Software Technologies: 17th International Conference, ICSOFT 2022, Lisbon, Portugal, July 11–13, 2022, Revised Selected Papers

Author:   Hans-Georg Fill ,  Marten van Sinderen ,  Leszek A. Maciaszek
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2023
Volume:   1859
ISBN:  

9783031372308


Pages:   231
Publication Date:   19 July 2023
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Software Technologies: 17th International Conference, ICSOFT 2022, Lisbon, Portugal, July 11–13, 2022, Revised Selected Papers


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Author:   Hans-Georg Fill ,  Marten van Sinderen ,  Leszek A. Maciaszek
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2023
Volume:   1859
Weight:   0.379kg
ISBN:  

9783031372308


ISBN 10:   3031372301
Pages:   231
Publication Date:   19 July 2023
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Tool Assisted Empirical Approach to Reusability Models Assessment.- Microservices Deployment on a Multi-platform Ecosystem: A Contract-based Approach.- A Decision Model based on an Optimized Choquet Integral: Multifactor Prediction and Intelligent Agriculture Application.-A New Simulation Tool for Sensor Networks based on an Energy-efficient and Fault-tolerant Methodology.- Adapting Cyber-Risk Assessment for the Planning of Cyber-Physical Smart Grids based on Industrial Needs.- Three Forms of Mutant Subsumption: Basic, Strict and Broad.- On the Efficiency of Building Large Collections of Software: Modeling, Algorithms, and Experimental Results.- An AST-based Code Change Representation and Its Performance in Just-in-time Vulnerability Prediction.- Towards Extracting Reusable and Maintainable Code Snippets.- A deep learning architecture based on advanced textual language models for detecting disease through its symptoms associated with a reinforcement learning algorithm.

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