This chapter, authored by G.A. Papadopoulos and F. Arbab, provides an overview of coordination models and languages, which are formalisms designed to integrate heterogeneous components into a single application that can leverage parallel and distributed systems. The chapter begins by defining the fundamental concepts of coordination models and languages, classifying them into "data-driven" and "control-driven" (or "process-oriented") categories. It then delves into the main existing coordination models and languages, detailing their features and comparing them. The chapter concludes with a discussion and conclusions, highlighting the potential of these models and languages in addressing the challenges of developing complex distributed and parallel systems. The introduction sets the context by discussing the need for multilingual and heterogeneous programming in the era of massively parallel and distributed systems. It explains how coordination models and languages emerged to handle the coordination of large numbers of concurrent active entities, enhancing modularity, reusability, and interoperability. The chapter also explores the historical evolution of coordination programming and the development of various models and metaphors, such as the blackboard model and the actor model. The main body of the chapter is divided into two parts. The first part provides a historical perspective on coordination programming, while the second part describes in detail the most important coordination models and languages, including their key features and applications. The chapter concludes with a comparison and classification of the models and languages, emphasizing their differences and similarities. The chapter also discusses specific coordination models such as Linda, Bauhaus Linda, Bonita, Law-Governed Linda, Objective Linda, LAURA, Ariadne/HOPLa, and Sonia, each with its unique features and applications. These models are designed to address different aspects of coordination, from data-driven coordination to process-oriented coordination, and are tailored for various application domains, including parallel computing, system modeling, and distributed systems. Overall, the chapter aims to provide a comprehensive understanding of the state-of-the-art in coordination models and languages, highlighting their potential and the ongoing research efforts in this field.This chapter, authored by G.A. Papadopoulos and F. Arbab, provides an overview of coordination models and languages, which are formalisms designed to integrate heterogeneous components into a single application that can leverage parallel and distributed systems. The chapter begins by defining the fundamental concepts of coordination models and languages, classifying them into "data-driven" and "control-driven" (or "process-oriented") categories. It then delves into the main existing coordination models and languages, detailing their features and comparing them. The chapter concludes with a discussion and conclusions, highlighting the potential of these models and languages in addressing the challenges of developing complex distributed and parallel systems. The introduction sets the context by discussing the need for multilingual and heterogeneous programming in the era of massively parallel and distributed systems. It explains how coordination models and languages emerged to handle the coordination of large numbers of concurrent active entities, enhancing modularity, reusability, and interoperability. The chapter also explores the historical evolution of coordination programming and the development of various models and metaphors, such as the blackboard model and the actor model. The main body of the chapter is divided into two parts. The first part provides a historical perspective on coordination programming, while the second part describes in detail the most important coordination models and languages, including their key features and applications. The chapter concludes with a comparison and classification of the models and languages, emphasizing their differences and similarities. The chapter also discusses specific coordination models such as Linda, Bauhaus Linda, Bonita, Law-Governed Linda, Objective Linda, LAURA, Ariadne/HOPLa, and Sonia, each with its unique features and applications. These models are designed to address different aspects of coordination, from data-driven coordination to process-oriented coordination, and are tailored for various application domains, including parallel computing, system modeling, and distributed systems. Overall, the chapter aims to provide a comprehensive understanding of the state-of-the-art in coordination models and languages, highlighting their potential and the ongoing research efforts in this field.