Data-Driven Search-based Software Engineering
Vivek Nair, Amritanshu Agrawal, Jianfeng Chen, Wei Fu, George Mathew,, Tim Menzies, Leandro Minku, Markus Wagner, Zhe Yu

TL;DR
This paper introduces Data-Driven Search-based Software Engineering (DSE), combining MSR and SBSE to enhance software engineering insights and optimization, supported by a comprehensive resource for research and development.
Contribution
It presents a new integrated DSE framework, explores its research topics, data types, approaches, and provides a resource with baseline artifacts for the community.
Findings
DSE unifies MSR and SBSE for improved software engineering solutions.
The resource includes 89 artifacts across 13 categories for benchmarking.
DSE addresses diverse topics like requirements engineering and software processes.
Abstract
This paper introduces Data-Driven Search-based Software Engineering (DSE), which combines insights from Mining Software Repositories (MSR) and Search-based Software Engineering (SBSE). While MSR formulates software engineering problems as data mining problems, SBSE reformulates SE problems as optimization problems and use meta-heuristic algorithms to solve them. Both MSR and SBSE share the common goal of providing insights to improve software engineering. The algorithms used in these two areas also have intrinsic relationships. We, therefore, argue that combining these two fields is useful for situations (a) which require learning from a large data source or (b) when optimizers need to know the lay of the land to find better solutions, faster. This paper aims to answer the following three questions: (1) What are the various topics addressed by DSE? (2) What types of data are used by…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
