Hengcheng Zhu

Orcid: 0000-0002-3082-5957

Affiliations:
  • Hong Kong University of Science and Technology, Hong Kong


According to our database1, Hengcheng Zhu authored at least 16 papers between 2020 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Improving LLM-Driven Test Generation by Learning from Mocking Information.
CoRR, April, 2026

MR-Coupler: Automated Metamorphic Test Generation via Functional Coupling Analysis.
CoRR, April, 2026

2025
LSPFuzz: Hunting Bugs in Language Servers (Experimental Data).
Dataset, October, 2025

LSPFuzz: Hunting Bugs in Language Servers (Experimental Data).
Dataset, September, 2025

LSPFuzz: Hunting Bugs in Language Servers (Experimental Data).
Dataset, September, 2025

Experimental Data: Understanding and Characterizing Mock Assertions in Unit Tests.
Dataset, January, 2025

Understanding and Characterizing Mock Assertions in Unit Tests.
Proc. ACM Softw. Eng., 2025

SemBIC: Semantic-Aware Identification of Bug-Inducing Commits.
Proc. ACM Softw. Eng., 2025

LspFuzz: Hunting Bugs in Language Servers.
Proceedings of the 40th IEEE/ACM International Conference on Automated Software Engineering, 2025

2024
MR-Scout: Automated Synthesis of Metamorphic Relations from Existing Test Cases.
ACM Trans. Softw. Eng. Methodol., July, 2024

StubCoder: Automated Generation and Repair of Stub Code for Mock Objects.
ACM Trans. Softw. Eng. Methodol., January, 2024

MR-Adopt: Automatic Deduction of Input Transformation Function for Metamorphic Testing.
Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering, 2024

2021
Why Do Developers Remove Lambda Expressions in Java?
Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021

2020

How Do Python Framework APIs Evolve? An Exploratory Study.
Proceedings of the 27th IEEE International Conference on Software Analysis, 2020

MockSniffer: Characterizing and Recommending Mocking Decisions for Unit Tests.
Proceedings of the 35th IEEE/ACM International Conference on Automated Software Engineering, 2020


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