https://www.mdu.se/

mdu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Automated Reuse Recommendation of Product Line Assets based on Natural Language Requirements
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1512-0844
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-2416-4205
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-5032-2310
Show others and affiliations
2020 (English)In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, Vol. 12541, p. 173-189Conference paper, Published paper (Refereed)
Abstract [en]

Software product lines (SPLs) are based on reuse rationale to aid quick and quality delivery of complex products at scale. Deriving a new product from a product line requires reuse analysis to avoid redundancy and support a high degree of assets reuse. In this paper, we propose and evaluate automated support for recommending SPL assets that can be reused to realize new customer requirements. Using the existing customer requirements as input, the approach applies natural language processing and clustering to generate reuse recommendations for unseen customer requirements in new projects. The approach is evaluated both quantitatively and qualitatively in the railway industry. Results show that our approach can recommend reuse with 74% accuracy and 57.4% exact match. The evaluation further indicates that the recommendations are relevant to engineers and can support the product derivation and feasibility analysis phase of the projects. The results encourage further study on automated reuse analysis on other levels of abstractions.

Place, publisher, year, edition, pages
2020. Vol. 12541, p. 173-189
Keywords [en]
software product line, reuse recommender, natural language processing, word embedding
National Category
Engineering and Technology Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-51700DOI: 10.1007/978-3-030-64694-3_11ISI: 000884369800011Scopus ID: 2-s2.0-85097807409OAI: oai:DiVA.org:mdh-51700DiVA, id: diva2:1477942
Conference
International Conference on Software and Systems Reuse ICSR2020, 02 Dec 2020, Virtual, Tunisia
Projects
ARRAY - Automation Region Research AcademyXIVT - eXcellence in Variant TestingAvailable from: 2020-10-20 Created: 2020-10-20 Last updated: 2023-04-12Bibliographically approved
In thesis
1. Requirements-Level Reuse Recommendation and Prioritization of Product Line Assets
Open this publication in new window or tab >>Requirements-Level Reuse Recommendation and Prioritization of Product Line Assets
2021 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Software systems often target a variety of different market segments. Targeting varying customer requirements requires a product-focused development process. Software Product Line (SPL) engineering is one possible approach based on reuse rationale to aid quick delivery of quality product variants at scale. SPLs reuse common features across derived products while still providing varying configuration options. The common features, in most cases, are realized by reusable assets. In practice, the assets are reused in a clone-and-own manner to reduce the upfront cost of systematic reuse. Besides, the assets are implemented in increments, and requirements prioritization also has to be done. In this context, the manual reuse analysis and prioritization process become impractical when the number of derived products grows. Besides, the manual reuse analysis process is time-consuming and heavily dependent on the experience of engineers.

In this licentiate thesis, we study requirements-level reuse recommendation and prioritization for SPL assets in industrial settings. We first identify challenges and opportunities in SPLs where reuse is done in a clone-and-own manner.  We then focus on one of the identified challenges: requirements-based SPL assets reuse and provide automated support for identifying reuse opportunities for SPL assets based on requirements. Finally, we provide automated support for requirements prioritization in the presence of dependencies resulting from reuse.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2021
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 306
National Category
Embedded Systems
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-53667 (URN)978-91-7485-504-3 (ISBN)
Presentation
2021-05-05, Lambda + Teams, Mälardalens högskola, Västerås, 13:15 (English)
Opponent
Supervisors
Funder
Vinnova, XIVTKnowledge Foundation, ARRAY
Available from: 2021-04-07 Created: 2021-03-19 Last updated: 2021-04-24Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Abbas, MuhammadSaadatmand, MehrdadEnoiu, Eduard PaulSundmark, Daniel

Search in DiVA

By author/editor
Abbas, MuhammadSaadatmand, MehrdadEnoiu, Eduard PaulSundmark, Daniel
By organisation
Embedded Systems
Engineering and TechnologyComputer Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 1330 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf