Automated Root-Cause Subclassification and No-Code Fix Generation for Invalid Bug Reports

📰 ArXiv cs.AI

Automate root-cause analysis and no-code fix generation for invalid bug reports to reduce customer support waste

advanced Published 19 May 2026

Action Steps

Collect and preprocess invalid bug report data using natural language processing techniques
Apply machine learning algorithms to classify root causes of invalid bug reports
Develop a no-code fix generation system using the classified root causes
Integrate the automated system with customer support workflows to reduce manual effort
Evaluate and refine the system using feedback from customer support agents

Who Needs to Know This

Customer support and software development teams can benefit from this automation to reduce manual effort and improve resolution efficiency

Key Insight

💡 Automating root-cause analysis and no-code fix generation can significantly reduce customer support waste and improve resolution efficiency

Full Article

Title: Automated Root-Cause Subclassification and No-Code Fix Generation for Invalid Bug Reports

Abstract:
arXiv:2605.17561v1 Announce Type: cross Abstract: Issues faced when using software are reported in the form of bug reports. However, many bug reports are invalid, meaning they do not require code changes, and are resolved with a no-code fix. Manually determining the root cause of the invalid bug reports and providing actionable resolutions by the customer support causes a serious waste of resources. Our goal is to introduce a standardized taxonomy for root-cause oriented invalid bug report subcl

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Automated Root-Cause Subclassification and No-Code Fix Generation for Invalid Bug Reports

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