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Hendrik Speidel

dblp:88/10357 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2011
—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
Software testing · 50% Program verification · 50%

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

TopicWeightPapersLastEvidence papers
Program verification
model checking
0.112011
Detection of feature interactions using feature-aware verification · ASE 2011
Software testing
software product line testing
0.112011
Detection of feature interactions using feature-aware verification · ASE 2011

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

variability encoding · 0.1model checking · 0.1
YearPublicationVenuePosition
2011 Detection of feature interactions using feature-aware verification
abstract
A software product line is a set of software products that are distinguished in terms of features (i.e., end-user-visible units of behavior). Feature interactions —situations in which the combination of features leads to emergent and possibly critical behavior— are a major source of failures in software product lines. We explore how feature-aware verification can improve the automatic detection of feature interactions in software product lines. Feature-aware verification uses product-line-verification techniques and supports the specification of feature properties along with the features in separate and composable units. It integrates the technique of variability encoding to verify a product line without generating and checking a possibly exponential number of feature combinations. We developed the tool suite SPLVERIFIER for feature-aware verification, which is based on standard model-checking technology. We applied it to an e-mail system that incorporates domain knowledge of AT&T. We found that feature interactions can be detected automatically based on specifications that have only local knowledge.
Sven Apel, Hendrik Speidel, Philipp Wendler, Alexander von Rhein, Dirk Beyer 0001
ASE2