Communications of the ACM
Coding for Two Audiences: Humans and Computers
Researchers say their algorithm will be able to identify spelling and grammatical errors in code.
Software code is written to be read by both computers and humans. With a new $1.2-million three-year project funded by the U.S. National Science Foundation, a group of software engineers and social scientists at UC Davis will leverage this bimodality to develop tools that make writing, reading, and maintaining code easier, improving software tools and the programming experience in the process.
The project is led by computer science distinguished professor Prem Devanbu, and includes Cindy Rubio González, Aditya Thakur, Gerardo Con Díaz, and Emily Morgan.
Making code easy for people to read is a critical part of programming. Humans write, edit, check and maintain code, and the best way to catch potentially catastrophic errors is code review, a proofreading-like process where a second person reads through code and explains what it's doing. The team plans to train an algorithm that can re-write code so it's easier to read without changing the computational meaning.
Their goal is to train an algorithm that can read through code to give it a score for readability. The program can then re-write the code until the readability score improves as much as possible. Improving readability will help coders and code reviewers parse through software and easily find and fix potential errors.
From University of California, Davis
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