Mohsen Ahmadi (Arizona State University), Pantea Kiaei (Worcester Polytechnic Institute), Navid Emamdoost (University of Minnesota)

Mutation analysis is an effective technique to evaluate a test suite adequacy in terms of revealing unforeseen bugs in software. Traditional source- or IR-level mutation analysis is not applicable to the software only available in binary format. This paper proposes a practical binary mutation analysis via binary rewriting, along with a rich set of mutation operators to represent more realistic bugs. We implemented our approach using two state-of-the-art binary rewriting tools and evaluated its effectiveness and scalability by applying them to SPEC CPU benchmarks. Our analysis revealed that the richer mutation operators contribute to generating more diverse mutants, which, compared to previous works leads to a higher mutation score for the test harness. We also conclude that the reassembleable disassembly rewriting yields better scalability in comparison to lifting to an intermediate representation and performing a full translation.

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Hengyi Liang, Ruochen Jiao (Northwestern University), Takami Sato, Junjie Shen, Qi Alfred Chen (UC Irvine), and Qi Zhu (Northwestern University) Best Short Paper Award Winner!

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Vijay k. Gurbani and Cynthia Hood ( Illinois Institute of Technology), Anita Nikolich (University of Illinois), Henning Schulzrinne (Columbia University) and Radu State (University of Luxembourg)

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Kristopher Micinski (Haverford College), Thomas Gilray (University of Alabama, Birmingham), Daniel Votipka (University of Maryland), Michelle L. Mazurek (University of Maryland), Jeffrey S. Foster (Tufts University)

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