# A Weighted PageRank-Based Bug Report Summarization Method Using Bug Report Relationships
## 1 Introduction  
Bug reports provide important information for developers to maintain a software system. Bug reports are used for developers to share and discuss information with others when fixing bugs, which account for approximately 40% of software maintenance tasks. Even after a bug is fixed, bug reports are used for various purposes, such as checking the history of past changes and referring to relevant bug fixes [1]. In general, bug reports are maintained in bug-tracking systems such as Bugzilla and Jira. Figure 1 shows an example of a bug report on the Bugzilla platform. As shown in Figure 1, each bug report contains a detailed description of the bug with a unique number and a title. Below the description of the bug, comments are listed that contain the developer's discussion on how to reproduce or fix the bug. Due to the characteristics of these bug reports, bug reports are generally considered as a document in the form of a sequential conversation. In addition, there are various metadata in bug reports, such as tags indicating the type or status of bugs and information about developers (e.g., bug manager and assignee), and links to the relevant bug reports. One example of when bug reports are utilized during software maintenance is a bug report duplicate detection task [2]. This task determines whether similar bug reports exist for the same bug and tag the bug reports with \"duplicates.\" To determine whether similar bug reports exist for the same bug, developers often perform keyword-based searches in bug-tracking systems. When bug reports are retrieved, a developer reads the bug reports one by one, which is very time consuming. Because a bug report is in the form of a conversation, the bug report is often long and verbose. Therefore, developers sometimes have difficulty finding the desired information in the bug report. To solve the problem, researchers have proposed using a summary of bug reports. As an alternative to this approach, a developer can write a summary of the bug when a bug is fixed. However, this requires additional work by the developer and, thus, may not be adopted in practice. As a result, researchers are working on automatic methods for summarizing bug reports. To propose a method for automatically generating a summary of bug reports, [PERSON] et al. [2] applied an existing supervised learning technique to bug reports and conducted experiments using the summary of bug reports so that actual developers can detect duplicate bug reports. The experiment showed that the time spent on the detection work was reduced by approximately 30% without affecting the quality of the output. In addition, when conducting a questionnaire survey on the developers who participated in the work, they found that developers responded that when they used the summary of bug reports, they could easily understand the bug reports. This showed the effectiveness of using the summary statement. Since then, various bug report summarization methods have been studied to improve the quality of bug report summaries. In most cases, however, researchers have focused on learning methods, such as adopting machine learning algorithms [3; 4; 5]. They have not focused on how to exploit specific domain knowledge, such as the characteristics of bug reports. [PERSON] et al. [6] used the  
Figure 1: An example of a bug report. characteristics of the bug report to improve the quality of bug report summaries. They considered that existing bug report summarization methods are used for detecting duplicate bugs and proposed a bug report summarization method using duplicate bug reports. [PERSON] et al. (2019) showed that using duplicates relationships among bug reports can improve the quality of bug report summaries. However, among various possible bug report relationships (Cf. Table 1), they used only duplicates relationships with the consequence that the effect of applying their method to bug reports is limited.