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Embedding research in the industrial field: a case of a transition to a software product line

Published: 16 September 2014 Publication History

Abstract

Java Cards [4, 5] are small resource-constrained embedded systems that have to fulfill rigorous security requirements. Multiple application scenarios demand diverse product performance profiles which are targeted towards markets such as banking applications and mobile applications. In order to tailor the products to the customer's needs we implemented a Software Product Line (SPL). This paper reports on the industrial case of an adoption to a SPL during the development of a highly-secure software system. In order to provide a scientific method which allows the description of research in the field, we apply Action Research (AR). The rationale of AR is to foster the transition of knowledge from a mature research field to practical problems encountered in the daily routine. Thus, AR is capable of providing insights which might be overlooked in a traditional research approach. In this paper we follow the iterative AR process, and report on the successful transfer of knowledge from a research project to a real industrial application.

References

[1]
Common Criteria. Java Card Protection Profile - Open Configuration. Version 3.0 (May 2012).
[2]
D. E. Avison, F. Lau, M. D. Myers, and P. A. Nielsen. Action research. Communications of the ACM, 42(1):94--97.
[3]
P. C. Clements and L. Northrop. Software Product Lines: Practices and Patterns. SEI Series in Software Engineering. Addison-Wesley, 2002.
[4]
Oracle. Runtime Environment Specification. Java Card Platform, Version 3.0.4, Classic Edition, 2011.
[5]
Oracle. Virtual Machine Specification. Java Card Platform, Version 3.0.4, Classic Edition, 2011.
[6]
K. Pohl, G. Böckle, and F. J. van der Linden. Software Product Line Engineering: Foundations, Principles and Techniques. Springer, 2005.
[7]
G. Susman and R. Evered. An assessment of the scientific merits of action research. Administrative science quarterly, Jan. 1978.

Cited By

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  • (2022)Successful combination of database search and snowballing for identification of primary studies in systematic literature studiesInformation and Software Technology10.1016/j.infsof.2022.106908147(106908)Online publication date: Jul-2022
  • (2017)Industry---academia collaborations in software testingSoftware Quality Journal10.1007/s11219-016-9319-525:4(1091-1143)Online publication date: 1-Dec-2017
  • (2016)Applying data analytics towards optimized issue managementProceedings of the 4th International Workshop on Conducting Empirical Studies in Industry10.1145/2896839.2896845(7-13)Online publication date: 14-May-2016
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cover image ACM Conferences
WISE '14: Proceedings of the 2014 international workshop on Long-term industrial collaboration on software engineering
September 2014
78 pages
ISBN:9781450330459
DOI:10.1145/2647648
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 September 2014

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Author Tags

  1. action research
  2. knowledge transfer
  3. software reuse

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Cited By

View all
  • (2022)Successful combination of database search and snowballing for identification of primary studies in systematic literature studiesInformation and Software Technology10.1016/j.infsof.2022.106908147(106908)Online publication date: Jul-2022
  • (2017)Industry---academia collaborations in software testingSoftware Quality Journal10.1007/s11219-016-9319-525:4(1091-1143)Online publication date: 1-Dec-2017
  • (2016)Applying data analytics towards optimized issue managementProceedings of the 4th International Workshop on Conducting Empirical Studies in Industry10.1145/2896839.2896845(7-13)Online publication date: 14-May-2016
  • (2016)A Researcher’s Experiences in Supporting Industrial Software Process ImprovementManaging Software Process Evolution10.1007/978-3-319-31545-4_12(235-255)Online publication date: 16-Sep-2016

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