Grammar-agnostic symbolic execution by token symbolization

Abstract

Parsing code exists extensively in software. Symbolic execution of complex parsing programs is challenging. The inputs generated by the symbolic execution using the byte-level symbolization are usually rejected by the parsing program, which dooms the effectiveness and efficiency of symbolic execution. Complex parsing programs usually adopt token-based input grammar checking. A token sequence represents one case of the input grammar. Based on this observation, we propose grammar-agnostic symbolic execution that can automatically generate token sequences to test complex parsing programs effectively and efficiently. Our method's key idea is to symbolize tokens instead of input bytes to improve the efficiency of symbolic execution. Technically, we propose a novel two-stage algorithm: the first stage collects the byte-level constraints of token values; the second stage employs token symbolization and the constraints collected in the first stage to generate the program inputs that are more possible to pass the parsing code. We have implemented our method on a Java Pathfinder (JPF) based concolic execution engine. The results of the extensive experiments on real-world Java parsing programs demonstrate the effectiveness and efficiency in testing complex parsing programs. Our method detects 6 unknown bugs in the benchmark programs and achieves orders of magnitude speedup to find the same bugs.