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20142024
most citedEvaluating Pre-trained Language Models for Repairing API Misuses

2 citations · 4 across the 8 of their papers we have counts for

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6 papers · 1 filter

cs.SE2024

On Evaluating the Efficiency of Source Code Generated by LLMs

Changan Niu, Ting Zhang, Chuanyi Li +2

Recent years have seen the remarkable capabilities of large language models (LLMs) for code generation. Different from existing work that evaluate the correctness of the code gener…

cs.SE20232 cited

Evaluating Pre-trained Language Models for Repairing API Misuses

Ting Zhang, Ivana Clairine Irsan, Ferdian Thung +3

API misuses often lead to software bugs, crashes, and vulnerabilities. While several API misuse detectors have been proposed, there are no automatic repair tools specifically desig…

cs.SE2023

APISENS- Sentiment Scoring Tool for APIs with Crowd-Knowledge

Kisub Kim, Ferdian Thung, Ting Zhang +4

Utilizing pre-existing software artifacts, such as libraries and Application Programming Interfaces (APIs), is crucial for software development efficiency. However, the abundance o…

cs.SE2023

APIHarvest: Harvesting API Information from Various Online Sources

Ferdian Thung, Kisub Kim, Ting Zhang +4

Using APIs to develop software applications is the norm. APIs help developers to build applications faster as they do not need to reinvent the wheel. It is therefore important for…

cs.SE20231 cited

PICASO: Enhancing API Recommendations with Relevant Stack Overflow Posts

Ivana Clairine Irsan, Ting Zhang, Ferdian Thung +2

While having options could be liberating, too many options could lead to the sub-optimal solution being chosen. This is not an exception in the software engineering domain. Nowaday…

cs.SE2022

Automatic Pull Request Title Generation

Ting Zhang, Ivana Clairine Irsan, Ferdian Thung +3

Pull Requests (PRs) are a mechanism on modern collaborative coding platforms, such as GitHub. PRs allow developers to tell others that their code changes are available for merging…