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Christian Zapf

dblp:51/416 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1996
—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
2 papers
Software testing · 100%

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

TopicWeightPapersLastEvidence papers
Software testing
mutation testing
0.021996
An Experimental Determination of Sufficient Mutant Operators · ACM Trans. Softw. Eng. Methodol. 1996
An Experimental Evaluation of Selective Mutation · ICSE 1993
Software testing › mutation testing
selective mutation
0.021996
An Experimental Determination of Sufficient Mutant Operators · ACM Trans. Softw. Eng. Methodol. 1996
An Experimental Evaluation of Selective Mutation · ICSE 1993
Software testing
unit testing
0.011996
An Experimental Determination of Sufficient Mutant Operators · ACM Trans. Softw. Eng. Methodol. 1996

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

experimental evaluation · 0.0
YearPublicationVenuePosition
1996 An Experimental Determination of Sufficient Mutant Operators
abstract
Mutation testing is a technique for unit-testing software that, although powerful, is computationally expensive, The principal expense of mutation is that many variants of the test program, called mutants, must be repeatedly executed.This article quantifies the expense of mutation in terms of the number of mutants that are created, then proposes and evaluates a technique that reduces the number of mutants by an order of magnitude.Selective mutation reduces.the cost of mutation testing by reducing the number of mutants, This article reports experimental results that compare selective mutation testing with standard, or nonselective, mutation testing, and results that quantify the savings achieved by selective mutation testing, The results support the hypothesis that selective mutation is almost as strong as nonselective mutation: in experimental trials selective mutation provides almost the same coverage as nonselective mutation.with a four-fold or more reduction in the number of mutants.
A. Jefferson Offutt, Ammei Lee, Gregg Rothermel, Roland H. Untch, Christian Zapf
ACM Trans. Softw. Eng. Methodol.5
1993 An Experimental Evaluation of Selective Mutation
A. Jefferson Offutt, Gregg Rothermel, Christian Zapf
ICSE3