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publications
AI Supported Software Development: Moving Beyond Code Completion
Published in University of Victoria, 2022
AI-supported programming has arrived, as shown by the introduction and successes of large language models for code, such as Copilot/Codex (Github/OpenAI) and AlphaCode (DeepMind). Above-average human performance on programming challenges is now possible. However, software development is much more than solving programming contests. Moving beyond code completion to AI-supported software development will require an AI system that can, among other things, understand how to avoid code smells, follow language idioms, and eventually (maybe!) propose rational software designs. Read more
Recommended citation: Rohith Pudari. "AI Supported Software Development: Moving Beyond Code Completion," Msc Thesis, Department of Computer Science, University of Victoria., Victoria, BC, 2022. [Online]. Available: http://hdl.handle.net/1828/14155 http://hdl.handle.net/1828/14155
Aligning Documentation and Q&A Forum through Constrained Decoding with Weak Supervision
Published in The International Conference on Software Maintenance and Evolution (ICSME) 2023 (NIER track), 2023
Stack Overflow (SO) is a widely used question-and- answer (Q&A) forum dedicated to software development. It plays a supplementary role to official documentation (DOC for short) by offering practical examples and resolving uncertainties. However, the process of simultaneously consulting both the documentation and SO posts can be challenging and time-consuming due to their disconnected nature. In this study, we propose DOSA, a novel approach to automatically align SO and DOC, which inject domain-specific knowledge about the DOC structure into large language models (LLMs) through weak supervision and constrained decoding, thereby enhancing knowledge retrieval and streamlining task completion during the software development procedure. Our preliminary experiments find that DOSA outperforms various widely-used baselines, showing the promise of using generative retrieval models to perform low-resource software engineering tasks. Read more
talks
Talk 1 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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