On the prediction of long-lived bugs: An analysis and comparative study using FLOSS projects-Reference-Cited by-同舟云学术

On the prediction of long-lived bugs: An analysis and comparative study using FLOSS projects

Author:

Gomes Luiz Alberto Ferreira,da Silva Torres Ricardo,Côrtes Mario Lúcio

Funder

Fundação de Amparo à Pesquisa do Estado de São Paulo

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Elsevier BV

Subject

Computer Science Applications,Information Systems,Software

Reference46 articles.

1. Predicting the severity of a reported bug;Lamkanfi,2010

2. Challenges and opportunities for software change request repositories: a systematic mapping study;Cavalcanti;J. Softw.: Evol. Process.,2014

3. Software engineering;Sommerville,2010

4. Analyzing emotion words to predict severity of software bugs: A case study of open source projects;Yang,2017

5. Predicting bug-fixing time: An empirical study of commercial software projects;Zhang,2013

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