The Acceptance of Search-Based Software Engineering Techniques: An Empirical Evaluation Using the Technology Acceptance Model

Abstract

Numerous topics in software engineering can be formulated as optimization problems. Due to the large scale of modern software systems, the methods of mathematical optimization have high computational complexity, and their application in many cases is not possible. To overcome this problem, search-based software engineering (SBSE) develops and applies metaheuristic search techniques to find near-optimal solutions. Despite the significant development that the SBSE techniques (SBSET) achieved in the last years, the level of SBSET use is very low. Therefore, this paper proposes and tests a model which evaluates and predicts the acceptance of SBSET by software engineering practitioners. The model is based on the technology acceptance model (TAM) and extended by the SBSET desired properties. A total of 163 practitioners participated in the study. The perceived ease of use, perceived usefulness, and organizational and team-based factors were all found to have significant positive effects on the actual use of the SBSET. This study also analyses the obstacles of SBSET acceptance and provides several proposals for its improvement in the software industry.