AsFuzzer: Differential Testing of Assemblers with Error-Driven Grammar InferenceACM SIGSOFT Distinguished Paper Award
Assembler is a critical component of the compiler toolchain, which has been less tested than the other components. Unfortunately, current grammar-based fuzzing techniques suffer from several challenges when testing assemblers. First, each different assembler accepts different grammar rules and syntaxes, and there are no existing assembly grammar specifications. Second, not every assembler is open-source, which makes it difficult to extract grammar rules from the source code. While existing black-box grammar inference approaches are applicable to such closed-source assemblers, they suffer from the scalability issue, which renders them impractical for testing assemblers. To address these challenges, we propose a novel way to test assemblers by automatically inferring their grammar rules with only a few queries to the target assemblers by leveraging their error messages. The key insight is that assembly error messages often deliver useful information to infer the underlying grammar rules. We have implemented our technique in a tool named AsFuzzer, and evaluated it on 4 real-world assemblers including Clang-integrated assembler (Clang), GNU assembler (GAS), Intel’s assembler (ICC), and Microsoft macro assembler (MASM). With AsFuzzer, we have successfully found 497 buggy instruction opcodes for six popular architectures, and reported them to the developers.
Wed 18 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
13:30 - 14:50 | Domain-Specific TestingTechnical Papers at EI 10 Fritz Paschke Chair(s): Marcelo d'Amorim North Carolina State University | ||
13:30 20mTalk | UPBEAT: Test Input Checks of Q# Quantum Libraries Technical Papers Tianmin Hu Northwest University, Guixin Ye Northwest University, Zhanyong Tang Northwest University, Shin Hwei Tan Concordia University, Huanting Wang University of Leeds, Meng Li Hefei University of Technology, Zheng Wang University of Leeds DOI | ||
13:50 20mTalk | Towards More Complete Constraints for Deep Learning Library Testing via Complementary Set Guided Refinement Technical Papers Gwihwan Go Tsinghua University, Chijin Zhou Tsinghua University, Quan Zhang Tsinghua University, Xiazijian Zou Central South University, Heyuan Shi Central South University, Yu Jiang Tsinghua University DOI | ||
14:10 20mTalk | AsFuzzer: Differential Testing of Assemblers with Error-Driven Grammar InferenceACM SIGSOFT Distinguished Paper Award Technical Papers DOI | ||
14:30 20mTalk | Ma11y: A Mutation Framework for Web Accessibility Testing Technical Papers Mahan Tafreshipour University of California at Irvine, Anmol Vilas Deshpande University of California at Irvine, Forough Mehralian University of California at Irvine, Iftekhar Ahmed University of California at Irvine, Sam Malek University of California at Irvine DOI |