Using Frame Embeddings to Identify Semantically Related Software Requirements
Waad Alhoshan, Riza Batista-Navarro, Liping Zhao · Research Explorer (The University of Manchester) · 2019
In requirements engineering (RE), software requirements typically come in the form of unstructured text, written in natural language. Consequently, identifying related requirements becomes a time consuming task. In this paper, we propose a novel method for measuring semantic relatedness between software requirements, with the aim to develop software tools that can automate or semi-automate the processing of identifying requirements traceability in requirements documents. The proposed method is based on an embedding-based representation of semantic frames in FrameNet, trained on a large corpus of user requirements. Applying the method to the task of detecting semantically related software requirements, the performance of the proposed method was evaluated against a manually labelled corpus and baseline system. Our method obtained a satisfactory performance of 86.36% against a manually labelled data set of software requirements, and outperformed the baseline system by 24 percentage points. These encouraging results demonstrate the potential of our method to be integrated with RE tools for facilitating software requirement analysis and traceability tasks.