Context: Researchers have increasingly recognised the benefit of mining software repositories to extract information. Although, the development logs of software projects, contained in Version Control (VC) systems can be severely incomplete when tracking bugs, especially in open-source software projects, resulting in reduced traceability of defects. Other times, such logs can contain bug information that is not available in the bug tracking system (BT system) repositories, and vice-versa. If the development logs and bug related-data (i.e., BT system data) were applied 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. Method The research aims to design and implement a toolchain to support the integration of a VC and BT toolset as well to synchronise the missing development logs and Bug data of open-source software projects automatically. Considering a random sample of 344 Open Source Software (OSS) projects development logs (55,689) and Bugs data (167,800), the two objectives of this paper are (i) to determine which of the keywords 'Fix', 'Bug' or the '#' identifier provide better precision; and (ii) to analyse their respective precision and recall at locating significant amount possible of bug IDs semi-automatically. In its formulation, the SZZ algorithm looks for the terms ``Bugs'' or ``Fixed'' (case-insensitive) along with the '#' sign, that shows the ID of a bug in the development logs and Bug data respectively. Results: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 the 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 open source software project. The results indicate that the development log and Bug related data can be track and recovered with better accuracy using only a part of the SZZ algorithm. Thus 80-95\% of all The missing bug data and development logs of 344 OSS projects have been synchronised using the proposed tool-chain into Bicho and CVSAnalY database respectively. Conclusion: The presented toolchain eliminate and avoid repetitive activities in traceability tasks, software maintenance and evolution. The fact that in the past researchers have proven linking and synchronising development logs and bug data is complicated. Thus Bicho and CVSAnalY tools were developed to mine and store development logs and bug data independently. This research provides a solution towards the automation and traceability of bug data of software projects (in particular, OSS projects) using development logs to complement and track the missing bug data. The Synchronisation involves completing the missing bug data in software repositories with the development logs which details the actions of developers.