EvoMe: A Software Evolution Management Engine Based on Differential Factbase

Xiuheng Wu, Mengyang Li, and Yi Li

In Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering (ASE), 2021

Abstract: Managing large and fast-evolving software systems can be a challenging task. Numerous solutions have been developed to assist in this process, enhancing software quality and reducing development costs. These techniques—e.g., regression test selection and change impact analysis—are often built as standalone tools, unable to share or reuse information among them. In this paper, we introduce a software evolution management engine, EvoMe, to streamline and simplify the development of such tools, allowing them to be easily prototyped using an intuitive query language and quickly deployed for different types of projects. EvoMe is based on differential factbase, a uniform exchangeable representation of evolving software artifacts, and can be accessed directly through a Web interface. We demonstrate the usage and key features of EvoMe on real open-source software projects. The demonstration video can be found at: http://youtu.be/6mMgu6rfnjY.

Cite:

@inproceedings{Wu2021EAS,
  author = {Wu, Xiuheng and Li, Mengyang and Li, Yi},
  booktitle = {Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering (ASE)},
  month = nov,
  pages = {1252--1256},
  title = {{EvoMe}: A Software Evolution Management Engine Based on Differential Factbase},
  year = {2021}
}