FINALIsT2: Feature identification, localization, and tracing tool
Andreas Burger, Sten Grüner · 2018
Feature identification and localization is a complicated and error-prone task. Nowadays it is mainly done manually by lead software developer or domain experts. Sometimes these experts are no longer available or cannot support in the feature identification and localization process. Due to that we propose a tool which supports this process with an iterative semi-automatic workflow for identifying, localizing and documenting features. Our tool calculates a feature cluster based on an defined entry point that is found by using information retrieval techniques. This feature cluster will be iteratively refined by the user. This iterative feedback-driven workflow enables developer which are not deeply involved in the development of the software to identify and extract features properly. We evaluated our tool on an industrial smart control system for electric motors with first promising results.