Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Scott Drylie

dblp:369/6517 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0001-2106-5765ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 since 2021

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 · 87% Software maintenance and evolution · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Empirical software engineering
software effort estimation
0.812024
An Assessment of Rules of Thumb for Software Phase Management, and the Relationship Between Phase Effort and Schedule Success · IEEE Trans. Software Eng. 2024
Empirical software engineering
software project management
0.812024
An Assessment of Rules of Thumb for Software Phase Management, and the Relationship Between Phase Effort and Schedule Success · IEEE Trans. Software Eng. 2024

Methods — techniques the papers use, named apart from their topics

least squares models · 0.8hotelling's t² test · 0.8
YearPublicationVenuePosition
2024 An Assessment of Rules of Thumb for Software Phase Management, and the Relationship Between Phase Effort and Schedule Success
abstract
In the planning of a software development project, managers must estimate the amount of effort needed for distinct phases of activity. A number of rules of thumb exist in the literature to help the program manager in this task. However, very little work has been done to validate these rules of thumb. Applying least square models and Hotelling's$T^{2}$test, we evaluate these rules of thumb against a large database of Department of Defense projects. We determine that variability limits the simple application of any such rule. However, there are some worthy of closer attention, and we recommend adjustments for improved application. We also determine that projects which give extra attention to early phases experience less schedule growth. These findings were robust across developmental process type, military service, and project size.
Daniel Long, Scott Drylie, Jonathan D. Ritschel, Clay Koschnick
IEEE Trans. Software Eng.2