recorded simulated resuscitation events and 42 teams across Canada. The first and fourth events represented "pre" and "post" training events, respectively. Teams were scored on SA five times within each 15-minute event. Distractions were introduced to investigate whether SA scores would be affected. The current study provides initial construct validity evidence for a new measure of SA and explicates SA's role in resuscitation teams.

The paper focuses on the analysis and optimization of production warehouses, proposing a novel approach to reduce inefficiencies which employs three lean manufacturing tools in an integrated and iterative framework. The proposed approach integrates the Unified Modeling Language (UML) – providing a detailed description of the warehouse logistics – the Value Stream Mapping (VSM) tool – identifying non-value adding activities – and a mathematical formulation of the so-called Genba Shikumi philosophy – ranking such system anomalies and assessing how they affect the warehouse. The subsequent reapplication of the VSM produces a complete picture of the reengineered warehouse, and using the UML tool allows describing in detail the updated system. By applying the presented methodology to the warehouse of an Italian interior design producer, we show that it represents a useful tool to systematically and dynamically improve the warehouse management. Indeed, the application of the approach to the company leads to an innovative proposal for the warehouse analysis and optimization: a warehouse management system that leads to increased profitability and quality as well as to reduced errors. 2014 Elsevier B.V. All rights reserved.

The software engineering process in video game development is not clearly understood, hindering the development of reliable practices and processes for this field. An investigation of factors leading to success or failure in video game development suggests that many failures can be traced to problems with the transition from preproduction to production. Three examples, drawn from real video games, illustrate specific problems: 1) how to transform documentation from its preproduction form to a form that can be used as a basis for production;, 2) how to identify implied information in preproduction documents; and 3) how to apply domain knowledge without hindering the creative process. We identify 3 levels of implication and show that there is a strong correlation between experience and the ability to identify issues at each level. The accumulated evidence clearly identifies the need to extend traditional requirements engineering techniques to support the creative process in video game development.

BACKGROUND The software intensive industry is moving towards the adoption of a value-driven and adaptive real-time business paradigm. The traditional view of software as an item that evolves through releases every few months is being replaced by continuous evolution of software functionality. OBJECTIVE This study aims to classify and analyse literature related to continuous deployment in the software domain in order to scope the phenomenon, provide an overview of its state-of-the-art, investigate the scientific evidence in the reported results and identify areas that are suitable for further research. METHOD We conducted a systematic mapping study and classified the continuous deployment literature. The benefits and challenges related to continuous deployment were also analyzed. RESULTS The systematic mapping study includes 50 primary studies published between 2001 and 2014. An in-depth analysis of the primary studies revealed ten recurrent themes that characterize continuous deployment and provide researchers with directions for future work. In addition, a set of benefits and challenges of which practitioners may take advantage were identified. CONCLUSION Overall, although the topic area is very promising, it is still in its infancy, thus offering a plethora of new opportunities for both researchers and software intensive companies.

It is well documented that software product cost estimates are notoriously inaccurate across the software industry. Creating accurate cost estimates for software product development projects early in the product development lifecycle has always been a challenge for the industry. This article describes how a large multi-team software engineering organization (over 450 engineers) estimates project cost accurately and early in the software development lifecycle using Use Case Points, and the process of evaluating metrics to ensure the accuracy of the model.The engineering teams of Agilis Solutions in partnership with FPT Software, provide our customers with accurate estimates for software product projects early in the product lifecycle. The bases for these estimates are initial definitions of Use Cases, given point factors and modified for technical and environmental factors according to the Use Case Point method defined within the Rational Unified Process. After applying the process across hundreds of sizable (60 man-months average) software projects, we have demonstrated metrics that prove an estimating accuracy of less than 9% deviation from actual to estimated cost on 95% of our projects. Our process and this success factor is documented over a period of five years, and across more than 200 projects.

Users can be involved in the design process in several ways. The author focuses on user-centred design, participatory design, ethnography, and contextual design. She briefly describes each approach and cites the corresponding literature. The expected benefits of these approaches highly overlap. Methods based on early user involvement promise to avoid the implementation of costly features that users do not want or cannot use. Participatory methods promise to improve the user satisfaction and the acceptance of a system. Nearly all approaches intend to improve the overall usability of the system and by this means increase the productivity and decrease the training costs and the need of user support.

In this paper we introduce SAMOD, a.k.a. Simplified Agile Methodology for Ontology Development, a novel agile methodology for the development of ontologies by means of small steps of an iterative workflow that focuses on creating well-developed and documented models starting from exemplar domain descriptions. RASH: https://w3id.org/people/essepuntato/papers/samod-owled2016.html


Question: Agile team perspectives on the determinants of productivity.

This paper explores the influence of agile methodologies, specifically eXtreme Programming (XP) and SCRUM, on communication dynamics within software development contexts. Agile practices have gained traction as a response to the dynamic and unpredictable nature of contemporary business environments, characterized by rapid market and technological changes. Despite the positive outcomes reported, the specific effects of agile practices on communication channels have remained relatively unexplored. To address this gap, a case study was conducted at F-Secure, focusing on two agile software development projects. The investigation aimed to elucidate the impact of XP and SCRUM practices on internal communication among developers and project leaders, as well as the external communication between the development team and stakeholders, including customers, testers, and other development teams. The findings reveal that agile practices enhance both informal and formal communication mechanisms. However, the study also highlights potential challenges, particularly in larger development settings with multiple external stakeholders, where mismatches in communication strategies can occasionally impede effective information exchange. Importantly, the research underscores the dual role of communication in shaping feature requirements and task dependencies, as posited by coordination theory. While SCRUM and certain XP practices bolster team and organizational communication regarding dependencies between product features and tasks, the adoption of agile practices necessitates the concurrent implementation of additional plan-driven practices to optimize external communication across all software development stakeholders.

It has been suggested that there is more than one reason for a software development project to fail. However, most of the literature that discusses project failure tends to be rather general, supplying us with lists of risk and failure factors, and focusing on the negative business effects of the failure. Very little research has attempted an in-depth investigation of a number of failed projects to identify exactly what are the factors behind the failure. In this research we analyze data from 70 failed projects. This data provides us with practitionerspsila perspectives on 57 development and management factors for projects they considered were failures. Our results show that all projects we investigated suffered from numerous failure factors. For a single project the number of such factors ranges from 5 to 47. While there does not appear to be any overarching set of failure factors we discovered that all of the projects suffered from poor project management. Most projects additionally suffered from organizational factors outside the project managerpsilas control. We conclude with suggestions for minimizing the four most common failure factors.

Decoding the important differences in terminology, underlying philosophy, and value systems between two similar categories of software.

Although many view iterative and incremental development as a modern practice, its application dates as far back as the mid-1950s. Prominent software-engineering thought leaders from each succeeding decade supported IID practices, and many large projects used them successfully. These practices may have differed in their details, but all had a common theme-to avoid a single-pass sequential, document-driven, gated-step approach.

Business Process Management (BPM) has been identified as the number one business priority by a recent Gartner study (Gartner, 2005). However, BPM has a plethora of facets as its origins are in Business Process Reengineering, Process Innovation, Process Modelling, and Workflow Management to name a few. Organisations increasingly recognize the requirement for an increased process orientation and require appropriate comprehensive frameworks, which help to scope and evaluate their BPM initiative. This research project aims toward the development of a holistic and widely accepted BPM maturity model, which facilitates the assessment of BPM capabilities. This paper provides an overview about the current model with a focus on the actual model development utilizing a series of Delphi studies. The development process includes separate studies that focus on further defining and expanding the six core factors within the model, i.e. strategic alignment, governance, method, Information Technology, people and culture.

Good software engineers are essential to the creation of good software. However, most of what we know about software-engineering expertise are vague stereotypes, such as 'excellent communicators' and 'great teammates'. The lack of specificity in our understanding hinders researchers from reasoning about them, employers from identifying them, and young engineers from becoming them. Our understanding also lacks breadth: what are all the distinguishing attributes of great engineers (technical expertise and beyond)? We took a first step in addressing these gaps by interviewing 59 experienced engineers across 13 divisions at Microsoft, uncovering 53 attributes of great engineers. We explain the attributes and examine how the most salient of these impact projects and teams. We discuss implications of this knowledge on research and the hiring and training of engineers.

Companies are moving towards quickly providing better customer-centric products and services improve market share and market size with continuously growing revenue. As such, the effective collaboration among customers, developers, suppliers, and manufacturers throughout the entire product lifecycle is becoming much more important for the most advanced competitiveness. To address this need, a framework for product lifecycle collaboration is proposed in this study. The details of these collaboration models throughout the entire product lifecycle are depicted. As one of the key elements in product lifecycle collaboration, technology to support collaborative product manufacturing is proposed, developed and implemented in this study. It is hoped that the developed technology for collaborative product manufacturing will lay a frontier basis for further research and development in product lifecycle management. # 2007 Elsevier B.V. All rights reserved.

Software development is usually a collaborative venture. Open Source Software (OSS) projects are no exception; indeed, by design, the OSS approach can accommodate teams that are more open, geographically distributed, and dynamic than commercial teams. This, we find, leads to OSS teams that are quite diverse. Team diversity, predominantly in offline groups, is known to correlate with team output, mostly with positive effects. How about in OSS? Using GitHub, the largest publicly available collection of OSS projects, we studied how gender and tenure diversity relate to team productivity and turnover. Using regression modeling of GitHub data and the results of a survey, we show that both gender and tenure diversity are positive and significant predictors of productivity, together explaining a sizable fraction of the data variability. These results can inform decision making on all levels, leading to better outcomes in recruiting and performance.

While face-to-face interaction is fundamental in agile software development, distributed environments must rely extensively on mediated interactions. Practicing agile principles in distributed environments therefore poses particular control challenges related to balancing fixed vs. evolving quality requirements and people vs. process-based collaboration. To investigate these challenges, we conducted an in-depth case study of a successful agile distributed software project with participants from a Russian firm and a Danish firm. Applying Kirsch’s elements of control framework, we offer an analysis of how control was enacted through the project context and in the participants’ mediated communication. The analysis reveals that formal measurement and evaluation control were persistently enacted through mediated communication. These formal control practices were, however, predominantly carried out in conjunction with informal roles and relationships such as clan-like control inherent in agile development. Overall, the study demonstrates that, if appropriately applied, communication technologies can significantly support distributed, agile practices by allowing concurrent enactment of both formal and informal controls. The paper discusses these findings as they relate to previous research and concludes with their implications for future research.

Innovation, the development and intentional introduction of new and useful ideas by individuals, teams, and organizations, lies at the heart of human adaptation. Decades of research in different disciplines and at different organizational levels have produced a wealth of knowledge about how innovation emerges and the factors that facilitate and inhibit innovation. We propose that this knowledge needs integration. In an initial step toward this goal, we apply a dialectic perspective on innovation to overcome limitations of dichotomous reasoning and to gain a more valid account of innovation. We point out that individuals, teams, and organizations need to self-regulate and manage conflicting demands of innovation and that multiple pathways can lead to idea generation and innovation. By scrutinizing the current use of the concept of organizational ambidexterity and extending it to individuals and teams, we develop a framework to help guide and facilitate future research and practice. Readers expecting specific and universal prescriptions of how to innovate will be disappointed as current research does not allow such inferences. Rather, we think innovation research should focus on developing and testing principles of innovation management in addition to developing decision aids for organizational practice. To this end, we put forward key propositions and action principles of innovation management. Dialectic Perspective on Innovation 3 A Dialectic Perspective on Innovation: Conflicting Demands, Multiple Pathways, and Ambidexterity Throughout this paper we use the term creativity for the generation of new and useful ideas and that of innovation to include both creative ideas and their implementation. Innovation can take different forms, including technological innovation, product and service innovation, and process innovation. The importance of innovation is widely acknowledged by organizational scholars, practitioners, and the wider society in an economic environment characterized by fierce competition, rapid change, and the global challenges of climate change and economic booms and busts. Decades of research have produced a wealth of knowledge about the characteristics of individuals, teams, and organizations that are related to outcomes of innovation (e.g., Anderson, De Dreu, & Nijstad, 2004; Damanpour, 1991). Some of these findings converge around factors that have been reliably found to influence innovation, such as a shared vision, innovative organizational culture (Miron, Erez, & Naveh, 2004; Naveh & Erez, 2004), emphasis on exploration rather than exploitation, and investment in R&D (Zahra & George, 2002; Cohen & Levinthal, 1990). Findings with respect to other factors, such as team diversity (Gibson & Gibbs, 2006), task related conflict, monetary rewards (Amabile, 2000; Eisenberger & Rhoades, 2001) remain contradictory. While we think that the scientific understanding of innovation is an important endeavor in its own right, we also suggest that the impact of scientific knowledge about innovation can be improved in organizational practice. While many reasons may account for a lack of transfer of scientific knowledge to management practices, one reason may be that the scientific findings do not readily or easily produce actionable knowledge. On the other hand, simplistically inferring practical implications or trying to be overly prescriptive can do harm, particularly if the context of an individual, team, or organization is not Dialectic Perspective on Innovation 4 taken into account. We, therefore, chose to integrate empirical findings of the extant literature with an attempt to develop a set of broad principles of innovation management that can guide decision making and action in organizations. We base this integration on a perspective on innovation which we term “dialectic”; we present and develop this perspective below. Toward this goal we offer three contributions to the literature: • By developing and applying a dialectic perspective on innovation, we aim to gain a more valid account of innovation in organizations that can enrich research and practice. • By reviewing core findings about innovation we illustrate how multiple pathways can lead to idea generation and innovation. • By redefining and extending the concept of ambidexterity, we propose a cross-level framework for the successful management of inherently conflicting demands of innovation. Tensions of Innovation: Theoretical Perspectives A pervasive theme in research on organizational innovation is that innovation is characterized by tensions (Lewis, Welsh, Dehler, & Green, 2002), paradoxes (Miron et al., 2004), contradictions (King, Anderson, & West, 1991), dilemmas (Benner & Tushman, 2003), and the so-called “dark side” of innovation processes (Anderson & Gasteiger, 2007). Table 1 presents a number of examples of tensions related to innovation that have been noted in the published literature. We organize Table 1 by the referent level of the tension (individual, team, or organizational) and by whether the tension is primarily focused on antecedents of innovation or on innovative processes and outcomes. That tensions have been described frequently at all levels of analysis and with regard to antecedents, processes, and consequences of innovation provides Dialectic Perspective on Innovation 5 what we think is compelling evidence for their pervasiveness within organizations attempting to innovate. -----------------------------Insert Table 1 about here -----------------------------We propose with others that understanding and managing these tensions is central to successful innovation and use the terms conflicting demands and conflicting activities to refer to the origins of tensions, paradoxes, contradictions and dilemmas. In the following we contrast two theoretical perspectives and the strategies they imply for dealing with these tensions. One strategy deals with tensions by emphasizing the separation of conflicting activities to different sub-organizations or even different organizations altogether (O'Reilly & Tushman, 2004). The top management of the organization is responsible for the necessary integration of activities that produce the tensions. In a way, this strategy deals with tensions by reducing them as much as possible. This strategy derives from a dichotomous theory perspective (March, Sproull, & Tamuz, 1991). We contrast the dichotomous approach with a second theoretical perspective which argues that a strict separation of conflicting activities to sub-organizations leads to disadvantages. Given that a system has sufficient levels of internal complexity (Brown & Eisenhardt, 1997), the tensions should be kept within the system to be managed rather than organized “out” of the system. Both the dichotomous (“keep separate”) and dialectic (“integrate and manage”) perspectives concur that the innovation process poses potentially conflicting task demands on individuals, teams, and organizations. By task demands we refer to the patterns of requisite Dialectic Perspective on Innovation 6 activity an individual, team, or organization must engage in to achieve an outcome. Innovation confronts individuals, teams, and organizations with fundamentally different demands in several important and unavoidable ways: First, the demands of innovation differ from the demands of routine performance. Whereas routine performance is based on the exploitation of knowledge, skills, and abilities that emphasize quality and efficiency criteria, innovation requires exploratory action and creative thinking. People and teams who need to be creative and innovative must crave newness and be curious, while people and teams who are supposed to produce efficiently must be able to close their minds to new ideas that just interrupt the clear pattern of existing routines and hinder the further development of those routines into ever more efficient production. Second, the innovation process itself encompasses different sets of activities, such as those related to idea generation and innovation implementation: These sets of activities are linked to different or conflicting antecedents. For instance, granting autonomy is linked to the generation of new ideas (Shalley, Zhou, & Oldham, 2004), while initiating structure is related to the success of implementing incremental innovation (Keller, 2006). Maximizing the conditions fostering creativity is unlikely to translate directly into innovation because innovation encompasses much more than idea generation. Indeed, the maximization of factors that facilitate the development of new ideas is likely to simultaneously cause conditions that may inhibit idea implementation, and thus innovation overall. For example, Xerox Parc developed many innovations in software design, PC hardware and PC connectivity. The creativity of this group was enormous. And these innovations were often implemented in products. However, Xerox made little economic use of these enormously creative new products that essentially were fed into innovations marketed by Apple and Microsoft (Bergin, 2006; Miller & Steinberg, 2006). Dialectic Perspective on Innovation 7 Third, in addition, there are different types of innovation: An innovation is incremental when it builds on and exploits existing products and processes; an innovation is radical or disruptive if it departs strongly from the status quo (Benner & Tushman, 2003). Incremental innovation leads to expected increases in mean levels of performance, while radical innovation creates variability in performance (potential for high losses or high returns). The expected level of returns is lower for radical than for incremental innovation (Taylor & Greve, 2006). We assume with others that for radical innovation the problem of conflicting task demands of innovation is more pronounced than for incremental innovation and the management of tensions is particularly challenging (Christensen, 1997). But even incremental inn

This study brings in the task interdependence as the antecedent for growing team social capital and increasing knowledge sharing among team members in IS project context in which heterogeneous members need to interact very closely. Data collected from 203 IS projects largely confirm the proposed research model. Between the task interdependence and team performance, the team social capital as well as the knowledge sharing among members fully mediates the relationship. Interestingly, direct path from task interdependence onto performance is found to be insignificant, rebutting the suggestions of the work design theory which says well designed interdependence directly increase performance in heterogeneous teams. Findings of our study signify the criticality of the mediating roles of social capital and knowledge sharing. Additionally, it is also confirmed that the social capital grows with time. Also, longer term projects revealed a bit different mechanism than shorter ones. Implications are discussed with limitations and further studies.


Question: Agile team perspectives on elements influencing productivity.

In the rapidly evolving landscape of the software industry, the importance of agility and innovation has become paramount. Agile software development methodologies, including Extreme Programming, Crystal methods, Lean Development, Scrum, Adaptive Software Development (ASD), and others, have emerged as critical tools for navigating the unpredictable business and technology environments. These approaches acknowledge the inevitability of change and prioritize customer satisfaction at the point of delivery, rather than rigidly adhering to initial project plans. In a study conducted by Michael Mah of QSM Associates, it was observed that original plans for over half of the 200 software development projects reviewed were no longer applicable, highlighting the need for flexibility in response to changing requirements, scope, and technology. The traditional perspective, which aimed to anticipate and freeze requirements early in the development process, is no longer viable in the face of continuous environmental shifts. The new strategy is not to avoid change, but to manage it effectively and reduce its associated costs. Agile methodologies, by embracing change, strive to maintain quality and responsiveness to market demands. Extreme Programming (XP), for instance, advocates for early and frequent delivery, aiming to secure initial victories and rapid feedback, which are crucial for iterative improvement and innovation. The success of agile methods lies in their ability to minimize the cost of change and rework, thereby fostering a culture of innovation that aligns with the dynamic nature of the modern business environment. This shift in perspective from rigid planning to agile adaptation is essential for organizations seeking to thrive in an era characterized by constant change and heightened customer expectations.

A consequence of the growing number of empirical studies in software engineering is the need to adopt systematic approaches to assessing and aggregating research outcomes in order to provide a balanced and objective summary of research evidence for a particular topic. The paper reports experiences with applying one such approach, the practice of systematic literature review, to the published studies relevant to topics within the software engineering domain. The systematic literature review process is summarised, a number of reviews being undertaken by the authors and others are described and some lessons about the applicability of this practice to software engineering are extracted. The basic systematic literature review process seems appropriate to software engineering and the preparation and validation of a review protocol in advance of a review activity is especially valuable. The paper highlights areas where some adaptation of the process to accommodate the domain-specific characteristics of software engineering is needed as well as areas where improvements to current software engineering infrastructure and practices would enhance its applicability. In particular, infrastructure support provided by software engineering indexing databases is inadequate. Also, the quality of abstracts is poor; it is usually not possible to judge the relevance of a study from a review of the abstract alone. 2006 Elsevier Inc. All rights reserved.

Knowledge Management Software must be embedded in processes of knowledge workers' everyday practice. In order to attain a seamless design, regarding the special qualities and requirements of knowledge work, detailed studies of the existing work processes and analysis of the used knowledge are necessary. Participation of the knowledge owners and future users us an important factor for success of knowledge management systems. In this paper we describe characteristics of knowledge work motivating the usage of participatory design techniques. We suggest a design process for developing or improving knowledge management, which includes ethnographic surveys, user participation in cyclic improvement, scenario based design, and the use of multiple design artifacts and documents. Finally we explain the benefits of our approach. The paper is based on a case study we carried out to design and introduce a knowledge management system in a training company.

Background/aims
The idea that champions are crucial to effective healthcare-related implementation has gained broad acceptance; yet the champion construct has been hampered by inconsistent use across the published literature. This integrative review sought to establish the current state of the literature on champions in healthcare settings and bring greater clarity to this important construct.

Methods
This integrative review was limited to research articles in peer-reviewed, English-language journals published from 1980 to 2016. Searches were conducted on the online MEDLINE database via OVID and PubMed using the keyword "champion." Several additional terms often describe champions and were also included as keywords: implementation leader, opinion leader, facilitator, and change agent. Bibliographies of full-text articles that met inclusion criteria were reviewed for additional references not yet identified via the main strategy of conducting keyword searches in MEDLINE. A five-member team abstracted all full-text articles meeting inclusion criteria.

Results
The final dataset for the integrative review consisted of 199 unique articles. Use of the term champion varied widely across the articles with respect to topic, specific job positions, or broader organizational roles. The most common method for operationalizing champion for purposes of analysis was the use of a dichotomous variable designating champion presence or absence. Four studies randomly allocated of the presence or absence of champions.

Conclusions
The number of published champion-related articles has markedly increased: more articles were published during the last two years of this review (i.e. 2015-2016) than during its first 30 years (i.e. 1980-2009).The number of champion-related articles has continued to increase sharply since the year 2000. Individual studies consistently found that champions were important positive influences on implementation effectiveness. Although few in number, the randomized trials of champions that have been conducted demonstrate the feasibility of using experimental design to study the effects of champions in healthcare.

Context There is extensive interest in global software development (GSD) which has led to a large number of papers reporting on GSD. A number of systematic literature reviews (SLRs) have attempted to aggregate information from individual studies. Objective: We wish to investigate GSD SLR research with a focus on discovering what research has been conducted in the area and to determine if the SLRs furnish appropriate risk and risk mitigation advice to provide guidance to organizations involved with GSD. Method: We performed a broad automated search to identify GSD SLRs. Data extracted from each study included: (1) authors, their affiliation and publishing venue, (2) SLR quality, (3) research focus, (4) GSD risks, (5) risk mitigation strategies and, (6) for each SLR the number of primary studies reporting each risk and risk mitigation strategy. Results: We found a total of 37 papers reporting 24 unique GSD SLR studies. Major GSD topics covered include: (1) organizational environment, (2) project execution, (3) project planning and control and (4) project scope and requirements. We extracted 85 risks and 77 risk mitigation advice items and categorized them under four major headings: outsourcing rationale, software development, human resources, and project management. The largest group of risks was related to project management. GSD outsourcing rationale risks ranked highest in terms of primary study support but in many cases these risks were only identified by a single SLR. Conclusions: The focus of the GSD SLRs we identified is mapping the research rather than providing evidence-based guidance to industry. Empirical support for the majority of risks identified is moderate to low, both in terms of the number of SLRs identifying the risk, and in the number of primary studies providing empirical support. Risk mitigation advice is also limited, and empirical support for these items is low. 2013 Elsevier B.V. All rights reserved.

Simulation is frequently used for training in many application areas like aviation and economics, but not in software engineering. We present the SESAM project which focuses on software engineering education using simulation. In the SESAM project a simulator was developed. Using this simulator, a student can take the role of a software project manager. The simulated software project can be finished within a couple of hours because it is simulated in “quick-motion” mode.
In this paper, the background and goals of the SESAM project are presented. A new simulation model, the so called QA model, is introduced. The model behavior is demonstrated by investigating and comparing different strategies for software development. The results of experiments based on the QA model are reported. Finally, conclusions are drawn from the experiments and future work is outlined.

A study of a spatially distributed product design team shows that most members are rarely at their individual desks. Mobility is essential for the use of shared resources and for communication. It facilitates informal interactions and awareness unavailable to colleagues at remote sites. Implications for technology design include portable and distributed computing resources, in particular, moving beyond individual workstation-centric CSCW applications.

A Project Scheduling Problem consists in deciding who does what during the software project lifetime. This is a capital issue in the practice of software engineering, since the total budget and human resources involved must be managed optimally in order to end in a successful project. In short, companies are principally concerned with reducing the duration and cost of projects, and these two goals are in conflict with each other. In this work we tackle the problem by using genetic algorithms (GAs) to solve many different software project scenarios. Thanks to our newly developed instance generator we can perform structured studies on the influence the most important problem attributes have on the solutions. Our conclusions show that GAs are quite flexible and accurate for this application, and an important tool for automatic project management. 2007 Elsevier Inc. All rights reserved.

Software inspections, reviews, and walkthroughs have become a standard process component in many software development domains. Maturity level 3 of the CMM-I requires establishment of peer reviews [12] and substantial sustained improvements in quality and productivity have been reported as a result of using reviews ([16], [21], [22], [27]). The NSF Impact project identifies the degree to which these industrial success cases have been instigated and improved by research in software engineering.
 This research identifies that there is widespread adoption of inspections, reviews or walkthroughs but that companies do not generally exploit their full potential. However there exist sustained industrial success cases with respect to the wide-spread and measurably successful application of them. It also identifies research in software engineering that can be credibly documented as having influenced the industrial success cases. Credible documentation may exist in the form of publications or documented reports by witnesses. Due to the semi-formal nature of inspections, reviews, and walkthroughs, a specific focus is given to empirical research results as motivators for adoption. Through the examination of one detailed case study, it is shown that software engineering research has had a significant impact on practice and that the impact can be traced in this case from research to that practice. The case study chosen provides evidence of both success and failure regarding sustained application in practice.
 Thus the analysis of historic impact chains of research reveals a clear impact of software engineering research on sustained industrial success for inspections, reviews and walkthroughs. More importantly, in impact chains where the empirical results have not been established, we conclude that success has not been achieved or has not been sustained.
 The paper closes with (1) lessons learned for creating the sustained use and impact of semi-formal software engineering processes, (2) a request for researchers and practitioners to further consider how their work can improve the effectiveness of research and practice, and (3) a request to contribute additional success cases and impact factors to the authors database for future enhancements of this paper.

In today’s business where speed is of essence, an iterative development approach that allows the functionality to be delivered in parts has become a necessity and an effective way to manage risks. In an iterative process, the development of a software system is done in increments, each increment forming of an iteration and resulting in a working system. A common iterative approach is to decide what should be developed in an iteration and then plan the iteration accordingly. A somewhat different iterative is approach is to time box different iterations. In this approach, the length of an iteration is fixed and what should be developed in an iteration is adjusted to fit the time box. Generally, the time boxed iterations are executed in sequence, with some overlap where feasible. In this paper we propose the timeboxing process model that takes the concept of time boxed iterations further by adding pipelining concepts to it for permitting overlapped execution of different iterations. In the timeboxing process model, each time boxed iteration is divided into equal length stages, each stage having a defined function and resulting in a clear work product that is handed over to the next stage. With this division into stages, pipelining concepts are employed to have multiple time boxes executing concurrently, leading to a reduction in the delivery time for product releases. We illustrate the use of this process model through an example of a commercial project that was successfully executed using the proposed model.

In a large, long-lived project, an effective code review process is key to ensuring the long-term quality of the code base. In this work, we study code review practices of a large, open source project, and we investigate how the developers themselves perceive code review quality. We present a qualitative study that summarizes the results from a survey of 88 Mozilla core developers. The results provide developer insights into how they define review quality, what factors contribute to how they evaluate submitted code, and what challenges they face when performing review tasks. We found that the review quality is primarily associated with the thoroughness of the feedback, the reviewer's familiarity with the code, and the perceived quality of the code itself. Also, we found that while different factors are perceived to contribute to the review quality, reviewers often find it difficult to keep their technical skills up-to-date, manage personal priorities, and mitigate context switching.