activity
20082024
most citedGuiding Language Models of Code with Global Context using Monitors

6 citations · 17 across the 11 of their papers we have counts for

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Showing 2023Show all

5 papers · 1 filter

cs.AI2023★ 3 cited

Frustrated with Code Quality Issues? LLMs can Help!

Nalin Wadhwa, Jui Pradhan, Atharv Sonwane +5

As software projects progress, quality of code assumes paramount importance as it affects reliability, maintainability and security of software. For this reason, static analysis to…

cs.SE2023★ 3 cited

CodePlan: Repository-level Coding using LLMs and Planning

Ramakrishna Bairi, Atharv Sonwane, Aditya Kanade +6

Software engineering activities such as package migration, fixing errors reports from static analysis or testing, and adding type annotations or other specifications to a codebase,…

cs.HC2023

PwR: Exploring the Role of Representations in Conversational Programming

Pradyumna YM, Vinod Ganesan, Dinesh Kumar Arumugam +7

Large Language Models (LLMs) have revolutionized programming and software engineering. AI programming assistants such as GitHub Copilot X enable conversational programming, narrowi…

cs.SE2023

StaticFixer: From Static Analysis to Static Repair

Naman Jain, Shubham Gandhi, Atharv Sonwane +5

Static analysis tools are traditionally used to detect and flag programs that violate properties. We show that static analysis tools can also be used to perturb programs that satis…

cs.CL2023★ 6 cited

Guiding Language Models of Code with Global Context using Monitors

Lakshya A Agrawal, Aditya Kanade, Navin Goyal +2

Language models of code (LMs) work well when the surrounding code provides sufficient context. This is not true when it becomes necessary to use types, functionality or APIs define…