It has been suggested that the data from bug repositories is not always in sync or complete compared to the logs detailing the actions of developers on source code.In this paper, we trace two sources of information relative to software bugs: the change logs of the actions of developers and the issues reported as bugs. The aim is to identify and quantify the discrepancies between the two sources in recording and storing the developer logs relative to bugs.Focussing on the databases produced by two mining software repository tools, CVSAnalY and Bicho, we use part of the SZZ algorithm to identify bugs and to compare how the "defects-fixing changes" are recorded in the two databases. We use a working example to show how to do so.The results indicate that there is a significant amount of information, not in sync when tracing bugs in the two databases. We, therefore, propose an automatic approach to re-align the two databases, so that the collected information is mirrored and in sync.

Context: Information and tracking of defects can be severely incomplete in almost every Open Source project, resulting in a reduced traceability of defects into the development logs (i.e., version control commit logs). In particular, defect data often appears not in sync when considering what developers logged as their actions. Synchronizing or completing the missing data of the bug repositories, with the logs detailing the actions of developers, would benefit various branches of empirical software engineering research: prediction of software faults, software reliability, traceability, software quality, effort and cost estimation, bug prediction and bug fixing.Objective: To design a framework that automates the process of synchronizing and filling the gaps of the development logs and bug issue data for open source software projects.Method: We instantiate the framework with a sample of OSS projects from GitHub, and by parsing, linking and filling the gaps found in their bug issue data, and development logs. UML diagrams show the relevant modules that will be used to merge, link and connect the bug issue data with the development data.Results: Analysing a sample of over 300 OSS projects we observed that around 1/2 of bug-related data is present in either development logs or issue tracker logs: the rest of the data is missing from one or the other source. We designed an automated approach that fills the gaps of either source by making use of the available data, and we successfully mapped all the missing data of the analysed projects, when using one heuristics of annotating bugs. Other heuristics need to be investigated and implemented.

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The development logs of software projects, contained in Version Control (VC) systems can be severely incomplete when tracking bugs, especially in open source projects, resulting in a reduced traceability of defects. Other times, such logs can contain bug information that is not available in bug tracking system (BT system) repositories, and vice-versa: if development logs and BT system data were used together, researchers and practitioners often would have a larger set of bug IDs for a software project, and a better picture of a bug life cycle, its evolution and maintenance. Considering a sample of 10 OSS projects and their development logs and BT systems data, the two objectives of this paper are (i) to determine which of the keywords 'Fix', 'Bug' or the '#' identifier provide the better precision; and (ii) to analyse their respective precision and recall at locating the larger amount possible of bug IDs manually. Overall, our results suggest that the use of the '#' identifier in conjunction with the bug ID digits (e.g., #1234) is more precise for locating bugs in development logs, than the use of the 'Bug' and 'Fix' keywords. Such keywords are indeed present in the development logs, but they are less useful when trying to connect the development actions with the bug traces in software project.

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