Neural-Based Test Oracle Generation: A Large-Scale Evaluation and Lessons Learned-Reference-Cited by-同舟云学术

Neural-Based Test Oracle Generation: A Large-Scale Evaluation and Lessons Learned

Published:2023-11-30 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
language:
Short-container-title:

Author:

Hossain Soneya Binta¹,Filieri Antonio²,Dwyer Matthew B.¹,Elbaum Sebastian¹,Visser Willem²

Affiliation:

1. University of Virginia, Charlottesville, USA

2. Amazon Web Services, Santa Clara, United States

Funder

This material is based in part upon work supported by the DARPA ARCOS program under contract FA8750-20-C-0507, by The Air Force Office of Scientific Research under award number FA9550-21-0164, and by Lockheed Martin Advanced Technology Laboratories.

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3611643.3616265

Reference62 articles.

1. A Systematic Review of the Application and Empirical Investigation of Search-Based Test Case Generation

2. An Industrial Evaluation of Unit Test Generation: Finding Real Faults in a Financial Application

3. Is mutation an appropriate tool for testing experiments?

4. The Oracle Problem in Software Testing: A Survey

5. What It Would Take to Use Mutation Testing in Industry—A Study at Facebook

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Automating the correctness assessment of AI-generated code for security contexts;Journal of Systems and Software;2024-10

2. A Deep Dive into Large Language Models for Automated Bug Localization and Repair;Proceedings of the ACM on Software Engineering;2024-07-12

3. Ensuring Critical Properties of Test Oracles for Effective Bug Detection;Proceedings of the 2024 IEEE/ACM 46th International Conference on Software Engineering: Companion Proceedings;2024-04-14