Towards Feature-Aware Retrieval of Refinement Traces

Abstract—Requirements traceability supports practitioners in reaching higher project maturity and better product quality. To gain this support, traces between various artifacts of the software development process are required. Depending on the number of existing artifacts, establishing traces can be a time-consuming and error-prone task. Additionally, the manual creation of traces frequently interrupts the software development process. In order to overcome those problems, practitioners are asking for techniques that support the creation of traces (see Grand Challenge: Ubiquitous (GC-U)). In this paper, we propose the usage of a graph clustering algorithm to support the retrieval of refinement traces. Refinement traces are traces that exist between artifacts created in different phases of a development project, e.g., between features and use cases. We assessed the effectiveness of our approach in several TraceLab experiments. These experiments employ three standard datasets containing differing types of refinement traces. Results show that graph clustering can improve the retrieval of refinement traces and is a step towards the overall goal of ubiquitous traceability. Index Terms—requirements traceability; graph clustering; trace retrieval; TraceLab experiment; ubiquitous challenge (GC-U); I