test-generation.html 关键词 test generation 的长期追踪 RSS，汇总历史命中文献。 zh-CN Sun, 28 Jun 2026 05:24:06 +0000 ../papers/arxiv-775fc4ccf6e9.html https://arxiv.org/abs/2511.14224#2026-06-05#test-generation Fri, 05 Jun 2026 13:25:00 +0800 Automated unit test generation using large language models (LLMs) holds great promise but often struggles with generating tests that are both correct and maintainable in real-world projects. This paper presents KTester, a novel framework that integrates project-specific knowledge and testing domain knowledge to enhance LLM-based test generation. Our approach first extracts project structure and usage knowledge through static analysis, which provides rich context for the model. It then employs a… ../papers/arxiv-c7c5bfa9c58b.html https://arxiv.org/abs/2606.04310#2026-06-04#test-generation Thu, 04 Jun 2026 14:02:06 +0800 Deep Neural Networks (DNNs) are increasingly being deployed in security-critical and safety-sensitive applications, which makes rigorous testing essential to identify and mitigate model weaknesses. Existing DNN testing approaches explore either the input space or a learned latent space. While latent-space generation can better maintain plausibility than direct input-space mutation, current methods still face a trade-off among exploration controllability, failure diversity, and seed-relative sem… ../papers/arxiv-1863054477e2.html https://arxiv.org/abs/2604.25862v1#2026-04-29#test-generation Wed, 29 Apr 2026 12:26:28 +0800 Existing REST API testing tools are typically evaluated using code coverage and crash-based fault metrics. However, recent LLM-based approaches increasingly generate tests from NL requirements to validate functional behaviour, making traditional metrics weak proxies for whether generated tests validate intended behaviour. To address this gap, we present RESTestBench, a benchmark comprising three REST services paired with manually verified NL requirements in both precise and vague variants, enab…