The interlinking of commit and issue data has become a de-facto standard in software development. Modern issue tracking systems, such as JIRA, automatically interlink commits and issues by the extraction of identifiers (e.g., Issue key) from commit messages. However, the conventions for the use of interlinking methodologies vary between software projects. For example, some projects enforce the use of identifiers for every commit while others have less restrictive conventions. In this work, we introduce a model called PaLiMod to enable the analysis of interlinking characteristics in commit and issue data. We surveyed 15 Apache projects to investigate differences and commonalities between linked and non-linked commits and issues. Based on the gathered information, we created a set of heuristics to interlink the residual of non-linked commits and issues. We present the characteristics of Loners and Phantoms in commit and issue data. The results of our evaluation indicate that the proposed PaLiMod model and heuristics enable an automatic interlinking and can indeed reduce the residual of non-linked commits and issues in software projects.

Continuous integration of source code changes, for example, via pull-request driven contribution channels, has become standard in many software projects. However, the decision to integrate source code changes into a release is complex and has to be taken by a software manager. In this work, we identify a set of three pragmatic recipes plus variations to support the decision making of integrating code contributions into a release. These recipes cover the isolation of source code changes, contribution of test code, and the linking of commits to issues. We analyze the development history of 21 open-source software projects, to evaluate whether, and to what extent, those recipes are followed in open-source projects. The results of our analysis showed that open-source projects largely follow recipes on a compliance level of > 75%. Hence, we conclude that the identified recipes plus variations can be seen as wide-spread relevant best-practices for source code integration.

Continuous Integration (CI) environments cope with the repeated integration of source code changes and provide rapid feedback about the status of a software project. However, as the integration cycles become shorter, the amount of data increases, and the effort to find information in CI environments becomes substantial. In modern CI environments, the selection of measurements (e.g., build status, quality metrics) listed in a dashboard does only change with the intervention of a stakeholder (e.g., a project manager). In this paper, we want to address the shortcoming of static views with so-called Software Quality Assessment (SQA) profiles. SQA-Profiles are defined as rule-sets and enable a dynamic composition of CI dashboards based on stakeholder activities in tools of a CI environment (e.g., version control system). We present a set of SQA-Profiles for project management committee (PMC) members: Bandleader, Integrator, Gatekeeper, and Onlooker. For this, we mined the commit and issue management activities of PMC members from 20 Apache projects. We implemented a framework to evaluate the performance of our rule-based SQA-Profiles in comparison to a machine learning approach. The results showed that project-independent SQA-Profiles can be used to automatically extract the profiles of PMC members with a precision of 0.92 and a recall of 0.78.

Software quality assessment shall monitor and guide the evolution of a system based on quality measurements. This continuous process should ideally involve multiple stakeholders and provide adequate information for each of them to use. We want to support an effective selection of quality measurements based on the type of software and individual information needs of the involved stakeholders. We propose an approach that brings together quality measurements and individual information needs for a context-sensitive tailoring of information related to a software quality assessment. We address the following research question: How can we better support different stakeholders in the quality assessment of a software system? For that we will devise theories, models, and prototypes to capture their individual information needs, tailor information from software repositories to these needs, and enable a contextual analysis of the quality aspects. Such a context-sensitive tailoring will provide a effective and individual view on the latest development trends in a project. We outline the milestones as well as evaluation approaches in this paper.