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