Barrett, The Honors College Thesis/Creative Project Collection
Barrett, The Honors College at Arizona State University proudly showcases the work of undergraduate honors students by sharing this collection exclusively with the ASU community.
Barrett accepts high performing, academically engaged undergraduate students and works with them in collaboration with all of the other academic units at Arizona State University. All Barrett students complete a thesis or creative project which is an opportunity to explore an intellectual interest and produce an original piece of scholarly research. The thesis or creative project is supervised and defended in front of a faculty committee. Students are able to engage with professors who are nationally recognized in their fields and committed to working with honors students. Completing a Barrett thesis or creative project is an opportunity for undergraduate honors students to contribute to the ASU academic community in a meaningful way.
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- Creators: Computer Science and Engineering Program
This thesis presents a possible solution to the problem of web application cloning. Our approach is a novel application of inductive programming, which we call inductive reverse engineering. The goal of inductive reverse engineering is to automatically reverse engineer an abstraction of the web application’s code in a completely black-box manner. We build this approach using recent advances in inductive programming, and we solve several technical challenges to scale the inductive programming techniques to realistic-sized web applications. We target the initial version of our inductive reverse engineering tool to a subset of web applications, i.e., those that do not store state and those that do not have loops. We introduce an evaluation methodology for web application cloning techniques and evaluate our approach on several real-world web applications. The results indicate that inductive reverse engineering can effectively reverse engineer specific types of web applications. In the future, we hope to extend the power of inductive reverse engineering to web applications with state and to learn loops, while still maintaining tractability.