Survey of many-objective optimization in SBSE

Publication

A. Ramírez, J.R. Romero* and S. Ventura. “A survey of many-objective optimisation in search-based software engineering”. Journal of Systems and Software, vol. 149, pp. 382-395. 2019.

Abstract

Search-based software engineering (SBSE) is changing the way traditional software engineering (SE) activities are carried out by reformulating them as optimization problems. The natural evolution of SBSE is bringing new challenges, such as the need of a large number of objectives to formally represent the many decision criteria involved in the resolution of SE tasks. This suggests that SBSE is moving towards many-objective optimization, an emerging area that provides advanced techniques to cope with high-dimensional optimization problems. To analyze this phenomenon, this paper surveys relevant SBSE literature focused on the resolution of many-objective problems. From the gathered knowledge, current limitations regarding problem formulation, algorithm selection, experimental design and industrial applicability are discussed. Through the analysis of observed trends, this survey provides a historical perspective and future lines of research concerning the adoption of many-objective optimization within SBSE.

Highlights

  • Software engineering problems often present many decision factors to be optimized.
  • Many-objective optimization brings advanced search methods well-suited for SBSE.
  • The literature survey identifies many-objective SBSE as an emerging research topic.
  • We discuss current findings and outline open challenges and future work in the field.

Additional material

List of candidate papers (bib format)

List of selected papers (bib format)

List of variant papers (bib format)

Data extraction summary sheet (Excel format)

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