Recent Submissions

  • Hyppo: efficient discovery and execution of data science pipelines in collaborative environments 

    Kontaxakis, Antonios; Sacharidis, Dimitris; Simitsis, Alkis; Abelló Gamazo, Alberto; Nadal Francesch, Sergi (OpenProceedings.org, 2025)
    Conference report
    Open Access
    In exploratory data science and machine learning (ML), developing an effective and efficient solution involves the exploration of numerous pipelines per dataset, considering various combinations of data preprocessing, ...
  • Capturing analytical intents from text 

    Pons Recasens, Gerard; Dimic, Miona; Bilalli, Besim (Springer, 2024)
    Conference report
    Restricted access - publisher's policy
    The ability to extract valuable information from data is crucial for organizations and individuals who want to remain competitive in a constantly evolving data-driven environment. However, some of them lack the skills ...
  • Knowledge graphs for enhancing large language models in entity disambiguation 

    Pons Recasens, Gerard; Bilalli, Besim; Queralt Calafat, Anna (Springer, 2024)
    Conference report
    Restricted access - publisher's policy
    Recent advances in Large Language Models (LLMs) have positioned them as a prominent solution for Natural Language Processing tasks. Notably, they can approach these problems in a zero or few-shot manner, thereby eliminating ...
  • Web API change-proneness prediction 

    Koçi, Rediana; Franch Gutiérrez, Javier; Jovanovic, Petar; Abelló Gamazo, Alberto (Institute of Electrical and Electronics Engineers (IEEE), 2024)
    Conference report
    Open Access
    Change-proneness of software artifacts has been mainly related to the design characteristics and their previous history of changes. While these two aspects are essential and contribute significantly to the prediction, they ...
  • Environmental sustainability of machine learning systems: reducing the carbon impact of their lifecycle process 

    Martínez Fernández, Silverio Juan (Springer, 2024)
    Conference report
    Restricted access - publisher's policy
    Software-related carbon dioxide emissions from the information and communications technology sector currently account for up to 3.9% of global emissions. With the increasing use of Machine Learning (ML) systems, this ...
  • Insights on the use of software design principles in machine learning pipelines 

    López Cuesta, Lidia; Gómez Seoane, Cristina; Ayala Martínez, Claudia Patricia (Springer, 2024)
    Conference report
    Restricted access - publisher's policy
    The rapid expansion of Artificial Intelligence has driven a surge in the development of Machine Learning (ML) pipelines, essential for constructing and maintaining ML models. Despite the growing recognition of the importance ...
  • Stories vs. user stories: a terminological clarification 

    Franch Gutiérrez, Javier; Steffe, Hans-Jörg; Bühne, Stan; López Cuesta, Lidia; Sturm, Stefan (Springer, 2024)
    Conference lecture
    Open Access
    User stories are the main vehicle to describe user needs in Agile projects and Agile project developments. But being this concept universally agreed, we may find that not all work increments have a clear user-centric view. ...
  • LD@Taiga: an embedded learning dashboard for agile project management in student teams 

    Farré Tost, Carles; López Cuesta, Lidia; Oriol Hilari, Marc; Franch Gutiérrez, Javier (Springer, 2024)
    Conference lecture
    Open Access
    We present LD@Taiga, a learning dashboard seamlessly integrated into the Taiga agile project management tool. LD@Taiga provides visualizations of individual and team performance metrics, offering students valuable feedback ...
  • Evolution of Kotlin apps in terms of energy consumption: an exploratory study 

    Ahmed, Hesham; Boshchenko, Alina; Khan, Niaz Ali; Knyajev, Dmitriy; Garifollina, Dinara; Scoccia, Gian Luca; Martínez Martínez, Matías-Sebastián; Malavolta, Ivano (Institute of Electrical and Electronics Engineers (IEEE), 2023)
    Conference report
    Open Access
    Context. Java and Kotlin are the two main programming languages used to create Android applications. Kotlin almost completely replicates the capabilities offered by Java and offers extra features, making it a popular choice ...
  • On the feasibility of cross-language detection of malicious packages in npm and PyPI 

    Ladisa, Piergiorgio; Ponta, Serena Elisa; Ronzoni, Nicola; Martínez Martínez, Matías-Sebastián; Barais, Olivier (Association for Computing Machinery (ACM), 2023)
    Conference report
    Restricted access - publisher's policy
    Current software supply chains heavily rely on open-source packages hosted in public repositories. Given the popularity of ecosystems like npm and PyPI, malicious users started to spread malware by publishing open-source ...
  • The Hitchhiker's guide to malicious third-party dependencies 

    Ladisa, Piergiorgio; Sahin, Merve; Ponta, Serena Elisa; Rosa, Marco; Martínez Martínez, Matías-Sebastián; Barais, Olivier (Association for Computing Machinery (ACM), 2023)
    Conference report
    Restricted access - publisher's policy
    The increasing popularity of certain programming languages has spurred the creation of ecosystem-specific package repositories and package managers. Such repositories (e.g., npm, PyPI) serve as public databases that users ...
  • Using metrics for code smells of ML pipelines 

    Costal Costa, Dolors; Gómez Seoane, Cristina; Rey Juárez, Santiago del; Martínez Fernández, Silverio Juan (Institute of Electrical and Electronics Engineers (IEEE), 2024)
    Conference report
    Open Access
    ML pipelines, as key components of ML systems, shall be developed following quality assurance techniques. Unfortunately, it is often the case in which they present maintainability issues, due to the experimental nature of ...

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