Software Technologies

17th International Conference, ICSOFT 2022, Lisbon, Portugal, July 11¿13, 2022, Revised Selected Papers
Herausgegeben:Fill, Hans-Georg; van Sinderen, Marten; Maciaszek, Leszek A.

• Broschiertes Buch

Produktbeschreibung

This book includes extended and revised versions of a set of selected papers from the 17th International Conference on Software Technologies, ICSOFT 2022, held in Lisbon, Portugal, during July 11-13, 2022.

The 10 full papers included in this book were carefully reviewed and selected from 102 submissions. They were organized in topical sections as follows: tool assisted empirical approach to reusability models assessment; functional programming; three forms of mutant subsumption: basic, strict and broad; and on the efficiency of building large collections of software: modeling, algorithms, and experimental results.

Produktdetails

• Communications in Computer and Information Science 1859
• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 978-3-031-37230-8
• 1st ed. 2023
• Seitenzahl: 244
• Erscheinungstermin: 19. Juli 2023
• Englisch
• Abmessung: 235mm x 155mm x 14mm
• Gewicht: 376g
• ISBN-13: 9783031372308
• ISBN-10: 3031372301
• Artikelnr.: 68152025

Inhaltsangabe

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.