Demo Data from VLDB 2026 / reviewers in the wild / expert
Jeff Mellen
dblp:73/4261
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2003
—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 · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Software testing › test generation
test suite generation |
0.0 | 1 | 2003 | Improving Test Suites via Operational Abstraction · ICSE 2003 |
Software testing › regression testing
test suite reduction |
0.0 | 1 | 2003 | Improving Test Suites via Operational Abstraction · ICSE 2003 |
Software testing › test coverage
code coverage |
0.0 | 1 | 2003 | Improving Test Suites via Operational Abstraction · ICSE 2003 |
Methods — techniques the papers use, named apart from their topics
operational difference technique · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2003 | Improving Test Suites via Operational AbstractionabstractThis paper presents the operational difference technique for generating, augmenting, and minimizing test suites. The technique is analogous to structural code coverage techniques, but it operates in the semantic domain of program properties rather than the syntactic domain of program text. The operational difference technique automatically selects test cases; it assumes only the existence of a source of test cases. The technique dynamically generates operational abstractions (which describe observed behavior and are syntactically identical to formal specifications)from test suite executions. Test suites can be generated by adding cases until the operational abstraction stops changing. The resulting test suites are as small, and detect as many faults, as suites with 100% branch coverage, and are better at detecting certain common faults. This paper also presents the area and stacking techniques for comparing test suite generation strategies; these techniques avoid bias due to test suite size. Michael Harder, Jeff Mellen, Michael D. Ernst |
ICSE | 2 |