19 citations · 57 across the 11 of their papers we have counts for
13 papers
Rebuttal to Berger et al., TOPLAS 2019
Baishakhi Ray, Prem Devanbu, Vladimir Filkov
Berger et al., published in TOPLAS 2019, is a critique of our 2014 FSE conference abstract and its archival version, the 2017 CACM paper: A Large-Scale Study of Programming Languag…
Do People Prefer "Natural" code?
Casey Casalnuovo, Kevin Lee, Hulin Wang +2
Natural code is known to be very repetitive (much more so than natural language corpora); furthermore, this repetitiveness persists, even after accounting for the simpler syntax of…
Learning Lenient Parsing & Typing via Indirect Supervision
Toufique Ahmed, Premkumar Devanbu, Vincent Hellendoorn
Both professional coders and teachers frequently deal with imperfect (fragmentary, incomplete, ill-formed) code. Such fragments are common in STACKOVERFLOW; students also frequentl…
Are My Invariants Valid? A Learning Approach
Vincent J. Hellendoorn, Premkumar T. Devanbu, Oleksandr Polozov +1
Ensuring that a program operates correctly is a difficult task in large, complex systems. Enshrining invariants -- desired properties of correct execution -- in code or comments ca…
BugSwarm: Mining and Continuously Growing a Dataset of Reproducible Failures and Fixes
David A. Tomassi, Naji Dmeiri, Yichen Wang +5
Fault-detection, localization, and repair methods are vital to software quality; but it is difficult to evaluate their generality, applicability, and current effectiveness. Large,…
Whom Are You Going to Call?: Determinants of @-Mentions in GitHub Discussions
David Kavaler, Premkumar Devanbu, Vladimir Filkov
Open Source Software (OSS) project success relies on crowd contributions. When an issue arises in pull-request based systems, @-mentions are used to call on people to task; previou…