1. Razvoj grafičnega vmesnika za ogrodje NiaAML : diplomsko deloAljaž Rant, 2025, diplomsko delo Opis: V diplomskem delu predstavljamo razvoj grafičnega uporabniškega vmesnika za ogrodje NiaAML, ki je ogrodje za samodejno strojno učenje, implementirano v programskem jeziku Python, zasnovano na algoritmih po vzorih iz narave. Cilj diplomskega dela je približati uporabo ogrodja tudi uporabnikom brez programerskega znanja ter jim omogočiti preprosto konfiguracijo in zagon optimizacijskih procesov. Delo vključuje teoretični pregled področja, zasnovo in implementacijo vmesnika ter evalvacijo delovanja.
Ključne besede: samodejno strojno učenje, uporabniški vmesnik, ogrodje NiaAML, Python, klasifikacijski cevovod
Objavljeno v DKUM: 23.09.2025; Ogledov: 0; Prenosov: 12
 Celotno besedilo (2,60 MB) |
2. Celovita primerjava ogrodij React in podprtih metod za upodabljanjeGašper Funda Povše, 2025, magistrsko delo Opis: V magistrskem delu smo primerjali ogrodja React: Next.js, Remix in Gatsby ter njihove podprte metode upodabljanja. Izhajali smo iz potrebe po boljšem razumevanju vpliva teh ogrodij na zmogljivost spletnih aplikacij in kako metode upodabljanja vplivajo na optimizacijo za iskalnike (SEO). V teoretičnem delu smo opisali in primerjali funkcionalnosti ter podporo skupnosti ogrodij. Praktični del vključuje implementacijo aplikacij za merjenje zmogljivosti, velikosti paketa in SEO metrik. Rezultati kažejo, da izbira ogrodja in metode upodabljanja pomembno vpliva na zmogljivost in SEO. Next.js izstopa po priljubljenosti in fleksibilnosti, Remix po interaktivnosti, Gatsby pa po hitrosti statičnih strani. Naloga ponuja smernice za izbiro ustreznega ogrodja glede na tip aplikacije.
Ključne besede: ogrodja React, metode upodabljanja, zmogljivost, SEO metrike, primerjalna analiza
Objavljeno v DKUM: 04.09.2025; Ogledov: 0; Prenosov: 21
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3. Integracija vizualizacijske tehnike Two-key in Sankey-evega diagrama v ogrodje NiaARM : diplomsko deloŽan Vrabič, 2025, diplomsko delo Opis: Zaključno delo obravnava ogrodje NiaARM, namenjeno za rudarjenje asociativnih pravil in
vizualizacijo asociativnih pravil. Predstavljeni so algoritmi, ki jemljejo vzor iz narave in se
uporabljajo za namen rudarjenja asociativnih pravil. Raziskane so različne vizualizacijske
tehnike, vključno z vizualizacijsko tehniko Two-key in Sankeyjevim diagramom.
Predstavljena je integracija obeh vizualizacij v ogrodje NiaARM, prikazani so primeri
uporabe vizualizacij v paketih arulesViz in networkD3. Rezultati vizualizacij zagotavljajo
izboljšano interpretacijo in razumevanje pravil. Zadnji del povzema dosežene cilje in glavne
ugotovitve.
Ključne besede: rudarjenje asociativnih pravil, vizualizacija asociativnih pravil, Two-key in
Sankeyjeva vizualizacija, ogrodje NiaARM
Objavljeno v DKUM: 08.05.2025; Ogledov: 0; Prenosov: 21
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4. The gap between the admitted and the measured technical debt: an empirical studyLuka Pavlič, Tilen Hliš, Marjan Heričko, Tina Beranič, 2022, izvirni znanstveni članek Opis: : Technical debt is a well understood and used concept in IT development. The metaphor,
rooted in the financial world, captures the amount of work that development teams owe to a product.
Every time developers take a shortcut within development, the technical debt accumulates. Technical
debt identification can be accomplished via manual reporting on the technical debt items, which
is called self-admitted technical debt. Several specialised methods and tools have also emerged
that promise to measure the technical debt. Based on experience in the community, the impression
emerged that the measured technical debt is of a significantly different amount than the self-admitted
debt. In this context, we decided to perform empirical research on the possible gap between the two.
We investigated 14 production-grade software products while determining the amount of accumulated technical debt via (a) a self-admitting procedure and (b) measuring the debt. The outcomes
show clearly the significant difference in the technical debt reported by the two methods. We urge
development and quality-assurance teams not to rely on technical debt measurement alone. The tools
demonstrated their strength in identifying low-level code technical debt items that violate a set of
predefined rules. However, developers should have additional insight into violations, based on the
interconnected source code and its relation to the domain and higher-level design decisions.
Ključne besede: technical debt identification, self-admitted technical debt, technical debt measurement, difference comparison
Objavljeno v DKUM: 27.03.2025; Ogledov: 0; Prenosov: 9
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Gradivo ima več datotek! Več... |
5. Digital twins in sport : concepts, taxonomies, challenges and practical potentialsTilen Hliš, Iztok Fister, Iztok Fister, 2024, pregledni znanstveni članek Opis: Digital twins belong to ten of the strategic technology trends according to the Gartner list from 2019, and have encountered a big expansion, especially with the introduction of Industry 4.0. Sport, on the other hand, has become a constant companion of the modern human suffering a lack of a healthy way of life. The application of digital twins in sport has brought dramatic changes not only in the domain of sport training, but also in managing athletes during competitions, searching for strategical solutions before and tactical solutions during the games by coaches. In this paper, the domain of digital twins in sport is reviewed based on papers which have emerged in this area. At first, the concept of a digital twin is discussed in general. Then, taxonomies of digital twins are appointed. According to these taxonomies, the collection of relevant papers is analyzed, and some real examples of digital twins are exposed. The review finishes with a discussion about how the digital twins affect changes in the modern sport disciplines, and what challenges and opportunities await the digital twins in the future.
Ključne besede: artificial intelligence, digital twin, machine learning, optimization, sports, sport science
Objavljeno v DKUM: 04.09.2024; Ogledov: 53; Prenosov: 125
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6. Testops strategije in orodja v okviru neprekinjene dostaveLuka Mlinarič Fekonja, 2024, magistrsko delo Opis: V magistrskem delu smo obravnavali TestOps strategije in orodja v okviru DevOps okolja. Osredotočili smo se na analizo temeljnih pojmov metodologije TestOps, raziskavo izzivov in rešitev integracije TestOps strategij ter orodij v DevOps okolje, primerjavo tradicionalnih in sodobnih metodologij testiranja ter analizo TestOps orodij. Metodološki pristop je vključeval sistematični pregled literature in študijo primera s praktično implementacijo dokaza koncepta ̶ CI/CD cevovoda. Rezultati so pokazali, da integracija TestOps strategij in orodij v DevOps okolje izboljša učinkovitost, hitrost in zanesljivost razvoja programske opreme, zmanjšuje napake, spodbuja inovacije in sodelovanje med ekipami ter izboljša kakovost programske opreme.
Ključne besede: TestOps, DevOps, neprekinjeno testiranje, testiranje v produkciji, neprekinjena dostava
Objavljeno v DKUM: 08.08.2024; Ogledov: 110; Prenosov: 200
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7. Evaluating the usability and functionality of intelligent source code completion assistants: a comprehensive reviewTilen Hliš, Luka Četina, Tina Beranič, Luka Pavlič, 2023, izvirni znanstveni članek Opis: As artificial intelligence advances, source code completion assistants are becoming more advanced and powerful. Existing traditional assistants are no longer up to all the developers’ challenges. Traditional assistants usually present proposals in alphabetically sorted lists, which does not make a developer’s tasks any easier (i.e., they still have to search and filter an appropriate proposal manually). As a possible solution to the presented issue, intelligent assistants that can classify suggestions according to relevance in particular contexts have emerged. Artificial intelligence methods have proven to be successful in solving such problems. Advanced intelligent assistants not only take into account the context of a particular source code but also, more importantly, examine other available projects in detail to extract possible patterns related to particular source code intentions. This is how intelligent assistants try to provide developers with relevant suggestions. By conducting a systematic literature review, we examined the current intelligent assistant landscape. Based on our review, we tested four intelligent assistants and compared them according to their functionality. GitHub Copilot, which stood out, allows suggestions in the form of complete source code sections. One would expect that intelligent assistants, with their outstanding functionalities, would be one of the most popular helpers in a developer’s toolbox. However, through a survey we conducted among practitioners, the results, surprisingly, contradicted this idea. Although intelligent assistants promise high usability, our questionnaires indicate that usability improvements are still needed. However, our research data show that experienced developers value intelligent assistants highly, highlighting their significant utility for the experienced developers group when compared to less experienced individuals. The unexpectedly low net promoter score (NPS) for intelligent code assistants in our study was quite surprising, highlighting a stark contrast between the anticipated impact of these advanced tools and their actual reception among developers.
Ključne besede: intelligent assistants, source code completion, source code
Objavljeno v DKUM: 21.05.2024; Ogledov: 188; Prenosov: 38
Celotno besedilo (590,64 KB)
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9. Primerjava samodejne in manualne ocene količine tehničnega dolga : magistrsko deloTilen Hliš, 2020, magistrsko delo Opis: V magistrskem delu smo raziskali področje metod za ocenjevanje količine tehničnega dolga. Izvedli smo sistematičen pregled literature, s katerim smo raziskali metode, ki se uporabljajo v orodjih za samodejno ocenjevanje količine tehničnega dolga. Analizirali in zbrali smo orodja, ki te metode implementirajo. Na petih izbranih projektih razvoja informacijskih rešitev smo izvedli popis tehničnega dolga. Pri tem smo najprej izvedli manualno identifikacijo in ocenjevanje količine tehničnega dolga. Sledila je samodejna identifikacija in ocenjevanje količine tehničnega dolga s pomočjo orodij. V zaključnem delu popisovanja smo dobljene manualne in samodejne ocene med seboj primerjali in analizirali. Empirični podatki, pridobljeni v popisu nakazujejo na velik razkorak med manualno in samodejno oceno.
Ključne besede: tehničen dolg, metode ocenjevanja, orodja, merjenje
Objavljeno v DKUM: 03.07.2020; Ogledov: 1681; Prenosov: 279
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10. E-vrt: mreža izobraževalnih in bivalnih vrtov : končno poročilo o raziskovalnem projektuMelita Rozman Cafuta, Ana Vovk, Marko Hölbl, Matjaž P. Nekrep, Tatjana Perc Nekrep, Gorazd Mauer, Dario Dogša, Tjaša Pauko, Lucija Cvejan, Špela Arzenšek, Danijel Davidović, Tilen Hliš, Jaka Zavratnik, Miha Podplatnik, 2018, končno poročilo o rezultatih raziskav Ključne besede: vrtovi, bivalni vrtovi, e-vrtovi, monitoring
Objavljeno v DKUM: 30.01.2019; Ogledov: 1649; Prenosov: 113
Celotno besedilo (417,23 KB) |
