Analyzing defect inflow distribution and applying Bayesian inference method for software defect prediction in large software projects

↓ Direkt till sidans innehåll
↓ Direkt till sidans sekundära innehåll (sidomenyn)

Search: onr:"swepub:oai:gup.ub.gu.se/238772" > Analyzing defect in...

1 of 1
Previous record
Next record
To hitlist

Details
MARC

Rana, RakeshGothenburg University,Göteborgs universitet,Institutionen för data- och informationsteknik (GU),Department of Computer Science and Engineering (GU),University of Gothenburg,Department of Computer Science & Engineering, Chalmers, University of Gothenburg, Göteborg, Sweden (author)

Analyzing defect inflow distribution and applying Bayesian inference method for software defect prediction in large software projects

Article/chapterEnglish2016

Publisher, publication year, extent ...

Elsevier BV,2016

Numbers

LIBRIS-ID:oai:gup.ub.gu.se/238772
https://gup.ub.gu.se/publication/238772URI
https://doi.org/10.1016/j.jss.2016.02.015DOI
https://research.chalmers.se/publication/238772URI
https://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-12642URI

Supplementary language notes

Language:English

Part of subdatabase

SwePubSwePub

Classification

Subject category:ref swepub-contenttype
Subject category:art swepub-publicationtype

Notes

Tracking and predicting quality and reliability is a major challenge in large and distributed software development projects. A number of standard distributions have been successfully used in reliability engineering theory and practice, common among these for modeling software defect inflow being exponential, Weibull, beta and Non-Homogeneous Poisson Process (NHPP). Although standard distribution models have been recognized in reliability engineering practice, their ability to fit defect data from proprietary and OSS software projects is not well understood. Lack of knowledge about underlying defect inflow distribution also leads to difficulty in applying Bayesian based inference methods for software defect prediction. In this paper we explore the defect inflow distribution of total of fourteen large software projects/release from two industrial domain and open source community. We evaluate six standard distributions for their ability to fit the defect inflow data and also assess which information criterion is practical for selecting the distribution with best fit. Our results show that beta distribution provides the best fit to the defect inflow data for all industrial projects as well as majority of OSS projects studied. In the paper we also evaluate how information about defect inflow distribution from historical projects is applied for modeling the prior beliefs/experience in Bayesian analysis which is useful for making software defect predictions early during the software project lifecycle.

Subject headings and genre

TEKNIK OCH TEKNOLOGIER Elektroteknik och elektronik hsv//swe
ENGINEERING AND TECHNOLOGY Electrical Engineering, Electronic Engineering, Information Engineering hsv//eng
NATURVETENSKAP Data- och informationsvetenskap Programvaruteknik hsv//swe
NATURAL SCIENCES Computer and Information Sciences Software Engineering hsv//eng
Software
SRGM
Defect Inflow
Software

Added entries (persons, corporate bodies, meetings, titles ...)

Staron, Miroslaw,1977Gothenburg University,Göteborgs universitet,Institutionen för data- och informationsteknik (GU),Department of Computer Science and Engineering (GU),University of Gothenburg,Department of Computer Science & Engineering, Chalmers, University of Gothenburg, Göteborg, Sweden(Swepub:gu)xstmir (author)
Berger, Christian,1980Gothenburg University,Göteborgs universitet,Institutionen för data- och informationsteknik (GU),Department of Computer Science and Engineering (GU),University of Gothenburg,Department of Computer Science & Engineering, Chalmers, University of Gothenburg, Göteborg, Sweden(Swepub:cth)bergerc (author)
Hansson, JörgenHögskolan i Skövde,Institutionen för informationsteknologi,Forskningscentrum för Informationsteknologi(Swepub:his)hanj (author)
Nilsson, M.Volvo Cars,Volvo Car Group, Göteborg, Sweden (author)
Meding, W.Telefonaktiebolaget L M Ericsson,Ericsson,Ericsson SW Research, Ericsson AB, Gothenburg, Sweden (author)
Göteborgs universitetInstitutionen för data- och informationsteknik (GU) (creator_code:org_t)

Related titles

In:Journal of Systems and Software: Elsevier BV117, s. 229-2440164-12121873-1228

Internet link

Find in a library

Journal of Systems and Software (Search for host publication in LIBRIS)

To the university's database

1 of 1
Previous record
Next record
To hitlist

Find more in SwePub

By the author/editor: Rana, Rakesh; Staron, Miroslaw ...; Berger, Christia ...; Hansson, Jörgen; Nilsson, M.; Meding, W.

About the subject

ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Electrical Engin ...

NATURAL SCIENCES: NATURAL SCIENCES; and Computer and Inf ...; and Software Enginee ...

Articles in the publication: Journal of Syste ...

By the university: University of Gothenburg; Chalmers University of Technology; University of Skövde

Search outside SwePub

Extend your search to:: Google; Google Book Search; Google Scholar

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.

LIBRIS.kb.se