Biblio

Transparent environments and social-coding platforms as GitHub help developers to stay abreast of changes during the development and maintenance phase of a project. Especially, notification feeds can help developers to learn about relevant changes in other projects. Unfortunately, transparent environments can quickly overwhelm developers with too many notifications, such that they loose the important ones in a sea of noise. Complementing existing prioritization and filtering strategies based on binary compatibility and code ownership, we develop an anomaly-detection mechanism to identify unusual commits in a repository, that stand out with respect to other changes in the same repository or by the same developer. Among others, we detect exceptionally large commits, commits at unusual times, and commits touching rarely changed file types given the characteristics of a particular repository or developer. We automatically flag unusual commits on GitHub through a browser plugin. In an interactive survey with 173 active GitHub users, rating commits in a project of their interest, we found that, though our unusual score is only a weak predictor of whether developers want to be notified about a commit, information about unusual characteristics of a commit change how developers regard commits. Our anomaly-detection mechanism is a building block for scaling transparent environments.

Certification schemes exist to regulate software systems and prevent them from being deployed before they are judged fit to use. However, practitioners are often unsatisfied with the efficiency of certification standards and processes. In this study, we analyzed two certification standards, Common Criteria and DO-178C, and collected insights from literature and from interviews with subject-matter experts to identify concepts affecting the efficiency of certification processes. Our results show that evaluation time, reusability of evaluation artifacts, and composition of systems and certified artifacts are barriers to achieve efficient certification.

Preprocessors support the diversification of software products with #ifdefs, but also require additional effort from developers to maintain and understand variable code. We conjecture that #ifdefs cause developers to produce more vulnerable code because they are required to reason about multiple features simultaneously and maintain complex mental models of dependencies of configurable code.

We extracted a variational call graph across all configurations of the Linux kernel, and used configuration complexity metrics to compare vulnerable and non-vulnerable functions considering their vulnerability history. Our goal was to learn about whether we can observe a measurable influence of configuration complexity on the occurrence of vulnerabilities.

Our results suggest, among others, that vulnerable functions have higher variability than non-vulnerable ones and are also constrained by fewer configuration options. This suggests that developers are inclined to notice functions appear in frequently-compiled product variants. We aim to raise developers' awareness to address variability more systematically, since configuration complexity is an important, but often ignored aspect of software product lines.

Software developers use #ifdef statements to support code configurability, allowing software product diversification. But because functions can be in many executions paths that depend on complex combinations of configuration options, the introduction of an #ifdef for a given purpose (such as adding a new feature to a program) can enable unintended function calls, which can be a source of vulnerabilities. Part of the difficulty lies in maintaining mental models of all dependencies. We propose analytic visualizations of thevariational callgraph to capture dependencies across configurations and create visualizations to demonstrate how it would help developers visually reason through the implications of diversification, for example through visually doing change impact analysis.

Security has consistently been the focus of attention in many highly-configurable software systems. Several vulnerabilities on widely-used systems, such as the Linux kernel and OpenSSL, are reported every day in the National Vulnerability Database (NVD). The configurability of these systems enables the rapid generation of customized products, but also creates security challenges in the development and maintenance processes. For instance, interactions caused by configurations may create serious security threats and make generated products more susceptible to attacks [6], but the causes of these problems may be harder to detect because they occur only in specific configurations.