A GQM-based Approach for Software Process Patterns Recommendation
Zhangyuan Meng, Cheng Zhang, Beijun Shen, Yin Wei · Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering · 2017
A good software process can help project manager manage software development effectively and control development risks.For this reason, theory and experts' experience are concluded and put into process patterns.But it still requires human skills to search for appropriate process patterns in practice.To tackle this challenge, this paper proposes a Goal-Question-Metric (GQM) based approach to recommending software process patterns.The essential idea of this approach is to use a GQM method to design scenario questions for software process patterns, elicit the requirement of new project by answering these questions, and then recommend the optimal matching patterns to the project.In particular, we use a Latent Dirichlet Allocation model on the scenario descriptions of software process patterns to achieve a text-topic distribution, and then apply the K-means method to do text clustering, which facilitate scenario questions design a lot.We evaluate the performance of our topic clustering method by comparing it with that of the statistics method based on TF-IDF.The evaluation results show that our method contributes a high F-score which is 11.6% higher than that of the traditional TF-IDF approach.Furthermore, the average precision of recommendation can reach 57%.