89 citations · 99 across the 8 of their papers we have counts for
8 papers
ClozeMaster: Fuzzing Rust Compiler by Harnessing LLMs for Infilling Masked Real Programs
Hongyan Gao, Yibiao Yang, Maolin Sun +3
Ensuring the reliability of the Rust compiler is of paramount importance, given increasing adoption of Rust for critical systems development, due to its emphasis on memory and thre…
DebugHarness: Emulating Human Dynamic Debugging for Autonomous Program Repair
Maolin Sun, Yibiao Yang, Xuanlin Liu +2
Patching severe security flaws in complex software remains a major challenge. While automated tools like fuzzers efficiently discover bugs, fixing deep-rooted low-level faults (e.g…
Isolating Compiler Faults via Multiple Pairs of Adversarial Compilation Configurations
Qingyang Li, Yibiao Yang, Maolin Sun +3
Compilers are fundamental to modern software development, making the effective identification and resolution of compiler faults essential. However, localizing these faults to speci…
Using a Sledgehammer to Crack a Nut? Revisiting Automated Compiler Fault Isolation
Yibiao Yang, Qingyang Li, Maolin Sun +2
Background: Compilers are fundamental to software development, translating high-level source code into executable software systems. Faults in compilers can have severe consequences…
WITNESS: A lightweight and practical approach to fine-grained predictive mutation testing
Zeyu Lu, Peng Zhang, Chun Yong Chong +5
Existing fine-grained predictive mutation testing studies predominantly rely on deep learning, which faces two critical limitations in practice: (1) Exorbitant computational costs.…
Once4All: Skeleton-Guided SMT Solver Fuzzing with LLM-Synthesized Generators
Maolin Sun, Yibiao Yang, Yuming Zhou
Satisfiability Modulo Theory (SMT) solvers are foundational to modern systems and programming languages research, providing the foundation for tasks like symbolic execution and aut…
Deep Learning-based Software Engineering: Progress, Challenges, and Opportunities
Xiangping Chen, Xing Hu, Yuan Huang +23
Researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language p…
Towards Better Code Understanding in Decoder-Only Models with Contrastive Learning
Jiayi Lin, Yanlin Wang, Yibiao Yang +2
Recent advances in large-scale code generation models have led to remarkable progress in producing high-quality code. These models are trained in a self-supervised manner on extens…