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  • Product-focused software process improvement = 24th International Conference, PROFES 2023, Dornbirn, Austria, December 10-13, 2023 : proceedings.. Part II /
  • Record Type: Electronic resources : Monograph/item
    Title/Author: Product-focused software process improvement/ edited by Regine Kadgien ... [et al.].
    Reminder of title: 24th International Conference, PROFES 2023, Dornbirn, Austria, December 10-13, 2023 : proceedings.
    remainder title: PROFES 2023
    other author: Kadgien, Regine.
    corporate name: PROFES (Conference)
    Published: Cham :Springer Nature Switzerland : : 2024.,
    Description: xvi, 155 p. :ill. (some col.), digital ;24 cm.
    [NT 15003449]: Poster -- Metrics for Code Smells of ML Pipelines -- Tutorial -- Declarative Process Mining for Software Processes: the RuM toolkit and the Declare4Py Python library -- 2nd Workshop on Computational Intelligence and Software Engineering (CISE 2023) -- MaREA: Multi-class Random Forest for Automotive Intrusion Detection -- Forecasting The Developer's Impact in Managing the Technical Debt -- Development of a Desktop Application to Enable Doctors to Remotely Monitor Patients' Hematological Parameters -- The significance of classical simulations in the adoption of quantum technologies for software development -- Enhancing Bug-Fixing Time Prediction with LSTM-Based Approach -- Enhancing Code Obfuscation Techniques: Exploring the Impact of Artificial Intelligence on Malware Detection -- A perspective on the interplay between 5G and quantum computing for secure algorithm -- Speech Therapy supported by AI and smart assistants -- 2nd Workshop on Engineering Processes and Practices for Quantum Software (PPQS' 23) -- Integration of Classical and Quantum Services Using an Enterprise Service Bus -- Problem decomposition to leverage quantum computing for optimization problems -- Quantum Algorithm Cards: Streamlining the development of hybrid classical-quantum applications -- Doctoral Symposium -- Simulation-Based Safety Testing of Automated Driving Systems -- Utilization of Machine Learning for the detection of self-admitted vulnerabilities -- Closing the Loop: Towards a Complete Metamorphic Testing Pipeline.
    Contained By: Springer Nature eBook
    Subject: Software engineering - Congresses. -
    Online resource: https://doi.org/10.1007/978-3-031-49269-3
    ISBN: 9783031492693
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