Open source code contributions contain a large amount of technical skill information about developers, which can help to identify suitable candidates for a particular development job and therefore impact the success of a development team. We develop CVExplorer as a tool to extract, visualize, and explore relevant technical skills data from GitHub, such as languages and libraries used. It allows non-technical users to filter and identify developers according to technical skills demonstrated across all of their open source contributions, in order to support more accurate candidate identification. We demonstrate the usefulness of CVExplorer by using it to recommend candidates for open positions in two companies.

Software engineering meta-data (SE data), such as revision control data, Github project data or test reports, is typically semi-structured, it comprises a mixture of formatted and free-text fields and is often self-describing. Semi-structured SE data cannot be queried in a SQL-like manner because of its lack of structure. Consequently, there are a variety of customized tools built to analyze specific datasets but these do not generalize. We propose to develop a generic framework for exploration and querying of semi-structured SE data. Our approach investigates the use of a formal concept lattice as a universal data structure and a tag cloud as an intuitive interface to support data exploration.

Version control repositories contain a wealth of implicit information that can be used to answer many questions about a project's development process. However, this information is not directly accessible in the version control archives and must be extracted and visualized. This paper describes ConceptCloud, a flexible, interactive browser for SVN and Git repositories. The main novelty of our approach is the combination of an intuitive tag cloud visualization with an underlying concept lattice that provides a formal structure for navigation. ConceptCloud supports concurrent navigation in multiple linked but individually customizable tag clouds, which allows for multi-faceted repository browsing and for the construction of unique visualizations. We describe the mathematical foundations and implementation of our approach, and use ConceptCloud to quickly gain insight into the team structure and development process of two projects.

ConceptCloud is an interactive browser for SVN and Git repositories. Its main novelty is the combination of an intuitive tag cloud interface with an underlying concept lattice that provides a formal structure for navigation. This combination allows users to explore repositories serendipitously, without predefined search goals and along different navigation paths. ConceptCloud can derive different lattice types for a repository and supports concurrent navigation in multiple linked tag clouds that can each be individually customized, which allows multi-faceted repository explorations.