![]() The data extraction process of the SLR showed that (1) Latent Dirichlet Allocation (LDA) topic modeling is among the widely used ML algorithm in the selected studies and (2) precision and recall are amongst the most commonly utilized evaluation methods for measuring the performance of these ML algorithms. This SLR study found 2,484 published papers related to RE and SO. This paper reports a systematic literature review (SLR) collecting empirical evidence published up to May 2020. To identify or recognize and classify the kinds of ML algorithms used for software requirements identification primarily on SO. Nonetheless, a complete, systematic, and detailed comprehension of these ML based techniques is considerably scarce. ![]() The appropriateness of ML-based techniques to tackle this issue has revealed quite substantial results, much effective than those produced by the usual available natural language processing (NLP) techniques. One such challenging issue is the effective identification and classification of the software requirements on Stack Overflow (SO) for building quality systems. The improvements made in the last couple of decades in the requirements engineering (RE) processes and methods have witnessed a rapid rise in effectively using diverse machine learning (ML) techniques to resolve several multifaceted RE issues.
0 Comments
Leave a Reply. |