Computer Science and Engineering, Department of
Date of this Version
Spring 2-4-2013
Abstract
Test cases are represented in various formats depending on the process, the technique or the tool used to generate the tests. While different test case representations are necessary, this diversity challenges us in comparing test cases and leveraging strengths among them - a common test representation will help.
In this thesis, we define a new Test Case Language (TCL) that can be used to represent test cases that vary in structure and are generated by multiple test generation frameworks. We also present a methodology for transforming test cases of varying representations into a common format where they can be matched and analyzed. With the common representation in our test case description language, we define five advice functions to leverage the testing strength from one type of tests to improve the effectiveness of other type(s) of tests. These advice functions analyze test input values, method call sequences, or test oracles of one source test suite to derive advice, and utilize the advice to amplify the effectiveness of an original test suite. Our assessment shows that the amplified test suite derived from the advice functions has improved values in terms of code coverage and mutant kill score compared to the original test suite before the advice functions applied.
Comments
A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Computer Science, Under the Supervision of Professors Matthew Dwyer and Sebastian Elbaum. Lincoln, Nebraska: January, 2013
Copyright (c) 2013 Yurong Wang