SeGa detects 29 of 60 real business-logic bugs by generating tests from requirement-document scenarios, 22-25 more than four LLM-based baselines.
Chatunitest: a chatgpt- based automated unit test generation tool
5 Pith papers cite this work, alongside 22 external citations. Polarity classification is still indexing.
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A fully static, LLM-driven pipeline estimates the execution trace from a single failure log, prunes the test code, and ranks faulty locations at function, block, and line levels, tested on 785 industrial Python test cases.
Frontier LLMs achieve only moderate performance on multi-file unit test generation, with basic executability and cascade errors common, but manual and self-error-fixing mechanisms yield measurable gains.
Proposes a context-aware generative AI framework using a continuously updated knowledge graph and delta engine for adaptive telecom test script generation.
citing papers explorer
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Uncovering Business Logic Bugs via Semantics-Driven Unit Test Generation
SeGa detects 29 of 60 real business-logic bugs by generating tests from requirement-document scenarios, 22-25 more than four LLM-based baselines.
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Efficient Black-Box Fault Localization for System-Level Test Code Using Large Language Models
A fully static, LLM-driven pipeline estimates the execution trace from a single failure log, prunes the test code, and ranks faulty locations at function, block, and line levels, tested on 785 industrial Python test cases.
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MultiFileTest: A Multi-File-Level LLM Unit Test Generation Benchmark and Impact of Error Fixing Mechanisms
Frontier LLMs achieve only moderate performance on multi-file unit test generation, with basic executability and cascade errors common, but manual and self-error-fixing mechanisms yield measurable gains.
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Context-Aware Generative AI for Automated Telecom Test Script Generation
Proposes a context-aware generative AI framework using a continuously updated knowledge graph and delta engine for adaptive telecom test script generation.
- Sakura: An Approach for Generating Complex Tests from Natural Language Test Descriptions