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Soft theory: a pragmatic alternative to conduct quantitative empirical studies

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dc.contributor.author Russo, Daniel
dc.contributor.author Stol, Klaas-Jan
dc.date.accessioned 2020-01-23T09:24:04Z
dc.date.available 2020-01-23T09:24:04Z
dc.date.issued 2019
dc.identifier.uri http://hdl.handle.net/10344/8416
dc.description peer-reviewed en_US
dc.description.abstract Practitioners and scholars often face new software engineering phenomena which lack sufficient theoretical grounding. When studying such nascent and emerging topics, it is important to establish an initial and rudimentary understanding, leaving a more precise understanding of underpinning mechanisms till later. Controlled experiments, for example, might lead to insights into the specific mechanisms underpinning a certain practice, such as distributed development, pair programming, and test-driven development. However, at an initial stage of research, such highly controlled studies may not be feasible. In other domains, it may not be clear what the key constructs are, so that effective measurement cannot be done. Instead, researchers might opt for pragmatic alternative research approaches that do not require experimental control or active intervention in a study’s setting. In this paper we advocate the use of soft theory (based on soft modeling techniques) for quantitative studies in software engineering research. We discuss the use of soft theory and position it within an existing taxonomy of quantitative data analysis techniques. Soft modeling and soft theory affords us a pragmatic approach to developing inferential and predictive research models, rather than aiming to develop a causal understanding. Soft theory approaches are grounded in robust quantitative data analysis techniques. We argue that these techniques can be effectively used in industry settings which are not amenable to highly controlled studies. en_US
dc.language.iso eng en_US
dc.publisher IEEE Computer Society en_US
dc.relation 15SIRG3293 en_US
dc.relation.ispartofseries 2019 IEEE/ACM Joint 7th International Workshop on Conducting Empirical Studies in Industry (CESI) and 6th International Workshop on Software Engineering Research and Industrial Practice (SER&IP);
dc.relation.uri http://dx.doi.org/10.1109/CESSER-IP.2019.00013
dc.rights © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. en_US
dc.subject software engineering en_US
dc.subject experiments en_US
dc.title Soft theory: a pragmatic alternative to conduct quantitative empirical studies en_US
dc.type info:eu-repo/semantics/conferenceObject en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1109/CESSER-IP.2019.00013
dc.contributor.sponsor SFI en_US
dc.relation.projectid 15/SIRG/3293 en_US
dc.relation.projectid 13/RC/2094 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US


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