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Comparison of software tools for static code analysis and the use of software metrics

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dc.contributor.author Oskouei, Elmira Hassani
dc.date.accessioned 2022-08-09T11:27:41Z
dc.date.available 2022-08-09T11:27:41Z
dc.date.issued 2019
dc.identifier.uri http://dspace.yildiz.edu.tr/xmlui/handle/1/12954
dc.description Tez (Yüksek Lisans) - Yıldız Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2019 en_US
dc.description.abstract Software testing processes are one of the most crucial topics now because the usage of software’s has grown so much bigger than before and developers are in desperate need for any ways that can help them test and evaluate their work with causing less time and lower cost. That is why software test metrics and automatic test tools plays an important role in this field. As software’s are getting much bigger and more complex so as testing methods should improve. In our study, first we emphasis on the importance of metrics used for software testing and provide samples of each type then we evaluate two well-known tools which are PMD and SonarQube that are being used often and are open source. PMD is a static code analysis tool that indicates bugs without executing the code. It uses a rule-based approach to analyze the source code. SonarQube performs automatic reviews with static and dynamic analysis of code to detect bugs. We ran these tools on variety of Java open source codes and then measure the differences between the results. In addition, we did a review process on some of the projects and compared the results with the tools. Our results showed that both tools have some weaknesses and also advantages. Some of the bugs were not found by the tools and their xii results were not the same. The logical issues were found during the review but tools are much faster and have lower cost. en_US
dc.language.iso en en_US
dc.subject Software metrics en_US
dc.subject Automatic test tools en_US
dc.subject Software testing en_US
dc.title Comparison of software tools for static code analysis and the use of software metrics en_US
dc.type Thesis en_US


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