The quality of a Software Requirements Specification (SRS) is measured in terms of quality properties such as completeness, conciseness, consistency and understandability. In general, evaluation of the SRS quality is done manually during review sessions. The evaluation process, however, is hugely dependent on the expertise of human experts i.e. the reviewers. In fact, the judgment of the human experts could also be inconsistent due to various factors including experience, knowledge and domain. The objectives of this study are to (1) identify feasible rules to measure SRS quality; and (2) help requirements engineer to improve their SRS quality. In this study, we analyzed SRS quality properties from the literature and identified quality factors that are feasible to be automated. From here, we identified two types of properties that are (1) requirements sentence quality (RSQ) and (2) requirements document quality (RDQ). For each of the type, its relevant quality indicators were identified. From here, rules on how to identify the quality indicators were further investigated and documented. As a case study, we implemented SRS Quality-Checker tool concept for demonstrating how the rules were implemented to measure the SRS quality
Adaptive Concept Map Approach for Software Requirements Validation
