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Known as Bayou, the Rice application was created through an initiative funded by the Defense Advanced Research Projects Agency aimed at extracting knowledge from online source code repositories like GitHub. A paper on Bayou will be presented May 1 in Vancouver, British Columbia, at the Sixth International Conference on Learning Representations, a premier outlet for deep learning research. Users can try it out at askbayou.com.
Designing applications that can program computers is a long-sought grail of the branch of computer science called artificial intelligence (AI).
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"People have tried for 60 years to build systems that can write code, but the problem is that these methods aren't that good with ambiguity," said Bayou co-creator Swarat Chaudhuri, associate professor of computer science at Rice. "You usually need to give a lot of details about what the target program does, and writing down these details can be as much work as just writing the code.
"Bayou is a considerable improvement," he said. "A developer can give Bayou a very small amount of information -- just a few keywords or prompts, really -- and Bayou will try to read the programmer's mind and predict the program they want."
Chaudhuri - Bayou - Millions - Lines - Java
Chaudhuri said Bayou trained itself by studying millions of lines of human-written Java code. "It's basically studied everything on GitHub, and it draws on that to write its own code."
Bayou co-creator Chris Jermaine, a professor of computer science who co-directs Rice's Intelligent Software Systems Laboratory with Chaudhuri, said Bayou is particularly useful for synthesizing examples of code for specific software APIs.
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"Programming today is very different than it was 30 or 40 years ago," Jermaine said. "Computers today are in our pockets, on our wrists and in billions of home appliances, vehicles and other devices. The days when a programmer could write code from scratch are long gone."
Bayou architect Vijay Murali,...
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