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Susan M. Mitchell

dblp:38/7686 · DBLP profile ↗
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4ranked-venue papers
4as first author
0since 2021 · last 2016
0000-0003-3718-0095ORCID · corroborated

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

Software engineering, systems software and programming languages · 4 · 4 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
Software maintenance and evolution · 50% Empirical software engineering · 50%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software maintenance and evolution
software process improvement
0.112012
Software process improvement through the identification and removal of project-level knowledge flow obstacles · ICSE 2012

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

pilot study · 0.1knowledge mapping · 0.1
YearPublicationVenuePosition
2016 Could removal of project-level knowledge flow obstacles contribute to software process improvement? A study of software engineer perceptions
Susan M. Mitchell, Carolyn B. Seaman
Inf. Softw. Technol.1
2012 Software process improvement through the identification and removal of project-level knowledge flow obstacles
abstract
Uncontrollable costs, schedule overruns, and poor end product quality continue to plague the software engineering field. This research investigates software process improvement (SPI) through the application of knowledge management (KM) at the software project level. A pilot study was conducted to investigate what types of obstacles to knowledge flow exist within a software development project, as well as the potential influence on SPI of their mitigation or removal. The KM technique of “knowledge mapping” was used as a research technique to characterize knowledge flow. Results show that such mitigation or removal was acknowledged by project team members as having the potential for lowering project labor cost, improving schedule adherence, and enhancing final product quality.
Susan M. Mitchell, Carolyn B. Seaman
ICSE1
2011 A Knowledge Mapping Technique for Project-level Knowledge Flow Analysis
abstract
A pilot study was conducted within a software development domain using "knowledge mapping" (K-mapping) as a research technique to locate and indicate improvements to problematic software project-level knowledge flows (K-flows). The goal of the study is to show that the mitigation or removal of obstacles to project-level K-flow will result in software process improvement (SPI) by lowering project labor cost, improving schedule adherence, and/or enhancing end-product quality. Results show support for the efficacy of the study's K-mapping technique for the identification and management of software project K-flow obstacles. Additionally, the suggested alleviation of such obstacles was acknowledged by project team members as having the potential for a positive effect on SPI.
Susan M. Mitchell, Carolyn B. Seaman
ESEM1
2009 A comparison of software cost, duration, and quality for waterfall vs. iterative and incremental development: A systematic review
abstract
The objective of this study is to present a body of evidence that will assist software project managers to make informed choices about software development approaches for their projects. In particular, two broadly defined competing approaches, the traditional ldquowaterfallrdquo approach and iterative and incremental development (IID), are compared with regards to development cost and duration, and resulting product quality. The method used for this comparison is a systematic literature review. The small set of studies we located did not demonstrate any identifiable cost, duration, or quality trends, although there was some evidence suggesting the superiority of IID (in particular XP). The results of this review indicate that further empirical studies, both quantitative and qualitative, on this topic need to be undertaken. In order to effectively compare study results, the research community needs to reach a consensus on a set of comparable parameters that best assess cost, duration, and quality.
Susan M. Mitchell, Carolyn B. Seaman
ESEM1