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The Design and Implementation of a Software Infrastructure for IQ Assessment
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.ORCID iD: 0000-0003-1173-5187
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.ORCID iD: 0000-0002-0835-823X
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.ORCID iD: 0000-0002-7565-3714
2012 (English)In: International Journal of Information Quality, ISSN 1751-0457, Vol. 3, no 1, 49-70 p.Article in journal (Refereed) Published
Abstract [en]

Information quality assessment of technical documentation is an integral part of quality management of products and services. Technical documentation is usually assessed using questionnaires, checklists, and reviews. This is cumbersome, costly and prone to errors. Acknowledging the fact that only people can assess certain quality aspects, we suggest complementing these with software-supported automatic quality assessment. The many different encodings and representations of documentation, e.g., various XML dialects and XML Schemas/DTDs, is one problem. We present a system, a software infrastructure, where abstraction and meta modelling are used to define reusable analyses and visualisations that are independent of specific encodings and representations. We show how this system is implemented and how it: 1) reads information from documentations; 2) performs analyses on this information; 3) visualises the results to help stakeholders understand quality issues. We introduce the system, the architecture and implementation, its adaptation to different formats of documentations and types of analyses, along with a number of real world cases exemplifying the feasibility and benefits of our approach. Altogether, our approach contributes to more efficient information quality assessments.

 

Place, publisher, year, edition, pages
2012. Vol. 3, no 1, 49-70 p.
Keyword [en]
information quality assessment; software-based analysis; technical documentation; software infrastructure; quality management; abstraction; metamodelling; reusable analysis; visualisation.
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:lnu:diva-26318DOI: 10.1504/IJIQ.2012.050049OAI: oai:DiVA.org:lnu-26318DiVA: diva2:627252
Available from: 2013-06-11 Created: 2013-06-11 Last updated: 2017-01-27Bibliographically approved

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Ericsson, MorganWingkvist, AnnaLöwe, Welf
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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