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Effective test generation using pre-trained Large Language Models and mutation testing

  • Published:2024-07 Issue: Volume:171 Page:107468
  • ISSN:0950-5849
  • Container-title:Information and Software Technology
  • language:en
  • Short-container-title:Information and Software Technology

Author:

Dakhel Arghavan MoradiORCID,Nikanjam Amin,Majdinasab VahidORCID,Khomh FoutseORCID,Desmarais Michel C.

Funder

Natural Sciences and Engineering Research Council of Canada

Canada Research Chairs

Fonds de recherche du Québec

Canadian Institute for Advanced Research

Publisher

Elsevier BV

Reference57 articles.

1. The Art of Agile Development;Shore,2021

2. Learning Test-Driven Development;Siddiqui,2021

3. Augmenting automatically generated unit-test suites with regression oracle checking;Xie,2006

4. Test generation for higher-order functions in dynamic languages;Selakovic;Proc. ACM Programm. Lang.,2018

5. E. Arteca, S. Harner, M. Pradel, F. Tip, Nessie: automatically testing JavaScript APIs with asynchronous callbacks, in: Proceedings of the 44th International Conference on Software Engineering, 2022, pp. 1494–1505.

Cited by 5 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. Natural Symbolic Execution-Based Testing for Big Data Analytics;Proceedings of the ACM on Software Engineering;2024-07-12

2. Can Large Language Model Aid in Generating Properties for UPPAAL Timed Automata? A Case Study;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02

3. Are We Testing or Being Tested? Exploring the Practical Applications of Large Language Models in Software Testing;2024 IEEE Conference on Software Testing, Verification and Validation (ICST);2024-05-27

4. Generative AI for Software Development: A Family of Studies on Code Generation;Generative AI for Effective Software Development;2024

5. An Overview on Large Language Models;Generative AI for Effective Software Development;2024
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