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Faculty of Graduate Studies

Rohith Pudari

  • BTech (Jawaharlal Nehru Technological University Hyderabad, 2019)

Notice of the Final Oral Examination for the Degree of Master of Science

Topic

AI Supported Software Development: Moving Beyond Code Completion

Computer Science

Date & location

  • Tuesday, August 23, 2022

  • 10:00 A.M.

  • Virtual Defence

Reviewers

Supervisory Committee

  • Dr. Neil Ernst, Department of Computer Science, University of Victoria (Supervisor)

  • Dr. Jens Weber, Department of Computer Science, UVic (Member)

External Examiner

  • Dr. Issa Traoré, Department of Electrical and Computer Engineering, UVic 

Chair of Oral Examination

  • Dr. Chris Nelson, Department of Biochemistry and Microbiology, UVic

Abstract

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.

In this study, we explore the current limitations of AI-supported code completion tools like Copilot and offer a simple taxonomy for understanding the classification of AI-supported code completion tools in this space. We first perform an exploratory study on Copilot’s code suggestions for language idioms and code smells. Copilot does not follow language idioms and avoid code smells in most of our test scenarios. We then conduct additional investigation to determine the current boundaries of AI-supported code completion tools like Copilot by introducing a taxonomy of software abstraction hierarchies where ‘basic programming functionality’ such as code compilation and syntax checking is at the least abstract level, software architecture analysis and design are at the most abstract level. We conclude by providing a discussion on challenges for future development of AI-supported code completion tools to reach the design level of abstraction in our taxonomy.

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