4 papers
On the Reliability of Code Comprehension Proxies
Erfan Arvan, Nadeeshan De Silva, Oscar Chaparro +1
Prior work on code comprehension uses different comprehension proxies-for example, Likert-scale ratings or answers to input-output questions about program snippets, usually collect…
Verifier Warnings Do Not Improve Comprehensibility Prediction
Nadeeshan De Silva, Martin Kellogg, Oscar Chaparro
Proponents of software verification suggest that code simplicity is linked to the effort to verify code, hypothesizing that formal verifiers produce fewer false positive warnings a…
From Absolute to Relative Code Comprehensibility Prediction
Nadeeshan De Silva, Martin Kellogg, Oscar Chaparro
Automatically predicting code comprehensibility could support tasks such as refactoring and code review. Existing metrics correlate poorly with human comprehension, motivating ML m…
Inferring Pluggable Types with Machine Learning
Kazi Amanul Islam Siddiqui, Martin Kellogg
Pluggable type systems allow programmers to extend the type system of a programming language to enforce semantic properties defined by the programmer. Pluggable type systems are di…