Collaborative Software Development in Agile Methodologies - Perspectives from Small Group Research

Collaborative software development is a hallmark of agile methodologies such as Extreme Programming (XP). These methodologies have practices like pair programming, where two programmers collaboratively work on all aspects of software development. There is however a dearth of empirical research in this area. Studies with sound theoretical underpinnings and strong empirical rigor are called for to inform the software practice of the effectiveness of this important practice. While such collaborative working is relatively new to software community, small group research has grappled with it over the years looking for the task and other contingencies impacting the effectiveness of collaborative working versus individual working. In this paper, we provide a brief overview of some research streams in small group research and social psychology that could potentially inform IS research on collaborative software development. These small group research topics include group task typologies, individual versus group performance, social facilitation, social loafing, and group motivational gains. We then discuss implications for research on collaborative programming and provide some illustrative research questions

Efficacy of MobileNet Models in Detecting Breast Cancer in Patient Histopathology Images – An Empirical Examination

Breast cancer, the most common of all the cancers, is treatable when detected early. Histopathology (HP) biopsy images generated from breast tissue samples are commonly used as early screening tools for detecting malignancy. This study has developed and compared the efficacy of two convolutional neural network (CNN) models that are based on MobileNet architecture for automatic detection of Invasive Ductal Carcinoma (IDC), the most common form of breast cancer, in histopathology (HP) images of breast tissues. The best of the two models has shown encouraging classification performance in terms of accuracy, precision and recall. The results attest to the viability of using lighter CNN models such as MobileNet for decision support when screening for breast cancer

Understanding the Structure of Agile Software Development Using Text Analytics: A Preliminary Analysis

The tenets of agile software development (ASD) were formulated over fifteen years ago. Since then, a number of methods and best practices have emerged, which, in turn, have spawned many research ideas. This study attempts to chronicle the evolution of thought in agile software development by using text analytics, an approach that is becoming invaluable in our efforts to understand unstructured text. Specifically, we use text analytics to unravel latent semantic relationships within the agile domain in order to get a sense of where we started, where we are today, and what to anticipate in the future

Exploring the Structure of Software Development Research: A Preliminary Text Analysis

Software development projects are critical to organizations when seeking operational efficiencies, competitive advantage, or both. In this research we use text analytics and bibliometrics to identify the key topics of software development that were studied in IS research published in four top IS journals. We also discuss the distribution of various topics across years and the underlying cluster groupings

Assessing Personality Profiles of Software Developers in Agile Development Teams

Agile methodologies are changing the way we develop software. Their emphasis on team-oriented development, joint code ownership, and reliance on people rather than predefined processes to guide activities, is transforming software development into a socio-technical process. As methodologies become increasingly more people and team-oriented, there is an urgent need to investigate the personality profiles of software developers and their likely impact on the productivity of the development team. A review of the IS research literature on personality studies found Jungian typology operationalized as Myers-Briggs Type Indicator (MBTI) to be the most popular approach for assessing personality profiles. We compared the Five Factor Model (FFM) of personality, which is currently gaining popularity among personality psychologists, with MBTI. Our analysis, based on extant research literature in personality psychology and group behavior, suggests that FFM not only provides better measures for all factors that are measured by MBTI, but it also allows us to assess Neuroticism, an important personality trait that is of interest to researchers studying work groups, such as the agile development team. Our finding has important implications for researchers studying the agile development process. It is also highly relevant to studies investigating the personality profiles of IS professionals. Thus, our study attempts to bring in fresh insights from Personality Psychology, our reference discipline, to enrich IS research

Are We Wielding this Hammer Correctly? A Reflective Review of the Application of Cluster Analysis in Information Systems Research

Cluster analysis is a powerful statistical procedure for extricating natural configurations among the data and the populations. Cluster analysis, with its seemingly limitless power to produce groupings in any dataset, has all the trappings of a super-technique. However, the method produces clusters even in the absence of any natural structure in the data, and has no statistical basis to reject the null hypothesis that there are no natural groupings in the data. Application of cluster analysis, therefore, presupposes sound researcher judgment and responsible analysis and reporting. This paper summarizes the results of a reflective review of the application of cluster analysis in Information Systems (IS) research published in major IS outlets. Based on the analysis of 55 IS applications of cluster analysis, various deficiencies noticed in its use are discussed along with suggestions for future practice. By analyzing the results over two time periods, longitudinal trends in the application of this technique are highlighted

Learning Effectiveness and Student Satisfication in Mobile Classrooms

As a rapidly growing social-networking generation enters colleges and global workforces, college instructors and IT managers worldwide inevitably face a critical issue of how to better educate this emerging population who could be rarely separated, even in classroom settings, from wireless networks and mobile technology. Drawing from the notion of tasktechnology fit and various e-learning literatures, we thus develop a research model that seeks to shed light on how mobile technology might shape this social-networking generation’s learning experiences. We propose that courses designed with mobile technology embedded contribute to greater learning effectiveness and satisfaction for students compared to course designs where mobile technology is not embedded. We also posit that these positive outcomes may be moderated by the nature of course with higher learning effectiveness and satisfaction in non-technical courses than in technical courses. Proposed research design, measurement issues, and potential contributions are discussed