Fuzzing C++ Compilers via Type-Driven Mutation

C++ is a system-level programming language for modern software development, which supports multiple programming paradigms, including object-oriented, generic, and functional programming. The intrinsic complexity of these paradigms and their interactions grants C++ powerful expressiveness while posing significant challenges for compilers in correctly implementing its type system. A type system encompasses various aspects such as type inference, type checking, subtyping, type conversions, generics, scoping, and binding. However, systematic testing of the type systems of C++ compilers remains largely underexplored in existing studies. In this work, we present TyMut, the first approach specifically designed to test the C++ type system. TyMut is a mutation-based compiler fuzzer equipped with advanced type-driven mutation operators, carefully crafted to target intricate type-related features such as template generics, type conversions, and inheritance. Beyond differential testing, TyMut introduces enhanced test oracles through a must analysis that partially confirms the validity of generated programs. Specifically, mutation operators are classified into well-formed and not-well-formed: Programs generated by well-formed mutation operators are valid and must be accepted by compilers. Programs generated by not-well-formed operators are validated against a set of well-formedness rules. Any violation indicates the program is invalid and must be rejected. For programs that pass the rules but lack a definitive oracle, TyMut applies differential testing to identify behavioral inconsistencies across compilers. The testing campaign took about 32 hours to generate and test 250584 programs. The must analysis provides definite test oracles for nearly 80% of all generated programs. TyMut uncovered 102 bugs in the recent versions of GCC and Clang, with 56 confirmed as new bugs by compiler developers. Among the confirmed bugs, 26 of them cause compiler crashes, and more than 50% cause miscompilation. Additionally, 7 of them had remained hidden for over 20 years, 22 for over 10 years, and 39 for over 5 years. One long-standing bug discovered by TyMut was later confirmed as the root cause of a real-world issue in TensorFlow. Before submitting this paper, 13 bugs were fixed, most of which were fixed within 60 days. Notably, some unconfirmed bugs have led to in-depth discussions among developers. For instance, one bug led a compiler developer to submit a new issue to the C++ language standard, showing that we uncovered ambiguities in the language specification.

Authors

Institutions

Publication Details

Journal
Proceedings of the ACM on Programming Languages
Published
2025-10-09
DOI
https://doi.org/10.1145/3763094
Citations
2
Primary Topic
Software Testing and Debugging Techniques
Type
article
Field-Weighted Citation Impact
4.62
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Fuzzing C++ Compilers via Type-Driven Mutation

Xing Zhang, Youfang Lin, Chong Chen, Dan Hao et al.
2 citations
Proceedings of the ACM on Programming Languages
Software Testing and Debugging Techniques
4.62
article

Fuzzing C++ Compilers via Type-Driven Mutation

Xing Zhang, Youfang Lin, Chong Chen, Dan Hao, Junjie Chen, Bo Wang, Jun Sun, Ming Deng
article en
2 citations

Abstract

C++ is a system-level programming language for modern software development, which supports multiple programming paradigms, including object-oriented, generic, and functional programming. The intrinsic complexity of these paradigms and their interactions grants C++ powerful expressiveness while posing significant challenges for compilers in correctly implementing its type system. A type system encompasses various aspects such as type inference, type checking, subtyping, type conversions, generics, scoping, and binding. However, systematic testing of the type systems of C++ compilers remains largely underexplored in existing studies. In this work, we present TyMut, the first approach specifically designed to test the C++ type system. TyMut is a mutation-based compiler fuzzer equipped with advanced type-driven mutation operators, carefully crafted to target intricate type-related features such as template generics, type conversions, and inheritance. Beyond differential testing, TyMut introduces enhanced test oracles through a must analysis that partially confirms the validity of generated programs. Specifically, mutation operators are classified into well-formed and not-well-formed: Programs generated by well-formed mutation operators are valid and must be accepted by compilers. Programs generated by not-well-formed operators are validated against a set of well-formedness rules. Any violation indicates the program is invalid and must be rejected. For programs that pass the rules but lack a definitive oracle, TyMut applies differential testing to identify behavioral inconsistencies across compilers. The testing campaign took about 32 hours to generate and test 250584 programs. The must analysis provides definite test oracles for nearly 80% of all generated programs. TyMut uncovered 102 bugs in the recent versions of GCC and Clang, with 56 confirmed as new bugs by compiler developers. Among the confirmed bugs, 26 of them cause compiler crashes, and more than 50% cause miscompilation. Additionally, 7 of them had remained hidden for over 20 years, 22 for over 10 years, and 39 for over 5 years. One long-standing bug discovered by TyMut was later confirmed as the root cause of a real-world issue in TensorFlow. Before submitting this paper, 13 bugs were fixed, most of which were fixed within 60 days. Notably, some unconfirmed bugs have led to in-depth discussions among developers. For instance, one bug led a compiler developer to submit a new issue to the C++ language standard, showing that we uncovered ambiguities in the language specification.

Proceedings of the ACM on Programming LanguagesVol. 9(OOPSLA2)
Tianjin University (CN), Peking University (CN), Beijing Jiaotong University (CN), Beijing Academy of Artificial Intelligence (CN), Singapore Management University (SG)
Openalex Percentile: Top 5%
Software Testing and Debugging Techniques
4.62
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.