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PhD Final Exam – Mohammad Amin Alipour


Monday, May 1, 2017 1:00 PM - 3:00 PM

Leveraging Generated Tests
The main goal of automated test generation is to improve the reliability of a program by exposing faults to developers. To this end, testing should cover the largest possible portion of the program given a test budget (i.e., time and resources) as frequently as possible. Coverage of a program entity in testing increases our confidence in the correctness of that entity.

Generating various tests to cover a program entity is a particularly hard problem to solve for large software systems because the test inputs are complex and they often exhibit sophisticated feature interactions. As a result, current test generation techniques, such as symbolic execution or search-based testing, do not scale well to complex, large-scale systems.

We propose a test generation technique which aims to increase the frequency of coverage in large, complex software systems. It leverages the information of existing test cases to direct the automated testing. We show the results of the application of this technique to some large systems such as GCC compiler (~850K Lines of code), and Mozilla’s JavaScript engine (~120K lines of code). It increases the frequency of coverage up to the factor of 9x, compared to the state-of-the-art technique.

Major Advisor: Alex Groce
Committee: Marinov Darko
Committee: Martin Erwig
Committee: Danny Dig
Committee: Carlos Jensen
Committee: Cindy Grimm


Kelley Engineering Center (campus map)
4107
Calvin Highes
1 541 737 3168
Calvin.Hughes at oregonstate.edu
Sch Elect Engr/Comp Sci
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