most citedPyTester: Deep Reinforcement Learning for Text-to-Testcase Generation

10 citations · 15 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SE2024★ 1 cited

A Survey on Web Application Testing: Over a Decade of Evolution

Tao Li, Chenhui Cui, Zhengdong Huang +5

As one of the most popular software applications, a web application is a program accessible through the web that dynamically generates content based on user interactions or context…

cs.AI2024

Rewarding What Matters: Step-by-Step Reinforcement Learning for Task-Oriented Dialogue

Huifang Du, Shuqin Li, Minghao Wu +3

Reinforcement learning (RL) is a powerful approach to enhance task-oriented dialogue (TOD) systems. However, existing RL methods tend to mainly focus on generation tasks, such as d…

cs.HC2024★ 2 cited

Towards Proactive Interactions for In-Vehicle Conversational Assistants Utilizing Large Language Models

Huifang Du, Xuejing Feng, Jun Ma +5

Research demonstrates that the proactivity of in-vehicle conversational assistants (IVCAs) can help to reduce distractions and enhance driving safety, better meeting users' cogniti…

cs.SE2024★ 10 cited

PyTester: Deep Reinforcement Learning for Text-to-Testcase Generation

Wannita Takerngsaksiri, Rujikorn Charakorn, Chakkrit Tantithamthavorn +1

Test-driven development (TDD) is a widely-employed software development practice that mandates writing test cases based on requirements before writing the actual code. While writin…

cs.SE2022★ 2 cited

Syntax-Aware On-the-Fly Code Completion

Wannita Takerngsaksiri, Chakkrit Tantithamthavorn, Yuan-Fang Li

Code completion aims to help improve developers' productivity by suggesting the next code tokens from a given context. Various approaches have been proposed to incorporate abstract…