Demo Data from EDBT 2026 / reviewers in the wild / expert
Robert T. Hughes
dblp:00/1674
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2010
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 2 · 1 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-author
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 |
Empirical software engineering · 100% | |
| Databases, data mining, and information retrieval
1 paper |
Data models and query languages · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering
software metrics |
0.0 | 1 | 2001 | Modeling Software Measurement Data · IEEE Trans. Software Eng. 2001 |
Data models and query languages
entity-relationship model |
0.0 | 1 | 2001 | Modeling Software Measurement Data · IEEE Trans. Software Eng. 2001 |
Methods — techniques the papers use, named apart from their topics
entity-relationship modeling · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2010 | Ontological Modelling to Support the Planning of is Development Processes - A Position Paper
Robert T. Hughes, Graham Winstanley, Karl Cox |
KEOD | 1 |
| 2001 | Modeling Software Measurement DataabstractThis paper proposes a method for specifying models of software data sets in order to capture the definitions and relationships among software measures. We believe a method of defining software data sets is necessary to ensure that software data are trustworthy. Software companies introducing a measurement program need to establish procedures to collect and store trustworthy measurement data. Without appropriate definitions it is difficult to ensure data values are repeatable and comparable. Software metrics researchers need to maintain collections of software data sets. Such collections allow researchers to assess the generality of software engineering phenomena. Without appropriate safeguards, it is difficult to ensure that data from different sources are analyzed correctly. These issues imply the need for a standard method of specifying software data sets so they are fully documented and can be exchanged with confidence. We suggest our method of defining data sets can be used as such a standard. We present our proposed method in terms of a conceptual entity-relationship data model that allows complex software data sets to be modeled and their data values stored. The standard can, therefore, contribute both to the definition of a company measurement program and to the exchange of data sets among researchers. Barbara A. Kitchenham, Robert T. Hughes, Stephen G. Linkman |
IEEE Trans. Software Eng. | 2 |
| 1996 | Expert judgement as an estimating method
Robert T. Hughes |
Inf. Softw. Technol. | 1 |