An Investigation of Classification-Based Algorithms for Modified Condition/Decision Coverage Criteria

Abstract

During software development, white-box testing is used to examine the internal design of the program. One of the most important aspects of white-box testing is the code coverage. Among various test coverage measurements, the Modified Condition/Decision Coverage (MC/DC) is a structural coverage measure and can be used to assess the adequacy and quality of the requirements-based testing (RBT) process. NASA has proposed a method to select the needed test cases for satisfying this criterion. However, there may have some flaws in NASA's method. That is, the selected test cases may not satisfy the original definition of the MC/DC criterion in some particular situations and perhaps can not detect errors completely. On the other hand, NASA's method may be hard to detect some operator errors. For example, we may not be able to detect the incorrectly coding or for xor in some cases. Additionally, this method is too complex and could take a lot of time to obtain the needed test cases. In this paper, we will propose a classification-based algorithm to select the needed test cases. First, test cases will be classified based on the outcome value of expression and the target condition. After classifying all test cases, MC/DC pairs can be found quickly, conveniently and effectively. Also, if there are some missing (unfound) test cases, our proposed classification-based method can also suggest to developers what kinds of test cases have to be generated. Finally, some experiments are performed based upon real programs to evaluate the performance and effectiveness of our proposed classification-based algorithm.