We present results for the "Impact Project Focus Area" on the topic of symbolic execution as used in software testing. Symbolic execution is a program analysis technique introduced in the 70s that has received renewed interest in recent years, due to algorithmic advances and increased availability of computational power and constraint solving technology. We review classical symbolic execution and some modern extensions such as generalized symbolic execution and dynamic test generation. We also give a preliminary assessment of the use in academia, research labs, and industry.
Abstract. Recent work has used variations of symbolic execution to automatically generate high-coverage test inputs [3,4,7,8,14]. Such tools have demonstrated their ability to find very subtle errors. However, one challenge they all face is how to effectively handle the exponential number of paths in checked code. This paper presents a new technique for reducing the number of traversed code paths by discarding those that must have side-effects identical to some previously explored path. Our results on a mix of open source applications and device drivers show that this (sound) optimization reduces the numbers of paths traversed by several orders of magnitude, often achieving program coverage far out of reach for a standard constraint-based execution system.
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