TAPHSIR: Towards AnaPHoric Ambiguity Detection and ReSolution In Requirements
This addresses the issue of misunderstandings in software development due to ambiguous pronouns in requirements, though it appears incremental as it builds on existing NLP methods.
The paper tackles the problem of anaphoric ambiguity in requirements specifications by introducing TAPHSIR, a tool that detects ambiguous pronouns and resolves them automatically, achieving public availability with a hybrid approach combining machine learning and BERT.
We introduce TAPHSIR, a tool for anaphoric ambiguity detection and anaphora resolution in requirements. TAPHSIR facilities reviewing the use of pronouns in a requirements specification and revising those pronouns that can lead to misunderstandings during the development process. To this end, TAPHSIR detects the requirements which have potential anaphoric ambiguity and further attempts interpreting anaphora occurrences automatically. TAPHSIR employs a hybrid solution composed of an ambiguity detection solution based on machine learning and an anaphora resolution solution based on a variant of the BERT language model. Given a requirements specification, TAPHSIR decides for each pronoun occurrence in the specification whether the pronoun is ambiguous or unambiguous, and further provides an automatic interpretation for the pronoun. The output generated by TAPHSIR can be easily reviewed and validated by requirements engineers. TAPHSIR is publicly available on Zenodo (DOI: 10.5281/zenodo.5902117).