Challenges on applying genetic improvement in JavaScript using a high-performance computer

Authors

  • Fábio de Almeida Farzat COPPE/UFRJ
  • Márcio de Oliveira Barros PPGI/UNIRIO
  • Guilherme Horta Travassos COPPE/UFRJ

Keywords:

Genetic Improvement, Source code Optimization, Search Based Software Engineering

Abstract

Genetic Improvement is an area of Search Based Software Engineering that aims to apply evolutionary computing operators to the software source code to improve it according to one or more quality metrics. This article describes challenges related to experimental studies using Genetic Improvement in JavaScript (an interpreted and non-typed language). It describes our experience on performing a study with fifteen projects submitted to genetic improvement with the use of a supercomputer. The construction of specific software infrastructure to support such an experimentation environment reveals peculiarities (parallelization problems, management of threads, etc.) that must be carefully considered to avoid future research threats to validity such as dead-ends, which make it impossible to observe relevant phenomena (code transformation) to the understanding of software improvements and evolution.

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Published

2018-10-06

How to Cite

de Almeida Farzat, F., de Oliveira Barros, M., & Horta Travassos, G. (2018). Challenges on applying genetic improvement in JavaScript using a high-performance computer. Journal of Software Engineering Research and Development, 6, 12:1 – 12:19. Retrieved from https://sol.sbc.org.br/journals/index.php/jserd/article/view/444

Issue

Section

Research Article