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A. Murray

dblp:19/6978 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2016
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-authorSecurity and privacy · 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 verification · 81% Operating systems · 19%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program verification › system verification
kernel verification
0.011990
The Deductive Theory Manager: A Knowledge Based System for Formal Verification · S&P 1990
Operating systems › system security › operating system security
secure operating system
0.011990
The Deductive Theory Manager: A Knowledge Based System for Formal Verification · S&P 1990

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

knowledge base · 0.0case study · 0.0
YearPublicationVenuePosition
2016 An Industry-focused Advertising Model
A. Murray
ICORES1
1990 The Deductive Theory Manager: A Knowledge Based System for Formal Verification
abstract
Formal verification tools and techniques are difficult and expensive to apply. To make verification of large, complex systems more practical, TRW is developing the deductive theory manager (DTM). A knowledge-based tool that integrates with the Gypsy verification environment (GVE), the DTM supports the construction of deductive theories and applies them to proofs. Knowledge bases applicable to a variety of projects, and one specific to the army secure operating system (ASOS) proofs, are simultaneously under development. The authors describe the underlying philosophy of the verification strategy on which the DTM is based, present the DTM architecture, and illustrate DTM knowledge engineering and proof processing with a case study.>
Ben L. Di Vito, Cristi Garvey, D. Kwong, A. Murray, Jane Solomon, Amy Wu
S&P4