IFSDA: An intuitionistic fuzzy set-based data aggregation approach for software maintainability evaluation

Abstract

The software maintainability which is an important part of software quality and trustworthiness has always been a hot topic in software engineering domain. The measurements of the software are multi-source and heterogeneous data, which result in big challenges on data aggregation for software maintainability evaluation. In this paper, an Intuitionistic Fuzzy Set-based Data Aggregation (IFSDA) approach is developed to evaluate the software maintainability. In order to unify the heterogeneous measurements, a Grade Mapping method is proposed to transform them to the membership function and the non-membership function based on Intuitionistic Fuzzy Set (IFS). The Einstein operation-based aggregation algorithm is applied to aggregate the measurements from the lower level to the higher level under the software maintainability index system. In the experiments, 880 versions of Linux kernels are collected and evaluated to test the IFSDA approach and the maintainability evolution of the Linux kernels can be studied from the experiment results and analysis.