2019•Unpublished venueRequires access

Test Case Generation Based on Client-Server of Web Applications by Memetic Algorithm

Weiwei Wang, Xiaohong Guo, Zheng Li, Ruilian Zhao

Open publisher page 10 citations

Abstract

Currently, more than 90% web applications are potentially vulnerable to attacks from both the client side and server side. Test case generation plays a crucial role in testing web applications, where most existing studies focus on test case generation either from client-side or from server-side to detect vulnerabilities, regardless of the interactions between client and server. Consequently, it is difficult for those test cases to discover certain faults which involve both client and server. In this paper, the server-side sensitive paths are considered as vulnerable code paths due to insufficient or erroneous filtering mechanisms. An evolutionary testing approach based on the memetic algorithm is proposed to connect the server-side and client-side, in which test cases are generated from the client-side behavior model, while guided by the coverage of sensitive paths from server-side. The experiments are conducted on four open source web applications, and the results demonstrate that our approach can generate test cases from the client-side behavior model that can cover the server-side sensitive paths, on which the vulnerabilities can be detected more effectively.

About this research paper

What this paper is about

Currently, more than 90% web applications are potentially vulnerable to attacks from both the client side and server side. Test case generation plays a crucial role in testing web applications, where most existing studies focus on test case generation either from client-side or from server-side to detect vulnerabilities, regardless of the interactions between client and server. Consequently, it is difficult for those test cases to discover certain faults which involve both client and server. In this paper, the server-side sensitive paths are considered as vulnerable code paths due to insufficient or erroneous filtering mechanisms. An evolutionary testing approach based on the memetic algorithm is proposed to connect the server-side and client-side, in which test cases are generated from the client-side behavior model, while guided by the coverage of sensitive paths from server-side. The experiments are conducted on four open source web applications, and the results demonstrate that our approach can generate test cases from the client-side behavior model that can cover the server-side sensitive paths, on which the vulnerabilities can be detected more effectively.

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OpenAlex reports 10 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Currently, more than 90% web applications are potentially vulnerable to attacks from both the client side and server side. Test case generation plays a crucial role in testing web applications, where most existing studies focus on test case generation either from client-side or from server-side to detect vulnerabilities, regardless of the interactions between client and server. Consequently, it is difficult for those test cases to discover certain faults which involve both client and server. In this paper, the server-side sensitive paths are considered as vulnerable code paths due to insufficient or erroneous filtering mechanisms. An evolutionary testing approach based on the memetic algorithm is proposed to connect the server-side and client-side, in which test cases are generated from the client-side behavior model, while guided by the coverage of sensitive paths from server-side. The experiments are conducted on four open source web applications, and the results demonstrate that our approach can generate test cases from the client-side behavior model that can cover the server-side sensitive paths, on which the vulnerabilities can be detected more effectively.

Key concepts: Client-side, Server-side, Computer science, Web server, Server, Cross-site scripting, Test case, Memetic algorithm

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