Abstract
Considerable research has demonstrated how effective requirements engineering is critical for the success of software projects. Requirements engineering has been established and recognized as one of the most important aspects of software engineering as of late. It is noteworthy to mention that requirement consistency is a critical factor in project success, and conflicts in requirements lead to waste of cost, time, and effort. A considerable number of research studies have shown the risks and problems caused by working with requirements that are in conflict with other requirements. These risks include running overtime or over budget, which may lead to project failure. At the very least, it would result in the extra expended effort. Various studies have also stated that failure in managing requirement conflicts is one of the main reasons for unsuccessful software projects due to high cost and insufficient time. Many prior research studies have proposed manual techniques to detect conflicts, whereas other research recommends automated approaches based on human analysis. Moreover, there are different resolutions for conflicting requirements. Our previous work proposed a scheme for dealing with this problem using a novel intelligent method to detect conflicts and resolve them. A rule-based system was proposed to identify conflicts in requirements, and a genetic algorithm (GA) was used to resolve conflicts. The objective of this work is to assess and evaluate the implementation of the method of minimizing the number of conflicts in the requirements. The methodology implemented comprises two different stages. The first stage, detecting conflicts using a rule-based system, demonstrated a correct result with 100% accuracy. The evaluation of using the GA to resolve and reduce conflicts in the second stage also displayed a good result and achieved the desired goal as well as the main objective of the research.