EDBT 2026 Demo / reviewers in the wild / expert
Angel Saenz-Badillos
dblp:65/6866
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2008
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 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
functional testing |
0.1 | 1 | 2008 | Automatic Result Verification for the Functional Testing of a Query Language · ICDE 2008 |
Software testing
result verification |
0.1 | 1 | 2008 | Automatic Result Verification for the Functional Testing of a Query Language · ICDE 2008 |
Software testing › test input generation
test database generation |
0.1 | 1 | 2008 | Automatic Result Verification for the Functional Testing of a Query Language · ICDE 2008 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2008 | Automatic Result Verification for the Functional Testing of a Query LanguageabstractFunctional testing of a query language is a challenging task in practice. In order to reveal errors in the query processing functionality, it is necessary to verify the actual result of a test query with the expected correct result. However, automatically computing the expected query result of an arbitrary test query is not trivial. One solution is to first generate a set of test database instances and test queries and then to compute the expected result for each test query over the individual test database instances. The problem of this solution is that many test queries might return an empty query result, which is not interesting for the functional testing of a query language. In this paper, we present a new approach to verify the result of a test query so as to facilitate the functional testing of a query language. Instead of first generating the database instance and then computing the expected result for each test query, we first create one or more interesting expected results for a given test query and then generate a test database instance for each combination of a test query and an expected result individually which returns the expected result if the test query is executed correctly. That way, we enable the verification of the actual result and allow an explicit definition of interesting test cases for the functional testing of a query language. Carsten Binnig, Donald Kossmann, Eric Lo 0001, Angel Saenz-Badillos |
ICDE | 4 |