Test-Data Generation Guided by Static Defect Detection  

作　　者：郝丹 张路 刘明浩 李合 孙家骕 

机构地区：[1]Key Laboratory of High Confidence Software Technologies, Ministry of Education [2]Institute of Software, School of Electronics Engineering and Computer Science, Peking University

出　　处：《Journal of Computer Science & Technology》2009年第2期284-293,共10页计算机科学技术学报（英文版）

基　　金：sponsored by the National High-Tech Research and Development 863 Program of China under Grant No.2007AA010301;the National Natural Science Foundation of China under Grant Nos. 60803012 and 90718016;China Postdoctoral Science Foundation funded project under Grant No. 20080440254

摘　　要：Software testing is an important technique to assure the quality of software systems, especially high-confidence systems. To automate the process of software testing, many automatic test-data generation techniques have been proposed. To generate effective test data, we propose a test-data generation technique guided by static defect detection in this paper. Using static defect detection analysis, our approach first identifies a set of suspicious statements which are likely to contain faults, then generates test data to cover these suspicious statements by converting the problem of test-data generation to the constraint satisfaction problem. We performed a case study to validate the effectiveness of our approach, and made a simple comparison with another test-data generation on-line tool, JUnit Factory. The results show that, compared with JUnit Factory, our approach generates fewer test data that are competitive on fault detection.Software testing is an important technique to assure the quality of software systems, especially high-confidence systems. To automate the process of software testing, many automatic test-data generation techniques have been proposed. To generate effective test data, we propose a test-data generation technique guided by static defect detection in this paper. Using static defect detection analysis, our approach first identifies a set of suspicious statements which are likely to contain faults, then generates test data to cover these suspicious statements by converting the problem of test-data generation to the constraint satisfaction problem. We performed a case study to validate the effectiveness of our approach, and made a simple comparison with another test-data generation on-line tool, JUnit Factory. The results show that, compared with JUnit Factory, our approach generates fewer test data that are competitive on fault detection.

关 键 词：test-data generation suspicious statements software testing constraint satisfaction problem 

分 类 号：TP311.53[自动化与计算机技术—计算机软件与理论]