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Software security has become an essential component of software development process. It is necessary for an organisation to maintain software security in order to ensure integrity, authenticity and availability of the software product. To ensure software security, one of the major task is to identify vulnerabilities present in the source code before the software is being deployed. Detecting vulnerabilities in early phases of software development cycle, makes the process of fixing those vulnerabilities much easier for software developers. The vulnerability detection can be done either at the production phase, this means when the software is still being developed by statically auditing the source code, or dynamically at run time. In this study, vulnerability detection was done through Static code analysis process. Static code analysis can be done either manually or through automated tools. This paper focuses on using automated source code scanning tools for vulnerabilities detection in a software. Automated static Code Analysis tools audits the entire source code for its quality and identify any potential security vulnerability, if present. Unlike dynamic source code analysis that evaluates the source code behaviour during code execution, which is done quite late in the software development life cycle, Static Code Analysis leads to detection of security vulnerabilities in a source code in early stages of software development process, when the software is still in production phase because it does not require code to be in execution state. This paper firstly explains the importance of incorporating static code analysis in software development life cycle process so as to facilitate early detection of vulnerabilities in software product, and then present a comparative study of various static code analysis tools available for vulnerability detection in C/C++ and JAVA source code. The comparative study of three C/C++ static code analysis tools (flawfinder, RATS and CPPCheck) and two JAVA static code analysis tools (spotbugs and PMD) is done using Juliet (version1.3) test suite and APACHE tomcat dataset respectively, on the basis of category of vulnerability detected by each of the selected tool and the likelihood of false positive reported by each tool. Results showed that Flawfinder detected maximum categories of vulnerabilities and RATS and CPPCheck were almost similar in types of vulnerabilities detected. Also, it was observed that CPPCheck reported maximum number of false positives as compared to other two tools. Java static code analysis tools Spot bugs was able to detect more number of vulnerabilities than PMD.
Kaur et al. (Wed,) studied this question.