Search‐based software test data generation: a survey

TLDR

Metaheuristic search techniques are increasingly used for automatic test data generation, offering efficient solutions to combinatorial problems, but prior work has been limited by software size, complexity, and the undecidable nature of the task. The paper aims to survey current work in search‑based software test data generation and propose future research directions. The authors conduct a comprehensive survey of existing research and outline potential future research directions across various subfields. © 2004 John Wiley & Sons, Ltd.

Abstract

Abstract The use of metaheuristic search techniques for the automatic generation of test data has been a burgeoning interest for many researchers in recent years. Previous attempts to automate the test generation process have been limited, having been constrained by the size and complexity of software, and the basic fact that, in general, test data generation is an undecidable problem. Metaheuristic search techniques offer much promise in regard to these problems. Metaheuristic search techniques are high‐level frameworks, which utilize heuristics to seek solutions for combinatorial problems at a reasonable computational cost. To date, metaheuristic search techniques have been applied to automate test data generation for structural and functional testing; the testing of grey‐box properties, for example safety constraints; and also non‐functional properties, such as worst‐case execution time. This paper surveys some of the work undertaken in this field, discussing possible new future directions of research for each of its different individual areas. Copyright © 2004 John Wiley & Sons, Ltd.