Section: New Results

Software Quality: History and Changes

Mining Architectural Violations from Version History. Software architecture conformance is a key software quality control activity that aims to reveal the progressive gap normally observed between concrete and planned software architectures. However, formally specifying an architecture can be difficult, as it must be done by an expert of the system having a high level understanding of it. We present a lightweighted approach for architecture conformance based on a combination of static and historical source code analysis. The proposed approach relies on four heuristics for detecting absences (something expected was not found) and divergences (something prohibited was found) in source code based architectures. We also present an architecture conformance process based on the proposed approach. We followed this process to evaluate the architecture of two industrial-strength information systems, achieving an overall precision of 62.7% and 53.8%. We also evaluated our approach in an open-source information retrieval library, achieving an overall precision of 59.2%. We envision that an heuristic-based approach for architecture conformance can be used to rapidly raise architectural warnings, without deeply involving experts in the process. [17]

Untangling Fine-Grained Code Changes. After working for some time, developers commit their code changes to a version control system. When doing so, they often bundle unrelated changes (e.g., bug fix and refactoring) in a single commit, thus creating a so-called tangled commit. Sharing tangled commits is problematic because it makes review, reversion, and integration of these commits harder and historical analyses of the project less reliable. Researchers have worked at untangling existing commits, i.e., finding which part of a commit relates to which task. We contribute to this line of work in two ways: (1) A publicly available dataset of untangled code changes, created with the help of two developers who accurately split their code changes into self contained tasks over a period of four months; (2) a novel approach, EpiceaUntangler, to help developers share untangled commits (aka. atomic commits) by using fine-grained code change information. EpiceaUntangler is based and tested on the publicly available dataset, and further evaluated by deploying it to 7 developers, who used it for 2 weeks. We recorded a median success rate of 91% and average one of 75%, in automatically creating clusters of untangled fine-grained code changes. [25]

Developers’ Perception of Co-Change Patterns: An Empirical Study. Co-change clusters are groups of classes that frequently change together. They are proposed as an alternative modular view, which can be used to assess the traditional decomposition of systems in packages. To investigate developer's perception of co-change clusters, we report a study with experts on six systems, implemented in two languages. We mine 102 co-change clusters from the version history of such systems, which are classified in three patterns regarding their projection to the package structure: Encapsulated, Crosscutting, and Octopus. We then collect the perception of expert developers on such clusters, aiming to ask two central questions: (a) what concerns and changes are captured by the extracted clusters? (b) do the extracted clusters reveal design anomalies? We conclude that Encapsulated Clusters are often viewed as healthy designs and that Crosscutting Clusters tend to be associated to design anomalies. Octopus Clusters are normally associated to expected class distributions, which are not easy to implement in an encapsulated way, according to the interviewed developers. [40]