- About CS
- Future Students
- Current Students
- News & Events
- Active Learning: Nina Balcan Shores Up Foundations of Her Field
- Algorithm for Success: Zvi Galil Brings the Fire to Georgia Tech
- An Agile Architecture: Hyesoon Kim Looks to Combine CPUs & GPUs
- Box Seats in Atlanta: Fortnow Poised to Take School of CS to the Show
- Quantum Resistance: Chris Peikert & the Power of Lattices
- The People’s Network: Computing Students Work for More Transparent Internet
HomePh.D. Defense of Dissertation: Saswat Anand
Ph.D. Defense of Dissertation: Saswat Anand
Add to Calendar
- May 4, 2012 11:00 am
- KACB 2108
Title: Techniques to Facilitate Symbolic Execution of Real-world Programs
School of Computer Science
College of Computing
Georgia Institute of Technology
When: May 04 Friday 11AM
Where: KACB 2108
- Dr. Mary Jean Harrold (Advisor, School of Computer Science, Georgia Institute of Technology)
- Dr. Mayur Naik (School of Computer Science, Georgia Institute of Technology)
- Dr. Alessandro Orso (School of Computer Science, Georgia Institute of Technology)
- Dr. Santosh Pande (School of Computer Science, Georgia Institute of Technology)
- Dr. Willem Visser (Department of Mathematical Science, University of Stellenbosch, South Africa)
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.