Automatic recommendation to omitted steps in use case specification

Completeness is one of the key attributes for a high-quality software requirements specification. Although incomplete requirements frequently occur in the requirements specification, it is rarely discovered. This turns out to be one of the major causes of software project failure. In order to handle this issue, this paper proposes an automatic approach to recommending omitted steps in a use case-based requirements specification. First, we automatically extract diverse scenario patterns by using the verb clustering algorithm and scenario flow graphs. Based on the scenario patterns, our approach detects omitted steps of user’s scenarios by the pattern matching algorithm and automatically recommends appropriate steps for the omitted parts. For validation of our approach, we have developed tool support, named ScenarioAmigo , and collected 231 use case specifications composing of 1874 scenario steps from 12 academic or proprietary projects. We first carried out the preliminary study to decide appropriate thresholds and weights. Then, we conducted three experiments as a quantitative performance evaluation. First, the cross-validation for the collected scenarios shows the 76% precision and 80% recall. Second, the comparison of recall of ScenarioAmigo to that of human experts obtained the 20% higher score. As the last experiment, we compared the result of ScenarioAmigo and human experts in terms of severity of each scenario and found that our approach could recommend normal as well as important scenarios, compared to the human experts.