Domagoj Babic
I joined Google in April 2013 and I'm currently a Staff Research Scientist, tech lead, and manager. My work focuses on research and development of automated software analysis systems for various security-related applications. Primarily, I want my work to have a positive impact on people's lives. I enjoy building top-notch teams and working with them on solving large-scale real-world important problems, while learning and having fun on the way. I'm particularly excited about big technical challenges and enjoy creating the vision, strategy, and technology for taming those challenges.
Over my career, I've published in the areas of verification, testing, security of complex software systems, automated reasoning, grammar inference, and applied formal methods. Before joining Google, I was a research scientist at UC Berkeley and elsewhere in industry.
I earned my Dipl.Ing. in Electrical Engineering and M.Sc. in Computer Science from the Zagreb University (Faculty of Electrical Engineering and Computing) in 2001 and 2003. I received a Ph.D. in Computer Science in 2008 from the University of British Columbia. I was a recipient of the NSERC PDF Research Fellowship (2010-2012), Microsoft Graduate Research Fellowship (2005-2007), and several awards at international programming competitions (1st place at the 2007 Satisfiability Modulo Theories competition in the bit-vector arithmetic category and 3rd place at the 2005 Satisfiability Testing competition in the satisfiable-crafted instances category).
Over my career, I've published in the areas of verification, testing, security of complex software systems, automated reasoning, grammar inference, and applied formal methods. Before joining Google, I was a research scientist at UC Berkeley and elsewhere in industry.
I earned my Dipl.Ing. in Electrical Engineering and M.Sc. in Computer Science from the Zagreb University (Faculty of Electrical Engineering and Computing) in 2001 and 2003. I received a Ph.D. in Computer Science in 2008 from the University of British Columbia. I was a recipient of the NSERC PDF Research Fellowship (2010-2012), Microsoft Graduate Research Fellowship (2005-2007), and several awards at international programming competitions (1st place at the 2007 Satisfiability Modulo Theories competition in the bit-vector arithmetic category and 3rd place at the 2005 Satisfiability Testing competition in the satisfiable-crafted instances category).
Authored Publications
Google Publications
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FUDGE: Fuzz Driver Generation at Scale
Yaohui Chen
Markus Kusano
Caroline Lemieux
Wei Wang
Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ACM
Preview abstract
At Google we have found tens of thousands of security and robustness bugs by fuzzing C and C++ libraries. To fuzz a library, a fuzzer requires a fuzz driver—which exercises some library code—to which it can pass inputs. Unfortunately, writing fuzz drivers remains a primarily manual exercise, a major hindrance to the widespread adoption of fuzzing. In this paper, we address this major hindrance by introducing the Fudge system for automated fuzz driver generation. Fudge automatically generates fuzz driver candidates for libraries based on existing client code. We have used Fudge to generate thousands of new drivers for a wide variety of libraries. Each generated driver includes a synthesized C/C++ program and a corresponding build script, and is automatically analyzed for quality. Developers have integrated over 200 of these generated drivers into continuous fuzzing services and have committed to address reported security bugs. Further, several of these fuzz drivers have been upstreamed to open source projects and integrated into the OSS-Fuzz fuzzing infrastructure. Running these fuzz drivers has resulted in over 150 bug fixes, including the elimination of numerous exploitable security vulnerabilities.
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Proving termination of nonlinear command sequences
Byron Cook
Alan J. Hu
Zvonimir Rakamaric
Formal Asp. Comput., vol. 25 (2013), pp. 389-403
Asynchronously Communicating Visibly Pushdown Systems
Zvonimir Rakamaric
Proceedings of the 2013 IFIP Joint International Conference on Formal Techniques for Distributed Systems, Springer, pp. 225-242
Sigma*: symbolic learning of input-output specifications
Recognizing malicious software behaviors with tree automata inference
Statically-directed dynamic automated test generation
MACE: Model-inference-Assisted Concolic Exploration for Protocol and Vulnerability Discovery
Chia Yuan Cho
Pongsin Poosankam
Kevin Zhijie Chen
Edward XueJun Wu
Dawn Song
USENIX Security Symposium (2011)
Malware Analysis with Tree Automata Inference
Input generation via decomposition and re-stitching: finding bugs in Malware
Juan Caballero
Pongsin Poosankam
Stephen McCamant
Dawn Song
ACM Conference on Computer and Communications Security (2010), pp. 413-425
Inference and analysis of formal models of botnet command and control protocols
Chia Yuan Cho
Eui Chul Richard Shin
Dawn Song
ACM Conference on Computer and Communications Security (2010), pp. 426-439
Approximating the safely reusable set of learned facts
Calysto: scalable and precise extended static checking
Proving Termination by Divergence
Boosting Verification by Automatic Tuning of Decision Procedures
Exploiting Shared Structure in Software Verification Conditions
Structural Abstraction of Software Verification Conditions
B-Cubing: New Possibilities for Efficient SAT-Solving
B-cubing theory: new possibilities for efficient SAT-solving
Efficient SAT solving: beyond supercubes
Integration of supercubing and learning in a SAT solver
