Assessing the benefits of search-based approaches when designing self-adaptive systems: a controlled experiment

Abstract

Background: The well-orchestrated use of distilled experience, domain-specific knowledge, and well-informed trade-off decisions is imperative if we are to design effective architectures for complex software-intensive systems. In particular, designing modern self-adaptive systems requires intricate decision-making over a remarkably complex problem space and a vast array of solution mechanisms. Nowadays, a large number of approaches tackle the issue of endowing software systems with self-adaptive behavior from different perspectives and under diverse assumptions, making it harder for architects to make judicious decisions about design alternatives and quality attributes trade-offs. It has currently been claimed that search-based software design approaches may improve the quality of resulting artifacts and the productivity of design processes, as a consequence of promoting a more comprehensive and systematic representation of design knowledge and preventing design bias and false intuition. To the best of our knowledge, no empirical studies have been performed to provide sound evidence of such claim in the self-adaptive systems domain.\r\rMethods: This paper reports the results of a quasi-experiment performed with 24 students of a graduate program in Distributed and Ubiquitous Computing. The experiment evaluated the design of self-adaptive systems using a search-based approach proposed by us, in contrast to the use of a non-automated approach based on architectural styles catalogs. The goal was to investigate to which extent the adoption of search-based design approaches impacts on the effectiveness and complexity of resulting architectures. In addition, we also analyzed the approach’s potential for leveraging the acquisition of distilled design knowledge.\r\rResults: Our findings show that search-based approaches can improve the effectiveness of resulting self-adaptive systems architectures and reduce their design complexity. We found no evidence regarding the approach’s potential for leveraging the acquisition of distilled design knowledge by novice software architects.\r\rConclusion: This study contributes to reveal empirical evidence on the benefits of search-based approaches when designing self-adaptive systems architectures. The results presented herein increase our belief that the systematic representation of distilled design knowledge and the adoption of search-based design approaches indeed lead to improved architectures.