Test-Data Generation Guided by Static Defect Detection

被引:12
作者
Hao, Dan
Zhang, Lu [1 ]
Liu, Ming-Hao
Li, He
Sun, Jia-Su
机构
[1] Minist Educ, Key Lab High Confidence Software Technol, Beijing 100871, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
test-data generation; suspicious statements; software testing; constraint satisfaction problem;
D O I
10.1007/s11390-009-9224-5
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
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.
引用
收藏
页码:284 / 293
页数:10
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