Previous taxonomies of software change have focused on the purpose of the change (i.e., the why) rather than the underlying mechanisms. This paper proposes a taxonomy of software change based on characterizing the mechanisms of change and the factors that influence these mechanisms. The ultimate goal of this taxonomy is to provide a framework that positions concrete tools, formalisms and methods within the domain of software evolution. Such a framework would considerably ease comparison between the various mechanisms of change. It would also allow practitioners to identify and evaluate the relevant tools, methods and formalisms for a particular change scenario. As an initial step towards this taxonomy, the paper presents a framework that can be used to characterize software change support tools and to identify the factors that impact on the use of these tools. The framework is evaluated by applying it to three different change support tools and by comparing these tools based on this analysis.

Background Contact tracing remains a critical part of controlling COVID-19 spread. Many countries have developed novel software applications (Apps) in an effort to augment traditional contact tracing methods. Aim Conduct a national survey of the Irish population to examine barriers and levers to the use of a contact tracing App. Methods Adult participants were invited to respond via an online survey weblink sent via e-mail and messaging Apps and posted on our university website and on popular social media platforms, prior to launch of the national App solution. Results A total of 8088 responses were received, with all 26 counties of the Republic of Ireland represented. Fifty-four percent of respondents said they would definitely download a contact-tracing App, while 30% said they would probably download a contact tracing App. Ninety-five percent of respondents identified at least one reason for them to download such an App, with the most common reasons being the potential for the App to help family members and friends and a sense of responsibility to the wider community. Fifty-nine percent identified at least one reason not to download the App, with the most common reasons being fear that technology companies or the government might use the App technology for greater surveillance after the pandemic. Conclusion The Irish citizens surveyed expressed high levels of willingness to download a public health-backed App to augment contact tracing. Concerns raised regarding privacy and data security will be critical if the App is to achieve the large-scale adoption and ongoing use required for its effective operation.

Concept location, the problem of associating human oriented concepts with their counterpart solution domain concepts, is a fundamental problem that lies at the heart of software comprehension. Recent research has attempted to alleviate the impact of the concept location problem through the application of methods drawn from the information retrieval (IR) community. Here we present a new approach based on a complimentary IR method which also has a sound basis in cognitive theory. We compare our approach to related work through an experiment and present our conclusions. This research adapts and expands upon existing language modelling frameworks in IR for use in concept location, in software systems. In doing so it is novel in that it leverages implicit information available in system documentation. Surprisingly, empirical evaluation of this approach showed little performance benefit overall and several possible explanations are forwarded for this finding.

Objectives: Software architecture is perceived as one of the most important artefacts created during a system's design. However, implementations often diverge from their intended architectures: a phenomenon called architectural drift. The objective of this research is to assess the occurrence of architectural drift in the context of de novo software development, to characterize it, and to evaluate whether its detection leads to inconsistency removal. Method: An in vivo, longitudinal case study was performed during the development of a commercial software system, where an approach based on Reflexion Modelling was employed to detect architectural drift. Observation and think‐aloud data, captured during the system's development, were assessed for the presence and types of architectural drift. When divergences were identified, the data were further analysed to see if identification led to the removal of these divergences. Results: The analysed system diverged from the intended architecture, during the initial implementation of the system. Surprisingly however, this work showed that Reflexion Modelling served to conceal some of the inconsistencies, a finding that directly contradicts the high regard that this technique enjoys as an architectural evaluation tool. Finally, the analysis illustrated that detection of inconsistencies was insufficient to prompt their removal, in the small, informal team context studied. Conclusions: Although the utility of the approach for detecting inconsistencies was demonstrated in most cases, it also served to hide several inconsistencies and did not act as a trigger for their removal. Hence additional efforts must be taken to lessen architectural drift and several improvements in this regard are suggested. Copyright © 2010 John Wiley & Sons, Ltd.