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Laura E. Barton

dblp:210/8829 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

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

Software engineering, systems software and programming languages · 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
Empirical software engineering · 81% Program analysis · 19%

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

TopicWeightPapersLastEvidence papers
Empirical software engineering › developer studies › developer behavior
developer productivity
0.312017
The Work Life of Developers: Activities, Switches and Perceived Productivity · IEEE Trans. Software Eng. 2017
Empirical software engineering › software engineering research methodology
field study
0.112017
The Work Life of Developers: Activities, Switches and Perceived Productivity · IEEE Trans. Software Eng. 2017
Program analysis › dynamic analysis
runtime monitoring
0.112017
The Work Life of Developers: Activities, Switches and Perceived Productivity · IEEE Trans. Software Eng. 2017

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

monitoring · 0.3linear regression · 0.3
YearPublicationVenuePosition
2017 The Work Life of Developers: Activities, Switches and Perceived Productivity
abstract
Many software development organizations strive to enhance the productivity of their developers. All too often, efforts aimed at improving developer productivity are undertaken without knowledge about how developers spend their time at work and how it influences their own perception of productivity. To fill in this gap, we deployed a monitoring application at 20 computers of professional software developers from four companies for an average of 11 full work day in situ. Corroborating earlier findings, we found that developers spend their time on a wide variety of activities and switch regularly between them, resulting in highly fragmented work. Our findings extend beyond existing research in that we correlate developers' work habits with perceived productivity and also show productivity is a personal matter. Although productivity is personal, developers can be roughly grouped into morning, low-at-lunch and afternoon people. A stepwise linear regression per participant revealed that more user input is most often associated with a positive, and emails, planned meetings and work unrelated websites with a negative perception of productivity. We discuss opportunities of our findings, the potential to predict high and low productivity and suggest design approaches to create better tool support for planning developers' work day and improving their personal productivity.
André N. Meyer, Laura E. Barton, Gail C. Murphy, Thomas Zimmermann 0001, Thomas Fritz 0001
IEEE Trans. Software Eng.2