A fuzzy logic-based quality model for identifying microservices with low maintainability

被引:0
|
作者
Yilmaz, Rahime [1 ]
Buzluca, Feza [2 ]
机构
[1] Istanbul Tech Univ, Comp Engn Dept, Altinbas Univ, Istanbul, Turkiye
[2] Istanbul Tech Univ, Comp Engn Dept, Istanbul, Turkiye
关键词
Microservice; Microservice quality; Quality model; Quality measurement; Maintainability; Fuzzy logic; DESIGN;
D O I
10.1016/j.jss.2024.112143
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Microservice Architecture (MSA) is a popular architectural style that offers many advantages regarding quality attributes, including maintainability and scalability. Developing a system as a set of microservices with expected benefits requires a quality assessment strategy that is established on the measurements of the system 's properties. This paper proposes a hierarchical quality model based on fuzzy logic to measure and evaluate the maintainability of MSAs considering ISO/IEC 250xy SQuaRE (System and Software Quality Requirements and Evaluation) standards. Since the qualitative bounds of low-level quality attributes are inherently ambiguous, we use a fuzzification technique to transform crisp values of code metrics into fuzzy levels and apply them as inputs to our quality model. The model generates fuzzy values for the quality sub-characteristics of the maintainability, i.e., modifiability and testability, converted to numerical values through defuzzification. In the last step, using the values of the sub-characteristics, we calculate numerical scores indicating the maintainability level of each microservice in the examined software system. This score was used to assess the quality of the microservices and decide whether they need refactoring. We evaluated our approach by creating a test set with the assistance of three developers, who reviewed and categorized the maintainability levels of the microservices in an open-source project based on their knowledge and experience. They labeled microservices as low, medium, or high, with low indicating the need for refactoring. Our method for identifying low-labeled microservices in the given test set achieved 94% accuracy, 78% precision, and 100% recall. These results indicate that our approach can assist designers in evaluating the maintainability quality of microservices.
引用
收藏
页数:17
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