6 citations · 11 across the 6 of their papers we have counts for
6 papers
Automated Type Annotation in Python Using Large Language Models
Varun Bharti, Shashwat Jha, Dhruv Kumar +1
Type annotations in Python enhance maintainability and error detection. However, generating these annotations manually is error prone and requires extra effort. Traditional automat…
Loop Invariant Generation: A Hybrid Framework of Reasoning optimised LLMs and SMT Solvers
Varun Bharti, Shashwat Jha, Dhruv Kumar +1
Loop invariants are essential for proving the correctness of programs with loops. Developing loop invariants is challenging, and fully automatic synthesis cannot be guaranteed for…
System Test Case Design from Requirements Specifications: Insights and Challenges of Using ChatGPT
Shreya Bhatia, Tarushi Gandhi, Dhruv Kumar +1
System testing is essential in any software development project to ensure that the final products meet the requirements. Creating comprehensive test cases for system testing from r…
Can ChatGPT Play the Role of a Teaching Assistant in an Introductory Programming Course?
Anishka, Atharva Mehta, Nipun Gupta +3
The emergence of Large language models (LLMs) is expected to have a major impact on education. This paper explores the potential of using ChatGPT, an LLM, as a virtual Teaching Ass…
Unit Test Generation using Generative AI : A Comparative Performance Analysis of Autogeneration Tools
Shreya Bhatia, Tarushi Gandhi, Dhruv Kumar +1
Generating unit tests is a crucial task in software development, demanding substantial time and effort from programmers. The advent of Large Language Models (LLMs) introduces a nov…
A Comparative Analysis of Large Language Models for Code Documentation Generation
Shubhang Shekhar Dvivedi, Vyshnav Vijay, Sai Leela Rahul Pujari +2
This paper presents a comprehensive comparative analysis of Large Language Models (LLMs) for generation of code documentation. Code documentation is an essential part of the softwa…