Interpreter-guided differential JIT compiler unit testing
Guillermo Polito, Stéphane Ducasse, Pablo Tesone
Abstract
Modern language implementations using Virtual Machines feature diverse execution engines such as byte-code interpreters and machine-code dynamic translators, a.k.a. JIT compilers. Validating such engines requires not only validating each in isolation, but also that they are functionally equivalent. Tests should be duplicated for each execution engine exercising the same execution paths on each of them.
In this paper we present a novel automated testing approach for virtual machines featuring byte-code interpreters. Our solution uses concolic meta-interpretation: it applies concolic testing to a byte-code interpreter to explore all possible execution interpreter paths and obtain a list of concrete values that explore such paths. We then use such values to apply differential testing on the VM interpreter and JIT compiler. This solution is based on two insights: (1) both the interpreter and compiler implement the same language semantics and (2) interpreters are simple executable specifications of those semantics and thus promising targets to (meta-) interpretation using concolic testing. We validated it on 4 different compilers of the open-source Pharo Virtual Machine and found 468 differences between them, produced by 91 different causes, organized in 6 different categories.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Cited by top-tier papers6
- Validating JIT Compilers via Compilation Space ExplorationCong Li, Yanyan Jiang, Chang Xu, Zhendong SuSOSP 2023 · 22 citations
- Compiler Testing using Template Java ProgramsZhiqiang Zang, Nathan Wiatrek, Milos Gligoric, August ShiASE 2022 · 21 citations
- A Generative and Mutational Approach for Synthesizing Bug-Exposing Test Cases to Guide Compiler FuzzingGuixin Ye, Tianmin Hu, Zhanyong Tang, Zhenye Fan et al.FSE 2023 · 14 citations
- Fuzzing Java Optimizing Compilers with Complex Inter-Class Structures Guided by Heterogeneous Program GraphsShiyu Qiu, Ming Wen, Zifan Xie, Hai JinICSE 2026
- Understanding and Finding JIT Compiler Performance BugsZijian Yi, Cheng Ding, August Shi, Milos GligoricOOPSLA 2026
Builds on3
- Automated conformance testing for JavaScript engines via deep compiler fuzzingGuixin Ye, Zhanyong Tang, Shin Hwei Tan, Songfang Huang et al.PLDI 2021 · 75 citations
- JEST: N+1 -version Differential Testing of Both JavaScript Engines and SpecificationJihyeok Park, Seungmin An, Dongjun Youn, Gyeongwon Kim et al.ICSE 2021 · 24 citations
- JUSTGen: Effective Test Generation for Unspecified JNI Behaviors on JVMsSungjae Hwang, Sungho Lee, Jihoon Kim, Sukyoung RyuICSE 2021 · 12 citations
Related papers
- ZendDiff: Differential Testing of PHP InterpreterYuancheng Jiang, Jianing Wang, Qiange Liu, Yeqi Fu et al.ASE 2025 · 1 citation
- BCFuzz: Bytecode-Driven Fuzzing for JavaScript EnginesJiming Wang, Chenggang Wu, Jikai Ren, Yuhao Hu et al.ASE 2025 · 1 citation
- Holistic Concolic Execution for Dynamic Web Applications via Symbolic Interpreter AnalysisPenghui Li, Wei Meng, Mingxue Zhang, Chenlin Wang et al.S&P 2024 · 6 citations
- FuzzJIT: Oracle-Enhanced Fuzzing for JavaScript Engine JIT CompilerJunjie Wang, Zhiyi Zhang, Shuang Liu, Xiaoning Du et al.USENIX Security 2023
- DUMPLING: Fine-grained Differential JavaScript Engine FuzzingLiam Wachter, Julian Gremminger, Christian Wressnegger, Mathias Payer et al.NDSS 2025
