# Graph-Driven Exploration of Issue Handling Schemes in Software Projects
## 1 Introduction  
Software development and maintenance processes are documented in project repositories. The most interesting repositories are provided by the Issue Tracking (ITS) and Version Control (VCS) Systems, which are used by project stakeholders to manage their activities. The importance and practical usefulness of the ITS and VCS is underlined in [1; 2; 3]. Data collected in software repositories are the basis for diverse practical and research studies in the software engineering domain. Here, we can distinguish the following aspects considered in the literature on software repositories: the detection of duplicate issues [4; 5], bug prediction and issue classification [6; 7], bug triaging [8], and issue report textual analysis [9; 10]. Most papers related to software bugs focus on a single selected problem considering coarse-grained data from repositories. Other types of issues also have a high impact on development processes and are underestimated. The issue handling schemes have a significant impact on software reliability. 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. The multitude and diversity of data in the ITS and VCS are challenges in data exploration targeting specific investigation problems. Issue management consists of identifying project requirements, planning development tasks, handling, and explaining appearing problems. All of these activities are documented in ITS repositories that describe diverseissue features (attributes), processing progress, project actor activities, etc. 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? The main contributions of our study are as follows:  
* Introducing an original issue handling model: a processing activity graph targeted at diverse observation perspectives and linked with issue repository databases. * Developing analysis schemes supported by original metrics and algorithms. * Verifying the efficiency and usefulness of the proposed approach in experiments with real project repositories. The issue handling model (IHM) with conceptualization entities and derived property profiles (fine-grained and aggregated) constitutes a body of represented knowledge on project development/maintenance processes. The IHM considers various issue attributes neglected in other approaches which impact the accuracy of the analysis. It enables the tracing of issue handling paths and defining quality analysis criteria related to issue processing phases or scenarios, handling times, and resolution coverage. The presented methodology and algorithms allow us to accumulate experience and facts in the knowledge database on software projects. Discussing the analysis results with project stakeholders facilitates making decisions on improving developed projects, avoiding bad practices, or transferring the identified good practices to new projects. The organization of the remainder of this paper is as follows. Section 2 outlines the related work and addresses our research scope. Section 3 presents general features of issue tracking repositories and formulates challenges in their analysis. Section 4 introduces a generalized graphical model (IHM) of issue handling processes and issue flow metrics.