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관련도 상

Behavior Tree

• Colledanchise & Ögren, "Behavior Trees in Robotics and AI: An Introduction"
• Marzinotto, Colledanchise, Smith, Ögren, "Towards a Unified Behavior Trees Framework for Robot Control"
• Iovino, Scukins, Styrud, Ögren, Smith, "A survey of Behavior Trees in robotics and AI"

LLM-based Testing

• Xia, Paltenghi, Tian, Pradel, Zhang, "Fuzz4All: Universal Fuzzing with Large Language Models"
• Deng, Xia, Peng, Yang, Zhang, "Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models"
• Fan, Gokkaya, Harman, Hellendoorn, Lucchetti, Mockus, Tan, "Large Language Models for Software Engineering: Survey and Open Problems"

관련도 중

평가 기준

• Klees, Ruef, Cooper, Wei, Hicks, "Evaluating Fuzz Testing"
• Arcuri & Briand, "A Hitchhiker's guide to statistical tests for assessing randomized algorithms in software engineering"
• Böhme, Szekeres, Metzman, "On the Reliability of Coverage-Based Fuzzer Benchmarking"

Metamorphic Testing

• Chen, Cheung, Yiu, "Metamorphic testing: a new approach for generating next test cases"
• Segura, Fraser, Sanchez, Ruiz-Cortés, "A Survey on Metamorphic Testing"
• Chen, Kuo, Liu, Poon, Towey, Tse, Zhou, "Metamorphic Testing: A Review of Challenges and Opportunities"

DifferentialTesting

• Yang, Chen, Eide, Regehr, "Finding and Understanding Bugs in C Compilers"
• McKeeman, "Differential Testing for Software"

Mutation Testing

• Jia & Harman, "An Analysis and Survey of the Development of Mutation Testing"
• [Papadakis, Kintis, Zhang, Jia, Le Traon, Harman, "Mutation Testing Advances: An Analysis and Survey"](Papadakis, Kintis, Zhang, Jia, Le Traon, Harman, "Mutation Testing Advances: An Analysis and Survey")

Embedded / Model-based Testing

• Utting, Pretschner, Legeard, "A taxonomy of model-based testing approaches"
• Bringmann & Krämer, "Model-based testing of automotive systems"

Search-Based Software Testing

• McMinn, "Search-based software testing: Past, present and future"
• Fraser & Arcuri, "EvoSuite: Automatic Test Suite Generation for Object-Oriented Software"

Scenario-based Testing

• Riedmaier, Ponn, Ludwig, Schick, Diermeyer, "Survey on Scenario-Based Safety Assessment of Automated Vehicles"

Prompting

• Schick et al., "Toolformer: Language Models Can Teach Themselves to Use Tools"
• Madaan et al., "Self-Refine: Iterative Refinement with Self-Feedback"
• Wei et al., "Chain-of-Thought Prompting Elicits Reasoning in Large Language Models"
• Yao et al., "ReAct: Synergizing Reasoning and Acting in Language Models"