Using Data Mining for Static Code Analysis of C

Abstract

Abstract. Static analysis of source code is one way to find bugs and problems in large software projects. Many approaches to static analysis have been proposed. We proposed a novel way of performing static analysis. Instead of methods based on semantic/logic analysis we apply machine learning directly to the problem. This has many benefits. Learning by example means trivial programmer adaptability (a problem with many other approaches), learning systems also has the advantage to be able to generalise and find problematic source code constructs that are not exactly as the programmer initially thought, to name a few. Due to the general interest in code quality and the availability of large open source code bases as test and development data, we believe this problem should be of interest to the larger data mining community. In this work we extend our previous approach and investigate a new way of doing feature selection and test the suitability of many different learning algorithms. This on a selection of problems we adapted from large publicly available open source projects. Many algorithms were much more successful than our previous proof-of-concept, and deliver practical levels of performance. This is clearly an interesting and minable problem.

Combining Clustering and Classification for Software Quality Evaluation

“…Tribus et al [5] focused on using classifiers for knowledge discovery and troubleshooting software written in C. Menzies et al used data mining to predict errors and assist large project management [4]. They used metrics such as McCabe's CC, Halstead's MI as well as LOC for C code, and classifiers such as C4.5.…”

“…Experience shows that collecting and analyzing fine grained test defects from large, complex software systems is difficult [1]. Data mining has been shown to facilitate quality evaluation when applied directly to source code as well as metrics extracted from code [3][4] [5]. Static analysis using software quality metrics means that the code is analyzed without having to execute the program [2].…”