Automatic Programming: How Far Can Machines Go • Hila Peleg • YOW! 2018
This presentation was recorded at YOW! 2018. #GOTOcon #YOW
Hila Peleg - Doctoral Researcher in the Department of Computer Science at the Technion
ABSTRACT
Program synthesis is the wild west beyond code generators and onward toward self-programming systems. What can it do for us? The answer, right now, is not a lot. It can harness the wisdom of the crowd to help reproduce scenarios that are repeated often, and in narrow scopes tools can make educated guesses about what the programmer intended, but full automatic program synthesis is likely impossible. Specifically because of this, it becomes most interesting to explore what it can’t and won’t be able to do on its own. Self-programming systems might be past the horizon, but getting a human more involved makes a big difference, and while the computer might never program for us, it might make for a decent pair-programming partner. We’ll look at glimpses of this future, in academia and outside it, and see why they’re more IDE plugins and less the robot apocalypse.
Hila Peleg is a doctoral researcher in the Department of Computer Science at the Technion. Hila’s research entails designing synthesis tools to help programmers navigate new programming languages and unfamiliar APIs. Prior to her graduate degree, Hila spent over a decade as a developer on enterprise server projects, and she also holds a degree in literature. [...]
TIMECODES
00:00 Intro
03:48 Program synthesis to the rescue
04:47 What if we have automatic programming?
13:29 Query knowledge about some kind of code
15:33 Commit Strip said it best...
17:26 Adjusting our expectations
20:05 What does this all mean?
20:35 Realistic expectations for realistic synthesis
22:37 The synthesis engine
29:22 Trying a different strategy altogether
31:53 The Interaction Model
33:39 Specifying (and re-specifying) intent Task: find the median of a list
35:08 Programming Not only by Example
38:31 When models “out-think“ the programmer
40:19 Keep understanding what’s going on
44:35 Read-Eval-Synth Loops
RECOMMENDED BOOKS
Christiansen, Foy, Wall & Orwant • Programming Perl •
Gamma, Helm, Johnson & Booch • Design Patterns (Gang of Four) •
Lee, Wickens, Liu & Boyle • Designing for People •
Phil Winder • Reinforcement Learning •
Holden Karau, Trevor Grant, Boris Lublinsky, Richard Liu & Ilan Filonenko • Kubeflow for Machine Learning •
Kelleher & Tierney • Data Science (The MIT Press Essential Knowledge series) •
Lakshmanan, Robinson & Munn • Machine Learning Design Patterns •
#AutomaticProgramming #NoCode #LowCode #AI #ML #HilaPeleg #Programming #Synthesis #AITutorial #MLTutorial #AIModels #YOWcon
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