Demo Data from EDBT 2026 / reviewers in the wild / expert
Pat Faherty
dblp:73/694
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2002
—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
black-box testing |
0.0 | 1 | 2002 | Generating Expected Results for Automated Black-Box Testing · ASE 2002 |
Software testing
combinatorial testing |
0.0 | 1 | 2002 | Generating Expected Results for Automated Black-Box Testing · ASE 2002 |
Software testing › test generation
test suite generation |
0.0 | 1 | 2002 | Generating Expected Results for Automated Black-Box Testing · ASE 2002 |
Methods — techniques the papers use, named apart from their topics
input-output relationship analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2002 | Generating Expected Results for Automated Black-Box TestingabstractIn this paper we describe a technique for generating expected results for automated black-box testing. Generating expected results allows larger automated test suites to be created, moving us toward continuous product testing. Our technique uses a program's Input-Output (IO) relationships to identify unique combinations of program inputs that influence program outputs. With this information, a small set of test cases is executed and checked for correctness. Given the correctness of this set, the expected results for the larger combinatorial test set can be generated automatically. Included in the paper is an experimental study in which checking the results of 384 test cases allows us to generate expected results and fully automate nearly 600,000 test cases. Patrick J. Schroeder, Pat Faherty, Bogdan Korel |
ASE | 2 |