An Automatic Approach to Detect Traceability Links Using Fuzzy Logic

Background: The Requirements Trace ability Matrix (RTM) is one of the most commonly used ways to represent requirements trace ability. Nevertheless, the difficulty of manually creating such a matrix motivates the investigation into alternatives to generate it automatically. Objective: This article presents one approach to automatically create the RTM based on fuzzy logic, called RTM-Fuzzy, which combines two other approaches, one based on functional requirements´ entry data - called RTM-E - and the other based on natural language processing - called RTM-NLP. Method: To create the RTM based on fuzzy logic, the RTM-E and RTM-NLP approaches were used as entry data for the fuzzy system rules. Aimed at evaluating these approaches, an experimental study was conducted where the RTMs created automatically were compared to the reference RTM (oracle) created manually based on stakeholder knowledge. Results: On average the approaches matched the following results in relation to the reference RTM: RTM-E achieved 78% effectiveness, RTM-NLP 76% effectiveness and the RTM-Fuzzy 83% effectiveness. Conclusions: The results show that using fuzzy logic to combine and generate a new RTM offered an enhanced effectiveness for determining the requirement´s dependencies and consequently the requirement´s trace ability links.