Soft theory: a pragmatic alternative to conduct quantitative empirical studies

Show simple item record Russo, Daniel Stol, Klaas-Jan 2019-09-02T14:00:42Z 2019-09-02T14:00:42Z 2019-05-27
dc.identifier.citation Russo, D. and Stol, K.-J. (2019) 'Soft theory: a pragmatic alternative to conduct quantitative empirical studies', CESSER-IP '19: Proceedings of the Joint 7th International Workshop on Conducting Empirical Studies in Industry and 6th International Workshop on Software Engineering Research and Industrial Practice, Montreal, Quebec, Canada, 27 May, 3338714: IEEE Press, pp. 30-33. doi: 10.1109/cesser-ip.2019.00013 en
dc.identifier.startpage 30 en
dc.identifier.endpage 33 en
dc.identifier.doi 10.1109/cesser-ip.2019.00013 en
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
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher IEEE Press/ACM en
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
dc.subject Software engineering en
dc.subject Software engineering research en
dc.subject Soft theory en
dc.title Soft theory: a pragmatic alternative to conduct quantitative empirical studies en
dc.type Conference item en
dc.internal.authorcontactother Klaas-Jan Stol, Computer Science, University College Cork, Cork, Ireland. +353-21-490-3000 Email: en
dc.internal.availability Full text available en 2019-09-02T13:52:53Z
dc.description.version Accepted Version en
dc.internal.rssid 498916873
dc.contributor.funder Science Foundation Ireland en
dc.description.status Peer reviewed en
dc.internal.copyrightchecked No
dc.internal.licenseacceptance Yes en
dc.internal.conferencelocation Montreal, Quebec, Canada en
dc.internal.IRISemailaddress en
dc.internal.IRISemailaddress en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Starting Investigator Research Grant (SIRG)/15/SIRG/3293/IE/Software Development with Alternative Workforces/ en
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Research Centres/13/RC/2094/IE/Lero - the Irish Software Research Centre/ en

Files in this item

This item appears in the following Collection(s)

Show simple item record

This website uses cookies. By using this website, you consent to the use of cookies in accordance with the UCC Privacy and Cookies Statement. For more information about cookies and how you can disable them, visit our Privacy and Cookies statement