Scott Moore

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Research

I am a PhD student in the Programming Languages group at Harvard University. Currently, I am working with Stephen Chong on improving the security of commodity operating systems.

In general, I am interested in programming language techniques and formal methods that help programmers write safe, correct, and understandable software.

Publications

Conference papers

Shill: A Secure Shell Scripting Language, Scott Moore, Christos Dimoulas, Dan King, and Stephen Chong. To appear in Proceedings of the 11th Usenix Symposium on Operating Systems Design and Implementation (OSDI), October 2014.

Declarative Policies for Capability Control, Christos Dimoulas, Scott Moore, Aslan Askarov, and Stephen Chong. In Proceedings of the 27th IEEE Computer Security Foundations Symposium (CSF), July 2014.

Precise Enforcement of Progress-Sensitive Security, Scott Moore, Aslan Askarov, and Stephen Chong. In Proceedings of the 19th ACM Conference on Computer and Communications Security (CCS), October 2012.

Static analysis for efficient hybrid information-flow control, Scott Moore and Stephen Chong. In Proceedings of the 24th IEEE Computer Security Foundations Symposium (CSF), June 2011.

Workshop papers

Declaratively Processing Provenance Metadata, Scott Moore, Ashish Gehani, and Natarajan Shankar. In Proceedings of the 5th USENIX conference on the Theory and Practice of Provenance (TaPP), April 2013.

ActionScript Bytecode Verification With Co-Logic Programming, Brian W. DeVries, Gopal Gupta, Kevin W. Hamlen, Scott Moore, and Meera Sridhar. In Proceedings of the ACM SIGPLAN Workshop on Programming Languages and Analysis for Security (PLAS), 9-15, June 2009.

Teaching

In fall term 2014, I was a teaching fellow for CS 152, Harvard's undergraduate course on the formal foundations of programming languages.

In fall term 2011, I was the head teaching fellow for CS 61, Harvard's introductory systems course.

Software

Some software projects that I have contributed to:

Polygot extensible compiler framework
Accrue object analysis framework