Software Engineering and Data Science / / Davide Tosi, editor.

• TeilnehmendeR: Tosi, Davide,
• Place / Publishing House: [Place of publication not identified] : : MDPI - Multidisciplinary Digital Publishing Institute,, 2023.
• Year of Publication: 2023
• Language: English
• Physical Description: 1 online resource (132 pages)

This reprint focuses on data-driven software solutions and their impact on research and development at the academic, industry, business, and government levels to exploit the hidden knowledge and big data that can be offered to cities and citizens in the future. Data-driven software solutions are different from "traditional" software development projects, as the focus of the main development core is on managing the data (e.g., data store and data quality) and designing behavioral models with the aid of artificial intelligence and machine learning techniques. To this end, new life cycles, algorithms, methods, processes, and tools are required. This reprint is centered on the recent trends and advancements in the field of engineering data-intensive software solutions to address the challenges in developing, testing, and maintaining such data-driven systems, with a focus on the application of data-driven solutions to real-life problems and techniques and algorithms addressing the different challenges of data-driven software engineering.

Table of Contents

About the Editor vii -- Editorial for the Special Issue on "Software Engineering and Data Science" 1 -- A Bayesian Analysis of the Inversion of the SARS-COV-2 Case Rate in the Countries of the 2020 European Football Championship 3 -- How Schools Affected the COVID-19 Pandemic in Italy: Data Analysis for Lombardy Region, Campania Region, and Emilia Region 19 -- Multi-Attribute Decision Making for Energy-Efficient Public Transport Network Selection in Smart Cities 31 -- Exploring the Benefits of Combining DevOps and Agile 61 -- Fast Library Recommendation in Software Dependency Graphs with Symmetric Partially Absorbing Random Walks 75 -- Ontology-Based Feature Selection: A Survey 95.