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Experimental analysis of dependency factors of Software Product Reliability using SonarQube
Persistent Systems Limited, Bhaskar-Charak, Goa India.
BITS-Pilani Goa Campus, India.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0001-5269-3900
2019 (English)In: IWSM Mensura IWSM-MENSURA2019, Harlem, Netherlands, 2019Conference paper, Published paper (Refereed)
Abstract [en]

Reliability is one of the key attributes of software product quality. Capability for accurate prediction of reliability will allow software product industry to have better market acceptability and enable wider usage in high integrity or critical applications domains for their product. Software Reliability analysis is performed at various stages during software product development life cycle. Popular software reliability prediction models proposed in literature are targeted to specific phases of life cycle with certain identified parameters. However, these models seem to have certain limitations in predicting software reliability in an accurate and acceptable manner to the industry. A recent industrial survey performed by the authors identified several factors which practitioners perceived to have influence in predicting reliability. Subsequently we have conducted an elaborate set of experiments in a systematic way to validate the perceived influence of identified parameters. Reliability of software products from diverse domains and technologies were evaluated using SonarQube. In this paper, we present our experimental evaluation approach, experimental set up and results from the study. Through these controlled experiments and analysis of data, we have identified and further short-listed the probable influential factors affecting software reliability. This paper further sets direction to our future research on modeling software product reliability as a function of the identified influential factors.

Place, publisher, year, edition, pages
Harlem, Netherlands, 2019.
Keywords [en]
Software Reliability, SonarQube, Empirical study, Experimental evaluation, Correlation, Software Product Attributes, Reliability prediction
National Category
Engineering and Technology Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-45143OAI: oai:DiVA.org:mdh-45143DiVA, id: diva2:1348809
Conference
IWSM Mensura IWSM-MENSURA2019, 07 Oct 2019, Harlem, Netherlands
Projects
Future factories in the CloudAvailable from: 2019-09-05 Created: 2019-09-05 Last updated: 2019-09-05Bibliographically approved

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Punnekkat, Sasikumar

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CiteExportLink to record
Permanent link

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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