2022
Applicability of Software Reliability Growth Models to Open Source Software
MIČKO, Radoslav, Stanislav CHREN a Bruno ROSSIZákladní údaje
Originální název
Applicability of Software Reliability Growth Models to Open Source Software
Autoři
MIČKO, Radoslav (703 Slovensko, domácí), Stanislav CHREN (703 Slovensko, domácí) a Bruno ROSSI (380 Itálie, garant, domácí)
Vydání
Not specified, 48th Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA2022), od s. 255-262, 8 s. 2022
Nakladatel
IEEE
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
10201 Computer sciences, information science, bioinformatics
Stát vydavatele
Spojené státy
Utajení
není předmětem státního či obchodního tajemství
Forma vydání
elektronická verze "online"
Odkazy
Kód RIV
RIV/00216224:14330/22:00125924
Organizační jednotka
Fakulta informatiky
ISBN
978-1-6654-6152-8
Klíčová slova anglicky
Software Reliability Growth Models; Open Source Software; Cumulative Software Failure Data; Mining Software Repositories
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 13. 3. 2023 09:17, Bruno Rossi, PhD
Anotace
V originále
Software reliability growth models (SRGMs) are based on underlying assumptions which make them typically more suited for quality evaluation of closed-source projects and their development lifecycles. Their usage in open-source software (OSS) projects is a subject of debate. Although the studies investigating the SRGMs applicability in OSS context do exist, they are limited by the number of models and projects considered which might lead to inconclusive results. In this paper, we present an experimental study of SRGMs applicability to a total of 88 OSS projects, comparing nine SRGMs, looking at the stability of the best models on the whole projects, on releases, on different domains and according to different projects attributes. With the aid of the STRAIT tool, we automated repository mining, data processing and SRGM analysis for reproducibility. Overall, we found good applicability of SRGMs to OSS, but with different performance when segmenting the dataset into releases, domains and considering projects attributes, suggesting that the search for one-fits-all models is unrealistic, rather recommending to look for the characteristics of projects and bug fixing processes for the prediction of applicable models.
Návaznosti
CZ.02.1.01/0.0/0.0/16_019/0000822, interní kód MU (Kód CEP: EF16_019/0000822) |
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EF16_019/0000822, projekt VaV |
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LM2015085, projekt VaV |
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