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Nathan Giles

dblp:128/5749 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Program analysis · 46% Compilers and program optimization · 46% Debugging and program repair · 7%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program analysis
binary analysis
0.212013
A compiler-level intermediate representation based binary analysis and rewriting system · EuroSys 2013
Compilers and program optimization
binary rewriting
0.212013
A compiler-level intermediate representation based binary analysis and rewriting system · EuroSys 2013
Compilers and program optimization
intermediate representation
0.212013
A compiler-level intermediate representation based binary analysis and rewriting system · EuroSys 2013
Program analysis
symbolic execution
0.212013
A compiler-level intermediate representation based binary analysis and rewriting system · EuroSys 2013

Methods — techniques the papers use, named apart from their topics

static analysis · 0.2
YearPublicationVenuePosition
2013 A compiler-level intermediate representation based binary analysis and rewriting system
abstract
This paper presents component techniques essential for converting executables to a high-level intermediate representation (IR) of an existing compiler. The compiler IR is then employed for three distinct applications: binary rewriting using the compiler's binary back-end, vulnerability detection using source-level symbolic execution, and source-code recovery using the compiler's C backend. Our techniques enable complex high-level transformations not possible in existing binary systems, address a major challenge of input-derived memory addresses in symbolic execution and are the first to enable recovery of a fully functional source-code.
Kapil Anand, Matthew Smithson, Khaled Elwazeer, Aparna Kotha, Jim Gruen, Nathan Giles, Rajeev Barua
EuroSys6
2013 MOSAIC: A Cohesive Method for Orchestrating Discrete Analytics in a Distributed Model
Ransom K. Winder, Joseph P. Jubinski, John Prange, Nathan Giles
NLDB4