Jianting Gao

dblp:431/1725 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0004-9613-9572ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software testing · 61% Program analysis · 30% Runtime systems and virtual machines · 9%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program analysis › static analysis
bug detection
1.012026
DrWASI: LLM-assisted Differential Testing for WebAssembly System Interface Implementations · ACM Trans. Softw. Eng. Methodol. 2026
Software testing
differential testing
1.012026
DrWASI: LLM-assisted Differential Testing for WebAssembly System Interface Implementations · ACM Trans. Softw. Eng. Methodol. 2026
Software testing
fuzzing
1.012026
DrWASI: LLM-assisted Differential Testing for WebAssembly System Interface Implementations · ACM Trans. Softw. Eng. Methodol. 2026

Methods — techniques the papers use, named apart from their topics

mutation testing · 1.0large language model · 1.0differential testing · 1.0
YearPublicationVenuePosition
2026 DrWASI: LLM-assisted Differential Testing for WebAssembly System Interface Implementations
abstract
WebAssembly (Wasm) is an emerging binary format that serves as a compilation target for over 40 programming languages. Wasm runtimes provide execution environments that enhance portability by abstracting away operating systems and hardware details. A key component in these runtimes is the WebAssembly System Interface (WASI), which manages interactions with operating systems, like file operations. Considering the critical role of Wasm runtimes, the community has aimed to detect their implementation bugs. However, no work has focused on WASI-specific bugs that can affect the original functionalities of running Wasm binaries and cause unexpected results. To fill the void, we present DrWASI , the first general-purpose differential testing framework for WASI implementations. Our approach uses a large language model to generate seeds and applies variant and environment mutation strategies to expand and enrich the test case corpus. We then perform differential testing across major Wasm runtimes. By leveraging dynamic and static information collected during and after the execution, DrWASI can identify bugs. Our evaluation shows that DrWASI uncovered 33 unique bugs, with all confirmed and 7 fixed by developers. This research represents a pioneering step in exploring a promising yet under-explored area of the Wasm ecosystem, providing valuable insights for stakeholders.
Ningyu He, Jianting Gao, Shangtong Cao, Kaibo Liu, Haoyu Wang 0001, Yun Ma 0002, Gang Huang 0001, Xuanzhe Liu
ACM Trans. Softw. Eng. Methodol.3