Visual querying and analysis of large software repositories

We present a software framework for mining software repositories. Our extensible framework enables the integration of data extraction from repositories with data analysis and interactive visualization. We demonstrate the applicability of the framework by presenting several case studies performed on industry-size software repositories. In each study we use the framework to give answers to one or several software engineering questions addressing a specific project. Next, we validate the answers by comparing them with existing project documentation, by interviewing domain experts and by detailed analyses of the source code. The results show that our framework can be used both for supporting case studies on mining software repository techniques and for building end-user tools for software maintenanc

How do coupled file changes influence how developers seek help during maintenance tasks?

Software repositories contain a lot of information that can be transformed into suggestions other files they need to modify during maintenance tasks (so-called “coupled changes”). Existing studies however ignore developer feedback and their influence on the developer strategy for getting help during maintenance tasks. We used the Grounded Theory approach to investigate screen capture videos from an experiment to find which information sources developers use to find help and what is their relevance. We compared the frequency as well as the sequence patterns of used information sources both for the developers using coupled change suggestions and those not using them. We found a set of information sources where the developers seek for help and identified two categories of relevance. Also, we discovered that for the tasks using coupled change suggestions, the developers used mostly the internal IDE elements as an information source whereby the developers not using coupled change suggestions often used external sources like the documentation or the web. Coupled change suggestions influence the strategy how the developers seek for help by reducing the search for information on external locations which makes the process of solving maintenance tasks more compact

Identification and analysis of chunks in software projects

Most software systems undergo continuous change in different phases of their lifecycle such as development or maintenance. Ideally, such changes should correspond to a system\u27s modular design. However, some changes span across more than one component thereby resulting in discrepancies between design and implementation. In such cases, making a change to one component requires changes to other components leading to an increase in time and effort to make changes to a software system as it evolves. This thesis investigates: 1) an approach to observe how components change together by identifying tightly coupled changes known as chunks, 2) whether there are any trends in how chunks evolve over time, and 3) whether chunks can help identify design issues in a software system. In this work, a family of algorithms is proposed to identify independently changing chunks from change data obtained from mining version history repositories of three large software systems - Moodle, Eclipse, and Company-X. A comprehensive analysis of certain characteristics of the resulting chunks is conducted. In addition, evolution of chunks with respect to size in terms of number of files within a chunk, and percentage of changes crossing a chunk are studied. Lastly, a pragmatic interpretation of the results to identify necessary code refactoring or system redesign is presented. The findings of this work show that the percentage correlation of a chunk decreases with an increase in the number of inter-component or subsystem couplings. We also observed that there is no association between chunk size and percentage correlation. Identifying chunks that merge helps in a better understanding of the inconsistencies between how a system is designed for change and how it is actually changed, and to identify areas of a system that require refactoring or redesign. Additionally, identifying stable chunks can provide insights into how size and percentage correlation of the corresponding empirical components change over time

Mining software repositories to support software evolution

Software evolution represents a major phase in the development life cycle of software systems. In recent years, software evolution has been recognized as one of the most important and challenging areas in the field of software engineering. Studies even show that 65-80% of the system lifetime will be spent on maintenance and evolution activities. Software repositories, such as versioning and bug tracking systems are essential parts of various software maintenance activities. Given the often large amounts of information stored in these repositories, researchers have proposed to mine and analyze these large knowledge bases in order to study and support various aspects of the evolution of a software system. In this thesis, we introduce a common ontological representation to support the mining and analysis of software repositories. In addition to this common representation, we introduce the SVN-Ontologizer and Bugzilla-Ontologizer tools that provide automation for both data extraction from remote repositories and ontology populations. A case study is presented to illustrate the applicability of the present approach in supporting software maintainers during the analysis and mining of these software repositorie