A Pipeline for Automating Labeling to Prediction in Classification of NFRsIndustrial Innovation Paper
Non-Functional Requirements (NFRs) focus on the operational constraints of the software system. Early detection of NFRs enables their incorporation into the architectural design at an initial stage, a practice obviously preferable to expensive refactoring at a later stage. Automated identification and classification of NFRs has therefore seen numerous efforts using rule-based, machine learning and deep learning-based approaches. One of the major challenges for such an automation is the manual effort that needs to be invested into labeling of training data. This is a concern for large software vendors who typically work on a variety of applications in diverse domains. We address this challenge by designing a pipeline that facilitates classification of NFRs using only a limited amount ( 20% of an available new dataset) of labeled data for training. We (1) employed Snorkel to automatically label a dataset comprising NFRs from various Software Requirement Specification documents, (2) trained several classifiers using it, and (3) reused these pre-trained classifiers using a Transfer Learning approach to classify NFRs in industry-specific datasets. From among the various language model classifiers, the best results have been obtained for a BERT based classifier fine-tuned to learn the linguistic intricacies of three different domain-specific datasets from real-life projects.
Fri 24 SepDisplayed time zone: Eastern Time (US & Canada) change
08:00 - 09:20 | Quality RequirementsIndustrial Innovation Papers / Research Papers / RE@Next! Papers at Basilica Chair(s): Jennifer Horkoff Chalmers and the University of Gothenburg | ||
08:00 30mTalk | Exploring Explainability: A Definition, a Model, and a Knowledge CatalogueResearch Paper Research Papers Larissa Chazette Leibniz University Hannover, Wasja Brunotte Leibniz University Hannover, Timo Speith Saarland University Pre-print | ||
08:30 30mTalk | A Pipeline for Automating Labeling to Prediction in Classification of NFRsIndustrial Innovation Paper Industrial Innovation Papers Ranit Chatterjee TCS Research, Abdul Ahmed TCS Research, Preethu Rose Anish TCS Research, Brijendra Suman TCS Research, Prashant Lawhatre TCS Research, Smita Ghaisas TCS Research | ||
09:00 20mTalk | Text Mining for Standardized Quality Criteria of Natural-Language IT RequirementsRE@Next RE@Next! Papers |