Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1007/978-3-...
Part of book or chapter of book . 2020 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
WU Research
Part of book or chapter of book . 2020
License: unspecified
Data sources: WU Research
versions View all 2 versions
addClaim

Empirical Software Engineering Experimentation with Human Computation

Authors: Marta Sabou; Dietmar Winkler; Stefan Biffl;

Empirical Software Engineering Experimentation with Human Computation

Abstract

Empirical software engineering (ESE) focuses on gathering evidence through measurements and experiments involving humans and software systems (software products, processes, and resources). While empirical studies often include considerable human effort for study planning, execution, and data analysis, human computation (HC) methods, such as crowdsourcing, are increasingly used to address human input intensive tasks in software engineering and beyond. Therefore, in this chapter, we explore the use of HC techniques to support ESE experiments. We address researchers from both research communities and provide (1) introductory notions into both fields, (2) an analysis of ESE experiment requirements and HC capabilities that could match those, and (3) a concrete example of an ESE experiment that compares the effects of using HC in software inspection with respect to a traditional inspection process preformed using pen and paper. Our focus is on software inspection for detecting defects in software engineering models (namely, extended entity relationship models). This chapter will enable ESE researchers to apply HC in their work and HC researchers to explore ESE as a new application area to further improve their methods and tools.

Country
Austria
Related Organizations
Keywords

102022 Softwareentwicklung, 102001 Artificial intelligence, 102001 Artificial Intelligence, 102015 Information systems, 102015 Informationssysteme, 102022 Software development, 102

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!