A mapping study on Bayesian networks for software quality prediction

Ayse Tosun Misirli, Ayşe Başar Bener

Araştırma sonucu: ???type-name???Konferans katkısıbilirkişi

17 Atıf (Scopus)

Özet

Bayesian Networks (BN) have been used for decision making in software engineering for many years. We investigate the current status of BNs in predicting software quality in three aspects: 1) techniques used for parameter learning, 2) techniques used for structure learning, and 3) type of variables that represent BN nodes. We performed a systematic mapping study on 38 primary studies that employed BNs to predict software quality. The most popular technique for building the final structure of BNs is the use of expert knowledge with different inference algorithms. Variables in BNs are treated as categorical in more than 70% of studies. Compared to other domains, the usage of BNs is still very limited due to high dependency on expert knowledge and tools.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığı3rd International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering, RAISE 2014 - Proceedings
YayınlayanAssociation for Computing Machinery, Inc
Sayfalar7-11
Sayfa sayısı5
ISBN (Elektronik)9781450328463
DOI'lar
Yayın durumuYayınlandı - 3 Haz 2014
Harici olarak yayınlandıEvet
Etkinlik3rd International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering, RAISE 2014 - Hyderabad, India
Süre: 3 Haz 2014 → …

Yayın serisi

Adı3rd International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering, RAISE 2014 - Proceedings

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???event.eventtypes.event.conference???3rd International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering, RAISE 2014
Ülke/BölgeIndia
ŞehirHyderabad
Periyot3/06/14 → …

Bibliyografik not

Publisher Copyright:
Copyright 2014 ACM.

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