1. Implementacija pragov kakovosti v sklopu programskega inženirstvaNadica Uzunova, 2025, magistrsko delo Opis: Pragovi kakovosti predstavljajo vnaprej določene kontrolne točke znotraj življenjskega cikla razvoja programske opreme, katerih namen je zagotoviti izpolnjevanje določenih kriterijev kakovosti pred prehodom v naslednjo fazo razvoja. V magistrskem delu predstavimo definicijo omenjenega koncepta ter preučujemo, kako prage kakovosti oblikovati, jih povezati z ustreznimi metrikami in vključiti v razvojne procese, zlasti v okolju neprekinjene integracije in dostave. Osredotočamo se na tehnične in metodološke vidike, kot so izbor kriterijev, določanje mejnih vrednosti ter razmerje med ročnim in avtomatiziranim preverjanjem. Delovanje pragov preverimo na praktičnem primeru z uporabo izbranega orodja v realnem razvojnem okolju. Na podlagi ugotovitev ter pregleda literature oblikujemo smernice za določanje pragov kakovosti, ki ponujajo osnovo za nadaljnjo uporabo in razvoj tovrstnih pristopov.
Ključne besede: zagotavljanje kakovosti, razvoj programske opreme, avtomatizacija, orodja, metrike
Objavljeno v DKUM: 08.05.2025; Ogledov: 0; Prenosov: 7
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2. A product quality impacts of a mobile software product line : an empirical studyLuka Pavlič, Tina Beranič, Marjan Heričko, 2021, izvirni znanstveni članek Opis: Background: The software product lines (SPL) enable development teams to fully address a systematic reuse of shared assets to deliver a family of similar software products. Mobile applications are an obvious candidate for employing an SPL approach. This paper presents our research outcomes, based on empirical data from an industry-level development project. Two development teams were confronted with the same functionalities set to be delivered through a family of native mobile applications for Android and iOS.
Methods: Empirical data was gathered before, during and after a year of full-time development. The data demonstrate the impact of a SPL approach by comparing the SPL and non-SPL multiple edition development. One family of products (Android apps) was developed using an SPL approach, while another (iOS apps), functionally the same, was developed without employing an SPL approach. The project generated a volume of raw and aggregated empirical data to support our research questions.
Results: The paper reports a positive impact of an SPL approach on product quality (internal and external) and feature output per week. As data shows, it also increases the delivery of functionalities (240% in 6 more editions), while investing the same amount of effort needed for a single-edition development. As a result of system-supported separation of development and production code, developers had a high confidence in further development. On the other hand, the second team delivered less new functionalities, only two new application editions, and lower software quality than the team that manages multi-edition development by employing an SPL approach.
Ključne besede: software product line, Android, simultaneous development, iOS, Software quality, software product editions
Objavljeno v DKUM: 17.04.2025; Ogledov: 0; Prenosov: 0
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3. 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: 3
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4. Can large-language models replace humans in agile effort estimation? Lessons from a controlled experimentLuka Pavlič, Vasilka Saklamaeva, Tina Beranič, 2024, izvirni znanstveni članek Opis: Effort estimation is critical in software engineering to assess the resources needed for development tasks and to enable realistic commitments in agile iterations. This study investigates whether generative AI tools, which are transforming various aspects of software development, can improve effort estimation efficiency. A controlled experiment was conducted in which development teams upgraded an existing information system, with the experimental group using the generative-AI-based tool GitLab Duo for estimation and the control group using conventional methods (e.g., planning poker or analogy-based planning). Results show that while generative-AI-based estimation tools achieved only 16% accuracy—currently insufficient for industry standards—they offered valuable support for task breakdown and iteration planning. Participants noted that a combination of conventional methods and AI-based tools could offer enhanced accuracy and efficiency in future planning.
Ključne besede: software engineering, agile development, iteration planning, effort estination, generative AI, tool accuracy
Objavljeno v DKUM: 24.12.2024; Ogledov: 0; Prenosov: 14
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5. Razvoj reaktivnih zalednih sistemov na osnovi platforme QuarkusNik Kovačević, Luka Pavlič, 2024, magistrsko delo Opis: V sodobnem mikrostoritevenem okolju se pogosto soočamo z visokimi stroški oblačne infrastrukture. Zato smo v magistrski nalogi raziskali reaktivne zaledne sisteme, ki omogočajo boljšo učinkovitost in nižjo porabo strojnih virov pri obdelavi zahtev. Osredotočili smo se na reaktivni zaledni sistem v ogrodju Quarkus, primerjali pa smo ga s tradicionalnima zalednima sistemoma v ogrodjih Quarkus in Spring Boot.
V nalogi smo implementirali reaktivni zaledni sistem v ogrodju Quarkus in ga primerjali s tradicionalnima zalednima sistemoma, pri tem pa smo identificirali vse izzive, s katerimi smo se soočili skozi celoten cikel razvoja. V okviru testiranja smo simulirali visoko obremenitev s pošiljanjem sočasnih zahtev in ugotovili, da reaktivni pristop kaže krajše čase obdelave in nižjo porabo virov. Pri izbiri pristopa je potrebno uravnotežiti višje stroške razvoja reaktivnega sistema z možnimi prihranki pri oblačnih stroških.
Ključne besede: Quarkus, Spring Boot, zaledni sistemi, reaktivni zaledni sistem
Objavljeno v DKUM: 23.12.2024; Ogledov: 0; Prenosov: 31
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6. Uporaba GitHub Actions pri avtomatizaciji dostave informacijskih rešitevTjan Ljubešek, 2024, diplomsko delo Opis: Tekom zaključnega dela smo raziskovali uporabo GitHub Actions pri avtomatizaciji dostave informacijskih rešitev. Izvedli smo pregled literature in študijo primera z vzpostavitvijo delovnega toka za kontinuirano integracijo in dostavo programske opreme. Preučevali smo vpliv različnih strategij razvoja in struktur repozitorijev na učinkovitost delovnih tokov. Ugotovili smo, da je vzpostavitev GitHub Actions za avtomatizacijo nalog, kot so gradnja, testiranje in uvajanje aplikacij, relativno enostavna, še posebej v začetnih fazah razvoja. Na podlagi svojih ugotovitev smo zaključili, da lahko določene kombinacije razvojnih strategij in struktur repozitorijev zmanjšajo stroške in podpirajo dobre prakse.
Ključne besede: avtomatizacija, GitHub Actions, DevOps, repozitoriji, delovni tokovi
Objavljeno v DKUM: 19.09.2024; Ogledov: 0; Prenosov: 29
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7. Avtomatizacija zagotavljanja infrastrukture s platformo TerraformPetar Nikolov, 2024, diplomsko delo Opis: V današnjem svetu se aplikacije hitro razvijajo, kar zahteva nenehne spremembe infrastrukture. V diplomskem delu je Terraform obravnavan kot orodje za infrastrukturo kot kodo (IaC), pri čemer so prikazane prednosti razvoja in uvajanja programske opreme. V nalogi smo primerjali priporočene prakse v orodju Terraform in poudarili njihov vpliv na široko obsežne projekte IaC. Analizirali smo obstoječo literaturo, da bi zasnovali eksperimentalno fazo in potrdili naše teoretične trditve s praktičnim projektom. Ugotovitve razkrivajo, da nekatere prakse sicer povečujejo učinkovitost projekta, vendar niso to edini odločilni dejavniki. Poleg tega se zavedamo, da raba IaC morda ni vedno ustrezna v vseh primerih.
Ključne besede: Terraform, IaC, Infrastruktura kot koda, DevOps, AWS
Objavljeno v DKUM: 19.09.2024; Ogledov: 0; Prenosov: 11
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8. OTS 2024 Advanced information technologies and services : conference proceedings of the 27th conference : zbornik 27. konference2024, zbornik Opis: V zborniku sedemindvajsete konference OTS 2024 so objavljeni prispevki strokovnjakov s področja informatike, v katerih so predstavljena nova spoznanja in trendi razvoja, vpeljave, prilagajanja ter upravljanja informacijskih rešitev, kot tudi konkretni uspešni pristopi in dobre prakse. Prispevki naslavljajo področja sodobnih arhitekturnih izzivov, klasične, generativne in globoke umetne inteligence, sodobnih spletnih ali mobilnih uporabniških vmesnikov, kot tudi tradicionalnih, brezstrežniških in decentraliziranih zalednih sistemov v oblaku. Tematike prispevkov obsegajo tudi zagotavljanje ustreznega skalabilnega okolja zanje ter avtomatizacijo testiranja, merjenje kakovosti in dostavo s proaktivnim naslavljanjem najpogostejših kibernetskih napadov. Rdečo nit prispevkov predstavljajo podatkovne tehnologije, ki so zastopane v obliki klasičnih podatkovnih baz, podatkovnih jezer ter učinkovitega zbiranja, obdelave in vizualizacije velepodatkov. Prispevki tako še naprej omogočajo boljšo povezanost IT strokovnjakov, informatikov, arhitektov in razvijalcev IT rešitev in storitev, kot tudi akademske sfere in gospodarstva.
Ključne besede: programsko inženirstvo, informacijski sistemi, informacijske rešitve, digitalna preobrazba, razvoj mobilnih in spletnih rešitev, arhitekture v oblaku, podatkovne tehnologije, poslovna inteligenca, umetna inteligenca in strojno učenje, obdelava velepodatkov in podatkovnih tokov, metode agilnega razvoja, tehnologije veriženja blokov, kibernetska varnost
Objavljeno v DKUM: 03.09.2024; Ogledov: 63; Prenosov: 50
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9. 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: 31
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10. The potential of ai-driven assistants in scaled agile software developmentVasilka Saklamaeva, Luka Pavlič, 2024, izvirni znanstveni članek Opis: Scaled agile development approaches are now used widely in modern software engineering, allowing businesses to improve teamwork, productivity, and product quality. The incorporation of artificial intelligence (AI) into scaled agile development methods (SADMs) has emerged as a potential strategy in response to the ongoing demand for simplified procedures and the increasing complexity of software projects. This paper explores the intersection of AI-driven assistants within the context of the scaled agile framework (SAFe) for large-scale software development, as it stands out as the most widely adopted framework. Our paper pursues three principal objectives: (1) an evaluation of the challenges and impediments encountered by organizations during the implementation of SADMs, (2) an assessment of the potential advantages stemming from the incorporation of AI in large-scale contexts, and (3) the compilation of aspects of SADMs that AI-driven assistants enhance. Through a comprehensive systematic literature review, we identified and described 18 distinct challenges that organizations confront. In the course of our research, we pinpointed seven benefits and five challenges associated with the implementation of AI in SADMs. These findings were systematically categorized based on their occurrence either within the development phase or the phases encompassing planning and control. Furthermore, we compiled a list of 15 different AI-driven assistants and tools, subjecting them to a more detailed examination, and employing them to address the challenges we uncovered during our research. One of the key takeaways from this paper is the exceptional versatility and effectiveness of AI-driven assistants, demonstrating their capability to tackle a broader spectrum of problems. In conclusion, this paper not only sheds light on the transformative potential of AI, but also provides invaluable insights for organizations aiming to enhance their agility and management capabilities.
Ključne besede: SAFe, scaled agile framework, AI, artificial intelligence, tools, assistants, agile, large-scale
Objavljeno v DKUM: 26.01.2024; Ogledov: 342; Prenosov: 90
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