The role of organizational culture in software development practices: A cross-case analysis of four software companies

Culture can be seen as the normative glue that holds an organization together. It is related to the institutionalized way of thinking and acting of people. Our aim is to study and characterize belief systems in software organizations. Our work highlights organizational culture influence by applying the Theory of Reasoned Action (TRA) to software project teams in terms of origins, sources and impacts of beliefs on software development practices. By applying TRA to guide two case studies, we were able to provide rich narrative accounts of software project teams, involving the influence factors associated to team belief systems and attitudes toward practice. Our research has gone through two cycles, comprising 2.5 years of study in Brazilian software companies. A particular moment of the research, the synthesis of the two case studies results is being explored in this paper. A set of interviews and observations was performed with professionals from different project teams and companies. A conceptual framework was built based on the TRA model to guide a cross-case analysis of the results. The synthesis of the analysis highlights the strong influence of past experiences and organizational contexts on software development practices

Beliefs underlying teams intention and practice: An application of the theory of planned behavior

Many theories aim to understand the beliefs underlying an intention or behavior. These theories are currently used to seek answers about how people progress from intention to practice in business environments. The Theory of Planned Behavior (TPB) is today one of the most popular sociopsychological models for the prediction of behavior. It is believed that people consider the implications of their actions and act based on a reasonable assessment of those implications. In this context, belief can be defined as the psychological state in which an individual holds a proposition or premise to be true. So, behavior is driven by what is believed, by what is culturally assumed to be true about the world. Our work aims to study and characterize a belief system applying TPB in project teams in terms of organizational and team levels factors associated to beliefs about the software development practices. A set of interviews on origins, sources and impacts of beliefs on software pr actices was conducted with professionals from different project teams and companies. The results point out to a strong influence of past experiences and show that it is possible to characterize belief systems in software project contexts within a behavioral perspective

Endless Bad Projects or Evidence-Based Practice? An agenda for action

This short position paper promotes the need for more evidence based practice to underpin the successful execution of information systems (IS) projects. This research responds to the high numbers of IS projects that are seen to have failed in terms of either one or many success criteria such as: not meeting original objectives, running over budget, negatively impacting on people, processes or organizations, to name but a few. We advocate the need for the development of a more rigorous evidence base for IS research similar to those used in medicine or more recently in social studies and software engineering. For example, Systematic Literature Reviews (SLRs) and also Meta-Analysis of empirical research studies could be used more extensively within IS to compile more coherent, consistent and referable bodies of evidence and knowledge. We conclude with a 7 point action plan and suggestions for further research

DConfusion: A technique to allow cross study performance evaluation of fault prediction studies.

There are many hundreds of fault prediction models published in the literature. The predictive performance of these models is often reported using a variety of different measures. Most performance measures are not directly comparable. This lack of comparability means that it is often difficult to evaluate the performance of one model against another. Our aim is to present an approach that allows other researchers and practitioners to transform many performance measures back into a confusion matrix. Once performance is expressed in a confusion matrix alternative preferred performance measures can then be derived. Our approach has enabled us to compare the performance of 600 models published in 42 studies. We demonstrate the application of our approach on 8 case studies, and discuss the advantages and implications of doing this.Peer reviewe