Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.

Stephen D. Lee

dblp:08/1196 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
0since 2021 · last 1994
—ORCID · none

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

Software engineering, systems software and programming languages · 2

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
Software testing · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Performance modeling and evaluation · 100%

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

TopicWeightPapersLastEvidence papers
Software testing
fault-based testing
0.011994
An Empirical Evaluation of Weak Mutation · IEEE Trans. Software Eng. 1994
Software testing
mutation testing
0.011994
An Empirical Evaluation of Weak Mutation · IEEE Trans. Software Eng. 1994
Software testing
unit testing
0.011994
An Empirical Evaluation of Weak Mutation · IEEE Trans. Software Eng. 1994
Software testing › mutation testing
weak mutation testing
0.011994
An Empirical Evaluation of Weak Mutation · IEEE Trans. Software Eng. 1994

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

empirical evaluation · 0.0
YearPublicationVenuePosition
1994 An Empirical Evaluation of Weak Mutation
abstract
Mutation testing is a fault-based technique for unit-level software testing. Weak mutation was proposed as a way to reduce the expense of mutation testing. Unfortunately, weak mutation is also expected to provide a weaker test of the software than mutation testing does. This paper presents results from an implementation of weak mutation, which we used to evaluate the effectiveness versus the efficiency of weak mutation. Additionally, we examined several options in an attempt to find the most appropriate way to implement weak mutation. Our results indicate that weak mutation can be applied in a manner that is almost as effective as mutation testing, and with significant computational savings.>
A. Jefferson Offutt, Stephen D. Lee
IEEE Trans. Software Eng.2
1994 Correction to "An Empirical Evaluation of Weak Mutation"
A. Jefferson Offutt, Stephen D. Lee
IEEE Trans. Software Eng.2