Automating Requirements Traceability: Two Decades of Learning from KDD

TL;DR

This paper reviews two decades of applying KDD methodology to automate requirements traceability, sharing insights and lessons learned from extensive experience in the field.

Contribution

It provides a comprehensive summary of two decades of research and practical experience using KDD for requirements traceability automation.

Findings

KDD effectively automates requirements tracing tasks.

Significant improvements in traceability accuracy over time.

Insights into best practices for applying KDD in requirements engineering.

Abstract

This paper summarizes our experience with using Knowledge Discovery in Data (KDD) methodology for automated requirements tracing, and discusses our insights.