A library migration recommendation tool based on large-scale historical migration data mining.
Relevant library migration papers and corresponding repositories are available as follows:
- Haiqiao Gu, Hao He, and Minghui Zhou. 2023. Self-Admitted Library Migrations in Java, JavaScript, and Python Packaging Ecosystems: A Comparative Study. In IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2023, Taipa, Macao, March 21-24, 2023, IEEE. https://github.com/guhaiqiao/SALMC
- Hao He, Runzhi He, Haiqiao Gu, and Minghui Zhou. 2021. A large-scale empirical study on Java library migrations: prevalence, trends, and rationales. In ESEC/FSE ’21: 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Athens, Greece, August 23-28, 2021, ACM. https://github.com/hehao98/LibraryMigration
- Hao He, Yulin Xu, Xiao Cheng, Guangtai Liang, and Minghui Zhou. 2021. MigrationAdvisor: Recommending Library Migrations from Large-Scale Open-Source Data. In 43rd IEEE/ACM International Conference on Software Engineering: Companion Proceedings, ICSE Companion 2021, Madrid, Spain, May 25-28, 2021, IEEE. https://github.com/hehao98/MigrationHelper
Reusing open-source software libraries has become the norm in modern software development, but libraries can fail due to various reasons, e.g., security vulnerabilities, lacking features, and end of maintenance. In some cases, developers need to replace a library with another competent library with similar functionalities, i.e., library migration. However, it is difficult to make the optimal migration decision with limited information, knowledge, or expertise. Therefore, we conducted large-scale library migration data mining and proposed an evidence-based tool to recommend library migration targets through intelligent analysis upon a large number of GitHub repositories and libraries (Java, JavaScript, and Python).
https://osslab-pku.org/project/2022-08-08-Library-migration-helper/