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Differentiating Feature Realization in Software Product Development
Malmö högskola, Faculty of Technology and Society (TS).ORCID iD: 0000-0003-4908-2708
Malmö högskola, Faculty of Technology and Society (TS).ORCID iD: 0000-0002-7700-1816
Department of Computer Science and Engineering, Chalmers University of Technology, Hörselgången 11, Gothenburg, 412 96, Sweden.
2017 (English)In: Product-Focused Software Process Improvement: Product-Focused Software Process Improvement. PROFES 2017., Springer, 2017, p. 221-236Conference paper, Published paper (Refereed)
Abstract [en]

Software is no longer only supporting mechanical and electrical products. Today, it is becoming the main competitive advantage and an enabler of innovation. Not all software, however, has an equal impact on customers. Companies still struggle to differentiate between the features that are regularly used, there to be for sale, differentiating and that add value to customers, or which are regarded commodity. Goal: The aim of this paper is to (1) identify the different types of software features that we can find in software products today, and (2) recommend how to prioritize the development activities for each of them. Method: In this paper, we conduct a case study with five large-scale software intensive companies. Results: Our main result is a model in which we differentiate between four fundamentally different types of features (e.g. ‘Checkbox’, ‘Flow’, ‘Duty’ and ‘Wow’). Conclusions: Our model helps companies in (1) differentiating between the feature types, and (2) selecting an optimal methodology for their development (e.g. ‘Output-Driven’ vs. ‘Outcome-Driven’).

Place, publisher, year, edition, pages
Springer, 2017. p. 221-236
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10611
Keywords [en]
Data, Feedback, Outcome-driven development, data-driven development, Goal-oriented development
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mau:diva-12579DOI: 10.1007/978-3-319-69926-4_16ISI: 000439967400016Scopus ID: 2-s2.0-85034596851Local ID: 24152OAI: oai:DiVA.org:mau-12579DiVA, id: diva2:1409626
Conference
Product-Focused Software Process Improvement (PROFES), Innsbruck, Austria (29 November - 01 December)
Available from: 2020-02-29 Created: 2020-02-29 Last updated: 2024-06-18Bibliographically approved
In thesis
1. Data-Driven Software Development at Large Scale: from Ad-Hoc Data Collection to Trustworthy Experimentation
Open this publication in new window or tab >>Data-Driven Software Development at Large Scale: from Ad-Hoc Data Collection to Trustworthy Experimentation
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Accurately learning what customers value is critical for the success of every company. Despite the extensive research on identifying customer preferences, only a handful of software companies succeed in becoming truly data-driven at scale. Benefiting from novel approaches such as experimentation in addition to the traditional feedback collection is challenging, yet tremendously impactful when performed correctly. In this thesis, we explore how software companies evolve from data-collectors with ad-hoc benefits, to trustworthy data-driven decision makers at scale. We base our work on a 3.5-year longitudinal multiple-case study research with companies working in both embedded systems domain (e.g. engineering connected vehicles, surveillance systems, etc.) as well as in the online domain (e.g. developing search engines, mobile applications, etc.). The contribution of this thesis is three-fold. First, we present how software companies use data to learn from customers. Second, we show how to adopt and evolve controlled experimentation to become more accurate in learning what customers value. Finally, we provide detailed guidelines that can be used by companies to improve their experimentation capabilities. With our work, we aim to empower software companies to become truly data-driven at scale through trustworthy experimentation. Ultimately this should lead to better software products and services.

Place, publisher, year, edition, pages
Malmö university, Faculty of Technology and society, 2018. p. 357
Series
Studies in Computer Science ; 6
National Category
Engineering and Technology
Identifiers
urn:nbn:se:mau:diva-7768 (URN)10.24834/2043/24873 (DOI)24873 (Local ID)9789171049186 (ISBN)9789171049193 (ISBN)24873 (Archive number)24873 (OAI)
Public defence
2018-06-15, NI:B0E07, Nordenskiöldsgatan 1, 13:00 (English)
Opponent
Note

In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of Malmö University's products or services. Internal or personal use of this material is permitted. If interested in reprinting/republishing IEEE copyrighted material for advertising or promotional purposes or for creating new collective works for resale or redistribution, please go to http://www.ieee.org/publications_standards/publications/rights/rights_link.html to learn how to obtain a License from RightsLink.

Available from: 2020-02-28 Created: 2020-02-28 Last updated: 2024-04-04Bibliographically approved

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fulltext(773 kB)181 downloads
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Publisher's full textScopushttps://profes2017.q-e.at/

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Fabijan, AleksanderOlsson Holmström, Helena

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