Published in Seoul, Republic of Korea, 2020
The fork-based development mechanism provides the flexibility and the unified processes for software teams to collaborate easily in a distributed setting without too much coordination overhead. Currently, multiple social coding platforms support fork-based de- velopment, such as GitHub, GitLab, and Bitbucket. Although these different platforms virtually share the same features, they have different emphasis. As GitHub is the most popular platform and the corresponding data is publicly available, most of the current stud- ies are focusing on GitHub hosted projects. However, we observed anecdote evidences that people are confused about choosing among these platforms, and some projects are migrating from one platform to another, and the reasons behind these activities remain unknown. With the advances of Software Heritage Graph Dataset (SWHGD), we have the opportunity to investigate the forking activities across platforms. In this paper, we conduct an exploratory study on 10 popular open-source projects to identify cross-platform forks and investigate the motivation behind. Preliminary result shows that cross-platform forks do exist. For the 10 subject systems in this study, we found 81,357 forks in total among which 179 forks are on GitLab. Based on our qualitative analysis, we found that most of the cross-platform forks that we identified are mirrors of the repos- itories on another platform, but we still find cases that were created due to preference of using certain functionalities (e.g. Continuous Integration (CI)) supported by different platforms. This study lays the foundation of future research directions, such as understanding the differences between platforms and supporting cross-platform collaboration. [pdf]
Recommended citation: Avijit Bhattacharjee, Sristy Sumana Nath, Shurui Zhou, Debasish Chakroborti, Banani Roy, Chanchal K. Roy, and Kevin Schneider. 2020. An Exploratory Study to Find Motives Behind Cross-platform Forks from Software Heritage Dataset . In 17th International Conference on Mining Software Repositories. https://arxiv.org/pdf/2003.07970
Published in International Conference on Intelligent Systems Design and Applications, 2018
Phylogenetic tree construction (PT) problem is a well-known NP-hard optimization problem that finds most accurate tree representing evolutionary relationships among species. Different criteria are used to measure the quality of a phylogeny tree by analyzing their relationships and nucleotide sequences. With increasing number of species, solution space of phylogenetic tree construction problem grows exponentially. In this paper, we have implemented Chemical Reaction Optimization algo- rithm to solve phylogeny construction problem for multiple datasets. For exploring both local and global search space, we have redesigned four elementary operators of CRO to solve phylogeny construction problem. One correction method has been designed for finding good combination of species according to maximum parsimony criterion. The experimen- tal results show that for maximum parsimony criterion our implemented algorithm gives better results for three real datasets and same for one dataset.
Recommended citation: Bhattacharjee, Avijit, SK Rahad Mannan, and Md Rafiqul Islam. "Phylogenetic Tree Construction Using Chemical Reaction Optimization." International Conference on Intelligent Systems Design and Applications. Springer, Cham, 2018. https://link.springer.com/chapter/10.1007/978-3-030-16660-1_89