About Me

I am a PhD student at UC Berkeley in the Programming Systems group and the Sky Lab advised by Koushik Sen. I broadly research techniques and design systems for expressive and reliable programming.

Research Interest

I am interested in Programming Languages and Software Engineering, specifically, in developer tools for expressive and reliable programming in the age of Language Models (LM). Currently, my work draws inspiration from the deep & old connections between programs and graphs. Graph abstractions unlock program synthesis guided by structure. Similarly, abstracting computational graphs with LMs as programs enables expressive programming and debugging with LMs. My work is motivated by these insights.

Previously, I worked at Microsoft Research (MSR) in the Programming Languages and Systems Group on developer and debugging tools for system reliability.

If you’d like to collaborate, drop me an email at: manishs@berkeley.edu

News

Jan 2024. Interning (returning) with the Systems Innovation group at Microsoft Research in Summer'24! Exploring next-generation AI Assisted System Reliability.
Sept 2023. Passed the Programming Languages Preliminary Exam at UC Berkeley!
May 2023. Taught my first class: CS164: Compilers and Programming Languages at UC Berkeley!
Nov 2022. Our empirical study @ Microsoft Research on production incidents in large-scale cloud services received the Best Paper Award 🏆 at SoCC 2022.
Aug 2022. Started my Ph.D. at UC Berkeley advised by Prof. Koushik Sen. Joining the Sky Lab and the Programming Systems group!

Publications

R2E: Turning any GitHub Repository into a Programming Agent Test Environment
Manish Shetty*, Naman Jain*, Tianjun Zhang, King Han, Koushik Sen, Ion Stoica
Preprint, 2023.

DSPy Assertions: Computational Constraints for Self-Refining LM Pipelines
Arnav Singhvi*, Manish Shetty*, Shangyin Tan*, Chris Potts, Koushik Sen, Matei Zaharia, Omar Khattab
Preprint, 2023.

preprint / code / blog

CodeScholar: Growing Idiomatic Code Examples
Manish Shetty, Koushik Sen, Ion Stoica
Preprint, 2023

preprint / code

How to Fight Production Incidents? An Empirical Study on a Large-scale Cloud Service
Supriyo Ghosh, Manish Shetty, Chetan Bansal, Suman Nath
SoCC 2022: Proceedings of the 13th Symposium on Cloud Computing

paper / Best Paper Award 🏆

AutoTSG: Learning and Synthesis for Incident Troubleshooting
Manish Shetty, Chetan Bansal, Sai Upadhyayula, Arjun Radhakrishna, Anurag Gupta
FSE 2022: Proceedings of the 30th ACM Symposium on the Foundations of Software Engineering

paper

DeepAnalyze: Learning to Localize Crashes at Scale
Manish Shetty, Chetan Bansal, Suman Nath, Sean Bowles, Henry Wang, Ozgur Arman, Siamak Ahari
ICSE 2022: Proceedings of the 44th International Conference on Software Engineering

paper / slides / talk-1 / talk-2 / talk-3

Neural Knowledge Extraction From Cloud Service Incidents
Manish Shetty, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan, Thomas Zimmermann
ICSE 2021: Proceedings of the 43rd International Conference on Software Engineering

paper / slides / talk / featured on VentureBeat

Teaching

UC Berkeley:

Service