Abstract:
An important goal for programmers is to minimize cost of identifying and correcting defects in source code. Code review
is commonly used for identifying programming defects. However, manual code review has some shortcomings: a) it is time
consuming, b) outcomes are subjective and depend on the skills of reviewers. An automated approach for assisting in code
reviews is thus highly desirable.
We present a tool for assisting in code review and results from our experiments evaluating the tool in different scenarios. The
tool leveraged content available from professional programmer support forums (e.g. StackOverflow.com) to determine potential
defectiveness of a given piece of source code. The defectiveness is expressed on the scale of {Likely defective, Neutral,
Unlikely to be defective}.
Basic idea employed in the tool is to: a) Identify a set P of discussion posts on StackOverflow such that each p ∈ P contains
source code fragment(s) which sufficiently resemble the input code C being reviewed. b) Determine the likelihood of C being
defective by considering all p ∈ P. A novel aspect of our approach is to use document fingerprinting for comparing two pieces
of source code. Our choice of document fingerprinting technique is inspired by source code plagiarism detection tools where
it has proven to be very successful. In the experiments that we performed to verify effectiveness of our approach source code
samples from more than 300 GitHub open source repositories were taken as input. A precision of more than 90% in identifying
correct/relevant results has been achieved.
