Automatic Identification of Potential Reusable Mobile Components

The software can be developed from scratch or the authors can make use of already developed software components, which can enhance the productivity and quality. On Internet, a large collection of software code is being offered by open-access repositories but, how one can identify a relevant and good quality code with minimum effort? In this paper, the domain relevancy of software components appraised, by extracting the different aspects processed by those software components, with help of Probabilistic Latent Semantic Analysis. Further, structural attributes of software components are calculated using software metrics and quality of the software is inferred by Neuro-fuzzy Inference engine, taking these metric values as input. The neuro-fuzzy system is optimized by selecting initial rule-base through ID3 decision tree algorithm.