Demo Data from SIGIR 2026 / reviewers in the wild / expert
T. E. Hastings
dblp:00/3746
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2001
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 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% |
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 effort estimation |
0.0 | 1 | 2001 | A Vector-Based Approach to Software Size Measurement and Effort Estimation · IEEE Trans. Software Eng. 2001 |
Empirical software engineering
software size measurement |
0.0 | 1 | 2001 | A Vector-Based Approach to Software Size Measurement and Effort Estimation · IEEE Trans. Software Eng. 2001 |
Methods — techniques the papers use, named apart from their topics
statistical validation · 0.0function point analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | A Vector-Based Approach to Software Size Measurement and Effort EstimationabstractSoftware size is a fundamental product measure that can be used for assessment, prediction and improvement purposes. However, existing software size measures, such as function points, do not address the underlying problem complexity of software systems adequately. This can result in disproportional measures of software size for different types of systems. We propose a vector size measure (VSM) that incorporates both functionality and problem complexity in a balanced and orthogonal manner. The VSM is used as the input to a vector prediction model (VPM) which can be used to estimate development effort early in the software life-cycle. We theoretically validate the approach against a formal framework. We also empirically validate the approach with a pilot study. The results indicate that the approach provides a mechanism to measure the size of software systems, classify software systems, and estimate development effort early in the software life-cycle to within /spl plusmn/20% across a range of application types. T. E. Hastings, A. S. M. Sajeev |
IEEE Trans. Software Eng. | 1 |