Search-based Software Testing Driven by Domain Knowledge: Reflections and New Perspectives

TL;DR

This paper reflects on recent experimental results in search-based software testing driven by domain knowledge, highlighting unexpected findings and proposing new research directions to better integrate engineer expertise.

Contribution

It offers a new perspective on SBST techniques with domain knowledge, emphasizing the need for re-evaluation and future research directions.

Findings

Revealed bold and unexpected experimental results

Highlighted limitations in current SBST approaches

Suggested new research directions for integrating domain knowledge

Abstract

Search-based Software Testing (SBST) can automatically generate test cases to search for requirements violations. Unlike manual test case development, it can generate a substantial number of test cases in a limited time. However, SBST does not possess the domain knowledge of engineers. Several techniques have been proposed to integrate engineers' domain knowledge within existing SBST frameworks. This paper will reflect on recent experimental results by highlighting bold and unexpected results. It will help re-examine SBST techniques driven by domain knowledge from a new perspective, suggesting new directions for future research.