Software Technologies

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

AvHans-Georg Fill,Marten van Sinderen

Häftad, Engelska, 2023

Del 1859 i serien Communications in Computer and Information Science

892 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Beskrivning

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.

Produktinformation

Utgivningsdatum:2023-07-19
Mått:155 x 235 x 14 mm
Vikt:376 g
Format:Häftad
Språk:Engelska
Serie:Communications in Computer and Information Science
Antal sidor:231
Förlag:Springer International Publishing AG
ISBN:9783031372308

Utforska kategorier

Systemvetenskap och AI inom Data och IT
Programvaruutveckling inom Data och IT

Innehållsförteckning

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.