The overall goal of this research is to reduce the cost of software development and improve the quality of software. Symbolic execution is a program-analysis technique that is used to address several problems that arise in developing high-quality software. Despite the fact that the symbolic execution technique is well understood, and performing symbolic execution on simple programs is straightforward, it is still not possible to apply the technique to the general class of large, real-world software. A symbolic-execution system can be effectively applied to large, real-world software if it has at least the two features: efficiency and automation. However, efficient and automatic symbolic execution of real-world programs is a lofty goal because of both theoretical and practical reasons. Theoretically, achieving this goal requires solving an intractable problem (i.e., solving constraints). Practically, achieving this goal requires overwhelming effort to implement a symbolic-execution system that can precisely and automatically symbolically execute real-world programs.
This research makes three major contributions.
1. Three new techniques that address three important problems of symbolic execution. Compared to existing techniques, the new techniques
* reduce the manual effort that may be required to symbolically execute those programs that either generate complex constraints or parts of which cannot be symbolically executed due to limitations of a symbolic-execution system.
* improve the usefulness of symbolic execution (e.g., expose more bugs in a program) by enabling discovery of more feasible paths within a given time budget.
2. A novel approach that uses symbolic execution to generate test inputs for Apps that run on modern mobile devices such as smartphones and tablets.
3. Implementations of the above techniques and empirical results obtained from applying those techniques to real-world programs that demonstrate their effectiveness.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/44733 |
| Date | 11 May 2012 |
| Creators | Anand, Saswat |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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