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Automating Software Engineering with Machine Learning

Published: 24 February 2022 Publication History

Abstract

Software plays a crucial role in our everyday lives. The scarcity of skilled software engineers has become a bottleneck in delivering better software at scale. Can we automate software engineering to help improve developer productivity and software quality? Can we take advantage of massive codebases to learn about building correct and scalable software?
In this talk, I will present some recent advances in automated software engineering using machine learning. Along the way, I will relate the data-driven techniques to traditional, algorithmic program analysis techniques. I will discuss representative deep learning methods to analyze and synthesize source code. Even though we are witnessing exciting new advances in machine learning for software engineering, we shall reflect on what challenges remain and the way forward.

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      ISEC '22: Proceedings of the 15th Innovations in Software Engineering Conference
      February 2022
      235 pages
      ISBN:9781450396189
      DOI:10.1145/3511430
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 24 February 2022

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      Author Tags

      1. machine learning
      2. program repair
      3. program synthesis
      4. software engineering

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      ISEC 2022

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      Overall Acceptance Rate 76 of 315 submissions, 24%

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