Quantifying the Characteristics of Java Programs That May Influence Symbolic Execution from a Test Data Generation Perspective

Testing plays a key role in assessing the quality of a software product. During testing, a program is run in hopes of finding faults. As exhaustive testing is seldom possible, specific testing criteria have been proposed to help testers to devise test cases that cover the most relevant faulty scenarios. Manually creating test cases that satisfy these criteria is time consuming, error prone, and unwieldy. Symbolic execution has been used as an effective way of automatically generating test data that meets those criteria. Although this technique has been used for over three decades, several challenges remain, such as path explosion, precision of floating-point data, constraints with complex expressions, and dependency of external libraries. In this paper, we explore a sample of 100 open source Java projects in order to analyze characteristics that are relevant to generate test data using symbolic execution. The results provide valuable insight into how researchers and practitioners can tailor symbolic execution techniques and tools to better suit the needs of different Java applications.