NFR Classification using Keyword Extraction and CNN on App Reviews

Documentation and fulfillment of software requirement are important aspects in measuring the success of a team in developing software. In the field of requirement engineering, there are two types of requirements namely functional requirements (FR) and non-functional requirements (NFR). Nowadays, requirements may also be found in app reviews, so this study conducted to classify non-functional requirements collected from app reviews. We classify keywords into 2 categories, namely project specific (PS) and non-project specific (NPS) and we propose an automatic method to extract them from app reviews and app description. We classify app reviews plus keyword extracted using convolutional neural network (CNN) and word2vec vectorization into several category of NFRs. Our proposed method managed to extract several keywords and improve the performance of the classification algorithm used. Our proposed method has an average accuracy of 80%, precision of 71%, and recall of 63%. The result show that our proposed method performed better than basic CNN and any classification algorithm.