Oct 11, 2023 · In this work, we revisit existing oracle generation studies plus ChatGPT to empirically investigate the current standing of their performance in both NLG-based ...
We train and run four state-of-the-art test oracle generation models on seven textual similarity and two test adequacy metrics for our analysis.
Sep 17, 2024 · Neural Oracle Generation (NOG) models are commonly evaluated using static (automatic) metrics which are mainly based on textual similarity of ...
Oct 11, 2023 · Overall, this work complements prior studies on test oracle generation with an extensive performance evaluation with both NLG and test adequacy ...
Jul 28, 2024 · In this work, we revisit existing oracle generation studies plus gpt-3.5 to empirically investigate the current standing of their performance in ...
The nlg_based folder contains the script to evaluate the generated oracles for the studied NTOGs with the NLG-based evaluation metrics. The script contains two ...
Jul 13, 2023 · Assessing Evaluation Metrics for Neural Test Oracle Generation. Recently, deep learning models have shown promising results in test oracle ...
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Lesson – 2: Precision should be a central evaluation metric for a realistic assessment. Finding - 3: SOTA learning-based method has limited unique bug ...
Metrics · Export ... In this paper, we first investigate the impacts of these settings on evaluating and understanding the performance of NTOG approaches.
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A known problem of traditional coverage metrics is that they do not assess oracle quality—that is, whether the computation result is actually checked ...