Int J Performability Eng ›› 2020, Vol. 16 ›› Issue (1): 78-86.doi: 10.23940/ijpe.20.01.p9.7886

• Orginal Article • Previous Articles     Next Articles

Fuzzy Multi-Attribute Decision Making for Software Defect Detection Model Evaluation

Yunjie Leia, Ying Maab*(), Shunyi Chena, Yu Sunbc*(), and Keshou Wuad   

  1. aXiamen University of Technology, No.600 Ligong Road, Jimei District, Xiamen, 361024, China
    bKey Laboratory of Data Mining and Intelligent Recommendation, Fujian Province University, No.600 Ligong Road, Jimei District, Xiamen, 361024, China
    cDepartment of Education and Learning Technology, Naional Tsing Hua University, Kuang-Fu Road, Hsinchu, Taiwan, 30013, China
    dEngineering Research Center for Software Testing and Evaluation of Fujian Province, No.600 Ligong Road, Jimei District, Xiamen, 361024, China
  • Submitted on ; Revised on ; Accepted on
  • Contact: Ying Ma,Yu Sun E-mail:maying@xmut.edu.cn;sunyu6336@163.com
  • Supported by:
    This work was supported in part by the National Natural Science Foundation of China (Grant No. 61502404), Natural Science Foundation of Fujian Province of China (Grant No. 2019J01851), Distinguished Young Scholars Foundation of Fujian Educational Committee (Grant No. DYS201707), Xiamen Science and Technology Program (Grant No. 3502Z20183059), and Open Fund of Key Laboratory of Data mining and Intelligent Recommendation, Fujian Province University. We thank the anonymous reviewers for their great helpful comments.

Abstract:

With the continuous expansion of the computer system application field, the complexity of software system is also improving. Software defect detection has gradually become an important research direction in the field of software engineering. At present, the mixed statistics and machine learning methods have been proved to be able to implement software defect detection models well. However, the evaluation index of the detection model is diverse and it is difficult to determine which model evaluation indicators are in line with the actual expectations. Aiming at this kind of problem, a software defect detection model evaluation method based on fuzzy multi-objective attribute decision making is proposed. First, extract the characteristics of software modules, use McCabe and Halstead software modules to measure attributes. Then select five common classification algorithms to establish software defect detection models, and obtain seven evaluation index values of each model. Further, based on fuzzy multi-objective attribute decision making method with fuzzy analytic hierarchy process (FAHP) to compare multiple objectives, and obtain the results of index determination. Finally, the fuzzy evaluation algorithm is used to convert the evaluation index of qualitative evaluation into quantitative evaluation to obtain the final decision evaluation value. The experimental results show the effectiveness and practicality of the method.

Key words: multi-objective decision making algorithm, software defect detection, model evaluation