Invited Talk
in
Workshop: Practical Adoption Challenges of ML for Systems in Industry (PACMI)

The Past and Future of Machine Programming in Academia and Industry (A Retrospective and Forecast)

Justin Gottschlich

2022 Invited Talk
in
Workshop: Practical Adoption Challenges of ML for Systems in Industry (PACMI)

Abstract

Machine programming (MP) is principally concerned with the automation of software development. Different than program synthesis, MP targets all aspects of software development such as automating debugging, testing, and profiling code, amongst other things. In this talk, we discuss the foundations of MP and consider its impact across three views: (i) academia, (ii) established corporations, and (iii) startup ventures.

We begin with the “The Three Pillars of Machine Programming” and the formation of the ACM SIGPLAN Machine Programming Symposium (MAPS) both in 2017. We then discuss critical developments that occurred in MP over the last five years leading us to today, including some potential missteps. We then forecast the future of MP over the next five years, including discussing some obvious upcoming developments (e.g., AI-coding partners) and some less obvious ones (e.g., semantic reasoners, transpilation, intentional programming languages, etc.).

Speaker

Justin Gottschlich

Justin Gottschlich is the Founder, CEO & Chief Scientist of Merly, Inc. (http://merly.ai), a company aimed at making software developers more productive using state-of-the-art machine programming systems. Justin is also a Lecturer at Stanford where he teaches machine programming. Before founding Merly, Justin was a Principal AI Scientist and the Founder & Director of Machine Programming Research at Intel Labs. In 2017, he co-founded the ACM SIGPLAN Machine Programming Symposium (MAPS) and now serves as its Steering Committee Chair. Justin received his PhD in Computer Engineering from the University of Colorado-Boulder in 2011 and has 40+ peer-reviewed publications, 60+ issued patents, with 120+ patents pending. Justin’s research has been highlighted in venues like The New York Times, Communications of the ACM, MIT Technology Review, and The Wall Street Journal.

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