A Semantic Approach for Traceability Link Recovery in Aerospace Requirements Management System

The efficiency and effectiveness of the recovery of traceability links in requirements management is becoming increasingly important within interdisciplinary industry. Due to the complexity of production development such as automotive, software industry and the aerospace industry, managing requirements is indispensable and challenging. Products in these industries are constantly being updated and modified as the understanding of risks increases with experience and new products are developed in light of such risk. Therefore, the traceability links among the requirements artifacts, which fulfill business objectives, is so critical to reducing the risk and ensuring the success of products. To that end, this paper propose a semantic based traceability link recovery (STLR) architecture. According to best of our knowledge this is the first architectural approach that uses DBpedia knowledge-base and Bablenet 2.5 multilingual dictionary and semantic network for finding similarity among requirements and the automation of the recovery traceability links using our novel Triple extraction, and Triple disambiguation algorithm. Our preliminary results show the effectiveness in term of precision and recall compared to Vector Space Model and Wu Palmer algorithm.