Buch, Englisch, 231 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 376 g
17th International Conference, ICSOFT 2022, Lisbon, Portugal, July 11-13, 2022, Revised Selected Papers
Buch, Englisch, 231 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 376 g
Reihe: Communications in Computer and Information Science
ISBN: 978-3-031-37230-8
Verlag: Springer Nature Switzerland
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.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Mathematik | Informatik EDV | Informatik Angewandte Informatik
- Mathematik | Informatik EDV | Informatik Technische Informatik Hardware: Grundlagen und Allgemeines
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmierung: Methoden und Allgemeines
- Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
- Mathematik | Informatik EDV | Informatik Informatik Rechnerarchitektur
Weitere Infos & Material
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.