20.500.12556/RUL-142922 Kontrola kakovosti omrežne programske opreme s pomočjo statistične analize Quality control of network software using statistical analysis Da tehnološka podjetja ostanejo konkurenčna svojim strankam, ponujajo novo in stabilno programsko opremo, kar zagotavljajo s kontrolo kakovosti. Zaradi hitrega razvoja se kljub robustnemu testiranju pojavljajo napake, ki jih je mogoče zaznati s pomočjo statistične analize. Za boljše razumevanje problematike v uvodu predstavimo obravnavano omrežno programsko opremo ter jasno definiramo cilje statističnega testiranja. Hipoteze temeljijo na količini generiranih alarmov (število ponovnih zagonov) ob določeni verziji programske opreme. Zaradi števne narave alarmov se delo osredotoča na metode modeliranja števnih podatkov. V ospredju je bila uporaba posplošenih linearnih modelov z dodatkom modeliranja povečanega števila ničel. Delo smo zaključili z empirično analizo števila ponovnih zagonov, kjer smo opravili analizo posameznih modelov ter primerjali njihovo kakovost. Izmed vseh modelov se je najbolje prilegal negativno binomski model, razširitve modeliranja presežka ničel v tem primeru niso prinesle večjih izboljšav. Model je pokazal, da so za različne verzije programske opreme razlike med številom ponovnih zagonov statistično značilne. For technological companies to stay competitive, they offer their customers new and stable software, which they ensure with quality control. Due to rapid development, despite robust testing, errors occur, errors that can be detected through statistical testing. To better understand the problem, the introduction contains a presentation of the discussed network software and clearly defined goals for statistical testing. Hypotheses are based on the number of alarms (count of reboots) generated at a given software version. Due to the count-like nature of alarms, the work focuses on methods of modeling count data. The focus was on the use of generalised linear models with the addition of modeling excessive zeroes. We concluded the work with an empirical analysis based on the number of restarts, where we performed an evaluation of individual models and compared their quality. Among all the models, the negative binomial model fitted best, in this case, the additional modeling excess of zeros did not yield major improvements. The model showed that for different software versions, the differences between the number of reboots were statistically significant. kontrola kakovosti telekomunikacijska omrežja statistično testiranje programska oprema Poissonov model ničelno-nasičen model model z oviro quality control telecommunications networks statistical testing software Poisson model zero inflated model hurdle model true false false Slovenski jezik Angleški jezik Magistrsko delo/naloga 2022-12-02 13:30:05 2022-12-02 13:30:17 2022-12-05 13:09:19 0000-00-00 00:00:00 2022 0 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 1970-01-01 56581 132324099 Nagelj_Ziga_-_Kontrola_kakovosti_omrezne_programske_opreme_s_pomocjo_statisticne_analize.pdf Nagelj_Ziga_-_Kontrola_kakovosti_omrezne_programske_opreme_s_pomocjo_statisticne_analize.pdf 1 60ED02578520748304BAFFBA065812CD 0155803562dbf464dc6fd7b928d081b159f8b72d81292e0937afb658f40ffe4a f0ad68e6-723c-11ed-9c94-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=164468 Fakulteta za elektrotehniko 0 0 0