PR-Miner: automatically extracting implicit programming rules and detecting violations in large software code

Programs usually follow many implicit programming rules, most of which are too tedious to be documented by programmers. When these rules are violated by programmers who are unaware of or forget about them, defects can be easily introduced. Therefore, it is highly desirable to have tools to automatically extract such rules and also to automatically detect violations. Previous work in this direction focuses on simple function-pair based programming rules and additionally requires programmers to provide rule templates. This paper proposes a general method called PR-Miner that uses a data mining technique called frequent itemset mining to efficiently extract implicit programming rules from large software code written in an industrial programming language such as C, requiring little effort from programmers and no prior knowledge of the software. Benefiting from frequent itemset mining, PR-Miner can extract programming rules in general forms (without being constrained by any fixed rule t...

• Type: Conference
• Year: 2005
• Where: SIGSOFT
• Authors: Zhenmin Li, Yuanyuan Zhou
• Keywords: Frequent Itemset Mining, Implicit Programming Rules, Programming Rules, SIGSOFT 2005, Software Engineering