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This paper introduces an innovative system for generating and validating critical quality assurance artifacts. Leveraging an AI-driven multi-agent system, software testing agents dynamically interact with and learn from their environment. This continuous feedback mechanism guides the agents’ strategic planning, enabling the synthesis of highly effective tests. The approach significantly improves the efficacy of quality assurance artifact generation, demonstrating advanced agent-bot support for robust software quality through adaptive, intelligence-driven testing.

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Intelligent Agent-Driven Test Artifact Synthesis with Dynamic Environmental Feedback

  • 会议论文

  • 发表日期：

    2026年

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  • Shahzaib Khan

摘要

This paper introduces an innovative system for generating and validating critical quality assurance artifacts. Leveraging an AI-driven multi-agent system, software testing agents dynamically interact with and learn from their environment. This continuous feedback mechanism guides the agents’ strategic planning, enabling the synthesis of highly effective tests. The approach significantly improves the efficacy of quality assurance artifact generation, demonstrating advanced agent-bot support for robust software quality through adaptive, intelligence-driven testing.