SCORE

Current industrial testing practices often generate test cases in a manual manner, which degrades both the effectiveness and efficiency of testing. To alleviate this problem, concolic testing generates test cases that can achieve high coverage in an automated fashion. One main task of concolic testing is to extract symbolic information from a concrete execution of a target program at runtime. Thus, a design decision on how to extract symbolic information affects efficiency, effectiveness, and applicability of concolic testing. We have developed a Scalable COncolic testing tool for REliable embedded software (SCORE) that targets embedded C programs. SCORE instruments a target C program to extract symbolic information and applies concolic testing to a target program in a scalable manner by utilizing a large number of distributed computing nodes. In this paper, we describe our design decisions that are implemented in SCORE and demonstrate the performance of SCORE through the experiments on the SIR benchmarks.