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Title:Na umetni inteligenci temelječi pomočniki v sklopu skaliranih metod agilnega razvoja : magistrsko delo
Authors:ID Saklamaeva, Vasilka (Author)
ID Pavlič, Luka (Mentor) More about this mentor... New window
Files:.pdf MAG_Saklamaeva_Vasilka_2023.pdf (3,10 MB)
MD5: E1E1D9030347AA4BB620C045BC82D00A
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Pristopi skaliranega agilnega razvoja se vedno pogosteje uporabljajo v sodobnem programskem inženirstvu, kar organizacijam ob izboljšani ekipni dinamiki omogoča doseganje višje produktivnosti in kakovosti izdelkov. Vključitev umetne inteligence (angl. Artificial Intelligence, AI) v metode skaliranega agilnega razvoja se je pojavila kot odgovor na nenehno povpraševanje po poenostavljenih postopkih in vse večjo kompleksnost razvojnih projektov in vzdrževanja programske opreme. V zaključnem delu se bomo posebej osredotočili na pomočnike, ki temeljijo na AI. Izvedli bomo sistematičen pregled literature, s katerim nameravamo preučiti trenutno stanje raziskav, ki se križajo s skaliranim agilnim razvojem. Pregled vključuje metodologijo za iskanje, izbiro in vrednotenje najrazličnejših publikacij iz izbranih digitalnih knjižnic in baz. Glavni cilj je povzeti in organizirati predhodne raziskave o pomočnikih, ki temeljijo na AI, v metodah skaliranega agilnega razvoja s poudarkom na njihovih zmogljivostih, učinkih na rezultate projekta in potencialnih težavah, ki jih lahko povzročijo. Na takšen način nudimo vpogled v najsodobnejše pomočnike, ki temeljijo na AI, v kontekstu skaliranega agilnega razvoja.
Keywords:umetna inteligenca, pomočniki, agilni razvoj, skalirani agilni razvoj, LeSS, SAFe
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[V. Saklamaeva]
Year of publishing:2023
Number of pages:1 spletni vir (1 datoteka PDF (IX, 60 f.))
PID:20.500.12556/DKUM-85068 New window
UDC:004.411-026.131:004.89(043.2)
COBISS.SI-ID:168577283 New window
Publication date in DKUM:21.09.2023
Views:624
Downloads:244
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-SA 4.0, Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
Link:http://creativecommons.org/licenses/by-nc-sa/4.0/
Description:A Creative Commons license that bans commercial use and requires the user to release any modified works under this license.
Licensing start date:17.08.2023

Secondary language

Language:English
Title:Artificial intelligence-based assistants for scaled agile development methods
Abstract:Scaled Agile Development approaches are now widely used in modern software engineering, allowing businesses to improve teamwork, productivity, and product quality. The Artificial Intelligence (AI) incorporation into scaled agile development methodologies has emerged as a potential strategy in response to the ongoing demand for simplified procedures and the increasing complexity of software projects. In this thesis, while specifically concentrating on AI-based assistants, we are conducting a systematic literature review that intends to examine the present research environment that intersects with scaled agile development. The review implements a methodology to find, choose, and evaluate a wide variety of publications from the chosen databases. The main goal is to summarize and organize the prior research on AI-based assistants in scaled agile development, emphasizing their capabilities, effects on project results, and difficulties they may provide. By conducting the systematic literature review, we provide insight of the state-of-the-art AI-based assistants in the context of scaled agile development.
Keywords:artificial intelligence, assistants, agile development, scaled agile development, LeSS, SAFe


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