Data-Driven Search-based Software Engineering

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 the researchers in this area? (3) What research approaches do researchers use? The paper briefly sets out to act as a practical guide to develop new DSE techniques and also to serve as a teaching resource. This paper also presents a resource (tiny.cc/data-se) for exploring DSE. The resource contains 89 artifacts which are related to DSE, divided into 13 groups such as requirements engineering, software product lines, software processes. All the materials in this repository have been used in recent software engineering papers; i.e., for all this material, there exist baseline results against which researchers can comparatively assess their new ideas.