A Similarity-based Test Case Quality Metric using Historical Failure Data

Description

A test case is a set of input data and expected output, designed to verify whether the system under test satisfies all requirements and works correctly. An effective test case reveals a fault when the actual output differs from the expected output (i.e., the test case fails). The effectiveness of test cases is estimated using quality metrics, such as code coverage, size, and historical fault detection. Prior studies have shown that previously failing test cases are highly likely to fail again in the next releases; therefore, they are ranked higher. However, in practice, a failing test case may not be exactly the same as a previously failed test case, but quite similar. In this thesis, I have defined a metric that estimates test case quality using its similarity to the previously failing test cases. Moreover, I have evaluated the effectiveness of the proposed test quality metric through detailed empirical study. / February 2016

Links & Downloads

1. Noor, Tanzeem, and Hadi Hemmati. "Test case analytics: Mining test case traces to improve risk-driven testing." Software Analytics (SWAN), 2015 IEEE 1st International Workshop on. IEEE, 2015.
2. Noor, Tanzeem Bin, and Hadi Hemmati. "A similarity-based approach for test case prioritization using historical failure data." International Symposium on Software Reliability Engineering (ISSRE), 2015 IEEE 26th International Symposium on. IEEE, 2015.
3. http://hdl.handle.net/1993/31045

Tags

Software Testing, Quality Metric

Additional Fields

Identifer	oai:union.ndltd.org:MANITOBA/oai:mspace.lib.umanitoba.ca:1993/31045
Date	January 2015
Creators	Noor, Tanzeem Bin
Contributors	Hemmati, Hadi (Computer Science), Wang, Yang (Computer Science) Jeffrey, Ian (Electrical and Computer Engineering)
Publisher	IEEE, IEEE
Source Sets	University of Manitoba Canada
Detected Language	English