An Introduction to Programming Languages

This book presents a unique comparative framework that teaches programming through parallel exposure to multiple languages. Rather than focusing on a single syntax, this book reveals the universal principles underlying modern software development by examining mirrored implementations across thirteen programming environments, including C++, C#, Java, JavaScript, Python, PHP, Ruby, Visual Basic, VBA, Rust, Go, Ada, and Perl. This Second Edition expands the comparative model with new chapters on runtime behavior, memory models, concurrency, error handling, security, browser environments, and programming in the age of artificial intelligence. Through carefully structured examples and conceptual discussions, the author connects the evolution of computing with the practical realities of modern software engineering. Designed for students, researchers, engineers, and educators, the book develops cross-language competence, conceptual clarity, and adaptability to rapidly evolving technological environments.

Includes historical and philosophical foundations of computing and software development Provides practical experiments and implementation-focused explanations Establishes a rigorous foundation for programming across scientific, industrial, and educational domains

Autorentext

Paul A. Gagniuc, PhD, is an Associate Professor of Bioinformatics and a Professor of Programming Languages at University Politehnica of Bucharest in Romania. He obtained his doctorate in Genetics at the University of Bucharest. Dr. Gagniuc is also an Academic Editor at PLoS ONE and a proactive reviewer for several well-known scientific journals. He has published numerous high-profile scientific articles and is the recipient of several awards for exceptional scientific results.

Inhalt

Historical Notes.- Philosophy and Discussions.- Paradigms and Concepts.- Operators and Expressions.- Data Types and Statements.- Variables & Immutability.- Control Structures.- Concurrency Models.- Tooling, Testing & CI.- Functions & Modularization.- Data Pipelines & AIReady Workflows.- Implementations and Experiments.- Capstone Project & Further Resources.