Enhancing Software Project Monitoring with Multidimensional Data Repository Mining

Abstract

Software project development and maintenance activities have been reported in various repositories. The data contained in these repositories have been widely used in various studies on specific problems, e.g., predicting bug appearance, allocating issues to developers, and identifying duplicated issues. Developed analysis schemes are usually based on simplified data models while issue report details are neglected. Confronting this problem requires a deep and wide-ranging exploration of software repository contents adapted to their specificities, which differs significantly from classical data mining. This paper is targeted at three aspects: the structural and semantic exploration of repositories, deriving characteristic features in value and time perspectives, and defining the space of project monitoring goals. The considerations presented demonstrate a holistic image of the project development process, which is useful in the assessment of its efficiency and identification of imperfections. The original analysis introduced in this work was verified using open source and some commercial software project repositories.

Graph-Driven Exploration of Issue Handling Schemes in Software Projects

“…Both lists can be combined in one history list. Having analyzed a wide scope of ITS repositories [12], we found that depending upon the project, issue attributes and their values may differ partially or significantly. Usually, within the same project, they are stable; however, some fluctuation may appear in time, e.g., due to ITS system upgrades, project organization and development improvements, project actors' fluctuations, etc.…”

“…Depending upon the project, the number of issue attributes is in the range of a few dozen to more than 100. However, only some of them can be useful in the analysis [12]. The ITS records individual issue features to provide project actors with information on their processing.…”

“…In the P1 project, we achieved a reduction in the number of code change operations (and modified files) by 30% within 3 years, which resulted in lowering the workload of programmers. We have also introduced some metrics of project actors' activities [12]. The presented coarse-grained project development features provide a general overview.…”

“…Numerous models have been proposed to address this problem, such as [11]. In [12], we showed the need to investigate fine-grained data in issue reports to obtain a deeper view regarding issue handling processes. Developing a holistic methodology of assessing the effectiveness of issue handling processes enriched with anomaly detection capabilities is a consequence of these studies.…”

“…Having examined many ITS repositories, we observed an abundance of diverse data relevant to project development and maintenance, which are not adequately exploited by project stakeholders. Moreover, our experience with developing and analyzing software projects [12][13][14] motivated us to formulate two research questions: Q1-What is the scope of issue specification, information accuracy, statistical properties (static and dynamic), and their impact on handling processes? Q2-How should we evaluate and improve issue handling processes on the basis of ITS reports?…”