Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Bohdan Uhrynovskyi"'
Autor:
VITALIY YAKOVYNA, BOHDAN UHRYNOVSKYI
Publikováno v:
Computer systems and information technologies. :116-124
A complex model based on Continuous-Time Markov Chains is proposed, which combines an extended aging and rejuvenation model taking into account different aging levels and a model of mobile device usage activity. A graph of states and transitions is c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b46de9ce0f407b258f8d280cf9a03c9
https://doi.org/10.31891/csit-2021-5-16
https://doi.org/10.31891/csit-2021-5-16
Autor:
Bohdan Uhrynovskyi, Vitaliy Yakovyna
Publikováno v:
Vìsnik Nacìonalʹnogo unìversitetu "Lʹvìvsʹka polìtehnìka". Serìâ Ìnformacìjnì sistemi ta merežì. 9:32-43
Mobile systems and devices including Android are vulnerable to the effects of software aging which are manifested in performance degradation during long run-time. It is important to identify efficient system and user interface metrics for detecting a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e6afee478ebaf2c4d212db407ccd0726
https://doi.org/10.23939/sisn2021.09.032
https://doi.org/10.23939/sisn2021.09.032
Publikováno v:
Electronics; Volume 12; Issue 7; Pages: 1600
The more complex the software system, the greater the number of possible combinations of defects that can cause errors, resulting in software defects that are difficult to isolate and expensive to correct in the development stage. An essential featur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9194771f22fd2d4807a3cd4390bd75d4
https://doi.org/10.3390/electronics12071600
https://doi.org/10.3390/electronics12071600
Publikováno v:
2019 IEEE 14th International Conference on Computer Sciences and Information Technologies (CSIT).
This paper describes the results of software failures prediction using regression (Auto-Regressive Integrated Moving Average, ARIMA), smoothing (Holt - Winters) and neural networks (Neural Network Auto-Regressive, NNAR) models. GitHub service was use
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::32966dfa857812473e8507f07249b6f0
https://doi.org/10.1109/stc-csit.2019.8929863
https://doi.org/10.1109/stc-csit.2019.8929863