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  • Research and Development of Methods of Dynamic Analysis for Detecting Input Data Affecting Conditional Branches Execution

Research and Development of Methods of Dynamic Analysis for Detecting Input Data Affecting Conditional Branches Execution

Student: Dyachkov Leonid

Supervisor: Alexander K. Petrenko

Faculty: Faculty of Computer Science

Educational Programme: System Programming (Master)

Final Grade: 10

Year of Graduation: 2019

Fuzz-testing is an actively developed and used method for software errors search. However there are some disadvantages, for example it may be difficult to reach some code with it. This can be resolved with by giving information about bytes which influenced on branch execution. We made an overview of dynamic analysis frameworks and propose two approaches to get the information. The first approach based on dynamic symbolic execution, we also propose a method based on the Angr framework as its implementation. It was tested on synthetic examples. The second approach is based on dynamic taint analysis. We propose improvements for the moflow gentrace tool to be used as the implementation of the method based on the second approach. This solution was tested on LAVA test set and open source programs.

Full text (added May 30, 2019)

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