On the Effectiveness of LLMs for Manual Test Verifications

Hunting for smells in natural language tests

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Earlier work this paper cites.

Attention is all you need

Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017

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Sentence-bert: Sentence embeddings using siamese bert-networks

Original

Nils Reimers and Iryna Gurevych. 2019 · 2019

Earlier work this paper cites.

Nalabs: Detecting bad smells in natural language requirements and test specifications

Kostadin Rajkovic and Eduard Paul Enoiu. 2022 · 2022

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Manual tests do smell! cataloging and identifying natural language test smells

Elvys Soares, Manoel Aranda, Naelson Oliveira, Márcio Ribeiro, Rohit Gheyi, Emerson Souza, Ivan Machado, André Santos, Baldoino Fonseca, and Rodrigo Bonifácio. 2023 · 2023

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No more manual tests? evaluating and improving chatgpt for unit test generation

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Zhiqiang Yuan, Yiling Lou, Mingwei Liu, Shiji Ding, Kaixin Wang, Yixuan Chen, and Xin Peng. 2023 · 2023

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A catalog of transformations to remove smells from natural language tests

Original

Manoel Aranda, Naelson Oliveira, Elvys Soares, Márcio Ribeiro, Davi Romão, Ullyanne Patriota, Rohit Gheyi, Emerson Souza, and Ivan Machado. 2024 · 2024

Cited alongside, same era.

Using large language models to generate junit tests: An empirical study

Mohammed Latif Siddiq, Joanna CS Santos, Ridwanul Hasan Tanvir, Noshin Ulfat, Fahmid Al Rifat, and Vinícius Carvalho Lopes. 2024 · 2024

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Ubuntu manual tests

Ubuntu. 2024 · 2024

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Software testing with large language models: Survey, landscape, and vision

Junjie Wang, Yuchao Huang, Chunyang Chen, Zhe Liu, Song Wang, and Qing Wang. 2024 · 2024

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