CP-Miner: finding copy-paste and related bugs in large-scale software code

Citations Over TimeTop 1% of 2006 papers

Abstract

Recent studies have shown that large software suites contain significant amounts of replicated code. It is assumed that some of this replication is due to copy-and-paste activity and that a significant proportion of bugs in operating systems are due to copy-paste errors. Existing static code analyzers are either not scalable to large software suites or do not perform robustly where replicated code is modified with insertions and deletions. Furthermore, the existing tools do not detect copy-paste related bugs. In this paper, we propose a tool, CP-Miner, that uses data mining techniques to efficiently identify copy-pasted code in large software suites and detects copy-paste bugs. Specifically, it takes less than 20 minutes for CP-Miner to identify 190,000 copy-pasted segments in Linux and 150,000 in FreeBSD. Moreover, CP-Miner has detected many new bugs in popular operating systems, 49 in Linux and 31 in FreeBSD, most of which have since been confirmed by the corresponding developers and have been rectified in the following releases. In addition, we have found some interesting characteristics of copy-paste in operating system code. Specifically, we analyze the distribution of copy-pasted code by size (number lines of code), granularity (basic blocks and functions), and modification within copy-pasted code. We also analyze copy-paste across different modules and various software versions.

Related Papers

• → Is GitHub copilot a substitute for human pair-programming?(2022)95 cited
• → How bugs are born: a model to identify how bugs are introduced in software components(2020)73 cited
• → Is GitHub Copilot a Substitute for Human Pair-programming? An Empirical Study(2022)25 cited
• ENHANCING SCALABILITY AND EFFICIENCY OF THE TOUGH2_MP FOR LINUX CLUSTERS(2006)
• Scalability of the parallelization of GCM T-80 code(1997)