TAPHSIR: Towards AnaPHoric Ambiguity Detection and ReSolution In Requirements

TL;DR

TAPHSIR is a hybrid tool that detects and resolves anaphoric ambiguities in requirements specifications, aiding requirements engineers in clarifying pronouns to prevent misunderstandings during development.

Contribution

It introduces a novel hybrid approach combining machine learning and BERT-based models for automatic ambiguity detection and anaphora resolution in requirements.

Findings

Effective detection of ambiguous pronouns in requirements.

Automatic interpretation of anaphora improves clarity.

Tool is publicly available for use and validation.

Abstract

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).