A theory of value for value-based feature selection in software engineering
|Author:||Rodríguez, Pilar1; Urquhart, Cathy2; Mendes, Emilia3|
1M3S Group, University of Oulu, Oulu, Finland
2Faculty of Business and Law, Manchester Metropolitan University, United Kingdom
3Computer Science, Blekinge Tekniska Hogskola, 4206 Karlskrona, Blekinge Sweden
|Online Access:||PDF Full Text (PDF, 2.3 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2020051126031
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2020-05-11
Value-Based Software Engineering stresses the role of value in software related decisions. In the context of feature selection, software features judged to provide higher value take priority in the development process. This paper focuses on what value means when selecting software features. Using grounded theory, we conducted and analyzed semi-structured interviews with 21 key stakeholders (decision-makers) from three software/software-intensive companies, within a context where value-based decision-making was already established. Our analysis led to the building of a theory of value for value-based feature selection that identifies the nature of value propositions considered by key stakeholders when selecting software features (i.e. decision-making criteria for deciding upon software features, as suggested by Boehm (2003)). We found that some value propositions were common to all three company cases (core value propositions), whereas others were dependent upon the context in which a company operates, and the characteristics of the product under development (specific value propositions). Moreover, value propositions vary according to the stakeholder group and the type of feature being assessed. Our study provides significant insight into value in the context of feature selection, and generates new concepts around value-based feature selection such as new value propositions.
IEEE transactions on software engineering
|Pages:||1 - 28|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
113 Computer and information sciences
We would like to thank the companies that collaborated with us for its commitment and in-kind time. This research has been carried out within the FiDiPro project number 40150/14, which was funded by Tekes (the Finnish Funding Agency for Technology and Innovation).
© 2020 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.