5 citations · 5 across the 8 of their papers we have counts for
8 papers
Spec-Driven Development as Prescribed and as Practiced
Shyam Agarwal, Anmol Singhal, Andrew Macvean +2
AI coding agents implement software from naturallanguage instructions, but the intent behind that work is lost when stated only in chat sessions. Spec-driven development (SDD) addr…
A Few Pages of Markdown: Committed AI Configuration and Lower Quality Cost after Coding-Agent Adoption
Yegor Denisov-Blanch, Shyam Agarwal, Pavel Azaletskiy +5
Coding agents increase development velocity but also technical debt. Prior work reports only average effects across adopters, hiding wide differences between teams. We introduce RA…
3100 Opinions on Code Review in an AI World: Building Causal Theory from Practitioner Discourse
Shyam Agarwal, Courtney Miller, Christian Kästner +1
Coding agents now author entire pull requests, and practitioners sharply disagree about what this does to code review: whether it becomes the bottleneck, whether human review is st…
AI Writes Faster Than Humans Can Review: A Longitudinal Study of an Enterprise 2x Mandate
Hao He, Shyam Agarwal, Yegor Denisov-Blanch +3
Enterprises increasingly mandate the use of AI coding tools and announce ambitious productivity targets, yet there is little longitudinal evidence on whether such productivity targ…
Practice Less, Explain More: LLM-Supported Self-Explanation Improves Explanation Quality on Transfer Problems in Calculus
Eason Chen, Xinyi Tang, Yvonne Zhao +10
We conducted a between-subjects experiment (N=92) comparing three conditions in a calculus learning environment: no self-explanation (control), menu-based self-explanation, and ope…
Comparing Developer and LLM Biases in Code Evaluation
Aditya Mittal, Ryan Shar, Zichu Wu +6
As LLMs are increasingly used as judges in code applications, they should be evaluated in realistic interactive settings that capture partial context and ambiguous intent. We prese…
AI IDEs or Autonomous Agents? Measuring the Impact of Coding Agents on Software Development
Shyam Agarwal, Hao He, Bogdan Vasilescu
Large language model (LLM) based coding agents increasingly act as autonomous contributors that generate and merge pull requests, yet their real-world effects on software projects…
Speed at the Cost of Quality: How Cursor AI Increases Short-Term Velocity and Long-Term Complexity in Open-Source Projects
Hao He, Courtney Miller, Shyam Agarwal +2
Large language models (LLMs) have demonstrated the promise to revolutionize the field of software engineering. Among other things, LLM agents are rapidly gaining momentum in softwa…