ADI equips AI debugging agents with function-level interaction via a new execution trace structure, raising SWE-bench Verified resolution to 63.8% at $1.28 per task and delivering 6-18% gains when added to existing agents.
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Coding agents reached 22-29% adoption in GitHub projects within months of release, with agent-assisted commits larger and focused on features and bug fixes.
ZORO integrates rules directly into AI coding workflows by enriching plans, enforcing compliance with proof requirements, and evolving rules via user feedback, resulting in better rule adherence and shifts in user behavior.
CDDRefactorER constrains AI-driven refactoring using Cognitive-Driven Development rules to cut failures by 54-71% and raise novice comprehension scores by 22-31%.
AI IDEs with structured guidance can produce functional large-scale code but frequently introduce design flaws such as duplication, complexity, and principle violations that risk long-term maintainability.
Organizational policies constrain agency in AI-mediated software engineering more than individual preferences, with seniors using detailed delegation and pre-AI instincts while juniors oscillate between over-reliance and avoidance.
citing papers explorer
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Empowering Autonomous Debugging Agents with Efficient Dynamic Analysis
ADI equips AI debugging agents with function-level interaction via a new execution trace structure, raising SWE-bench Verified resolution to 63.8% at $1.28 per task and delivering 6-18% gains when added to existing agents.
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Agentic Much? Adoption of Coding Agents on GitHub
Coding agents reached 22-29% adoption in GitHub projects within months of release, with agent-assisted commits larger and focused on features and bug fixes.
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ZORO: Active Rules for Reliable Vibe Coding
ZORO integrates rules directly into AI coding workflows by enriching plans, enforcing compliance with proof requirements, and evolving rules via user feedback, resulting in better rule adherence and shifts in user behavior.
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Improving Code Comprehension through Cognitive-Load Aware Automated Refactoring for Novice Programmers
CDDRefactorER constrains AI-driven refactoring using Cognitive-Driven Development rules to cut failures by 54-71% and raise novice comprehension scores by 22-31%.
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Beyond Functional Correctness: Design Issues in AI IDE-Generated Large-Scale Projects
AI IDEs with structured guidance can produce functional large-scale code but frequently introduce design flaws such as duplication, complexity, and principle violations that risk long-term maintainability.
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From Junior to Senior: Allocating Agency and Navigating Professional Growth in Agentic AI-Mediated Software Engineering
Organizational policies constrain agency in AI-mediated software engineering more than individual preferences, with seniors using detailed delegation and pre-AI instincts while juniors oscillate between over-reliance and avoidance.