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Scott Ranville

dblp:40/4716 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2001
—ORCID · none

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

Software engineering, systems software and programming languages · 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 · 67% Requirements engineering and software design · 33%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 100%

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

TopicWeightPapersLastEvidence papers
Program verification › invariant verification
invariant checking
0.012001
Automated Validation of Software Models · ASE 2001
Program verification
model checking
0.012001
Automated Validation of Software Models · ASE 2001
Requirements engineering and software design › model-driven engineering
model-driven development
0.012001
Automated Validation of Software Models · ASE 2001
Embedded and real-time systems › automotive embedded systems
automotive software
0.012001
Automated Validation of Software Models · ASE 2001

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

invariant checking · 0.1formal verification · 0.1
YearPublicationVenuePosition
2001 Automated Validation of Software Models
abstract
The paper describes the application of an automated verification tool to a software model developed at Ford Motor Company. Ford already has in place an advanced model-based software development framework that employs the Matlab(R), Simulink(R), and Stateflow(R) modeling tools. During this project, we applied the invariant checker Salsa to a Simulink(R)/Stateflow(R) model of automotive software to check for nondeterminism, missing cases, dead code, and redundant code. During the analysis, a number of anomalies were detected that had not been found during manual review. We argue that the detection and correction of these problems demonstrates a cost-effective application of formal verification that elevates our level of confidence in the model.
Steve Sims, Rance Cleaveland, Kenneth R. Butts, Scott Ranville
ASE4