(Compulsory)
(15 marks)
Multi-sessional papers: Candidate will be assigned to appear only in one of the sessions for the papers running in multiple sessions.
Computer Science and Information Technology (CS) and Civil Engineering (CE) will be conducted as multi-session papers in GATE 2025. More precisely, they will be two-session papers. This means that the candidates will be assigned to one of the sessions only — either the forenoon session or the afternoon session. The question papers will be different for each session. Test papers are held in multiple sessions when the candidate count is so high that they cannot all appear for the test in the same session. The scores of the candidates will be normalized according to the normalization formula given in Section 13.2 of the Information Brochure.
Candidates must familiarize themselves with the paper code as it is required both during application and examination.
Each candidate should fill ONLY ONE application. If they wish to appear in second paper (from the two-paper combination), they can add respective paper in their original application. In case of Multiple applications, only one will be accepted and remaining applications will be rejected without any refund for the paid fee.
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Title: where are large language models for code generation on github.
Abstract: The increasing use of Large Language Models (LLMs) in software development has garnered significant attention from researchers assessing the quality of the code they generate. However, much of the research focuses on controlled datasets such as HumanEval, which fail to adequately represent how developers actually utilize LLMs' code generation capabilities or clarify the characteristics of LLM-generated code in real-world development scenarios. To bridge this gap, our study investigates the characteristics of LLM-generated code and its corresponding projects hosted on GitHub. Our findings reveal several key insights: (1) ChatGPT and Copilot are the most frequently utilized for generating code on GitHub. In contrast, there is very little code generated by other LLMs on GitHub. (2) Projects containing ChatGPT/Copilot-generated code are often small and less known, led by individuals or small teams. Despite this, most projects are continuously evolving and improving. (3) ChatGPT/Copilot is mainly utilized for generating Python, Java, and TypeScript scripts for data processing and transformation. C/C++ and JavaScript code generation focuses on algorithm and data structure implementation and user interface code. Most ChatGPT/Copilot-generated code snippets are relatively short and exhibit low complexity. (4) Compared to human-written code, ChatGPT/Copilot-generated code exists in a small proportion of projects and generally undergoes fewer modifications. Additionally, modifications due to bugs are even fewer, ranging from just 3% to 8% across different languages. (5) Most comments on ChatGPT/Copilot-generated code lack detailed information, often only stating the code's origin without mentioning prompts, human modifications, or testing status. Based on these findings, we discuss the implications for researchers and practitioners.
Subjects: | Software Engineering (cs.SE) |
Cite as: | [cs.SE] |
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Engineers are the architects of our modern world. They use science and math to solve problems and create new things.
You might see their work in bridges, buildings, or even the phone in your hand. Engineers make life easier, safer, and more fun.
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