The chapter discusses the higraph, a visual formalism of topological nature, which is particularly suited for representing complex concurrent systems using statecharts. Higraphs are an extension of Euler circles and Venn diagrams, incorporating concepts like Cartesian products and hyperedges. The author emphasizes the importance of nonmetric information, such as connectedness, in higraphs, which differ from graphs and hypergraphs in their focus on structural and set-theoretical relationships. The chapter outlines the development of higraphs, starting with basic Euler circles and Venn diagrams, and then extending them to include unique contours for sets, Cartesian products, and hyperedges. These extensions allow for more complex representations of sets and their relationships, making higraphs suitable for various applications in computer science, such as entity-relationship diagrams, semantic networks, and dataflow diagrams. A key application of higraphs is in statecharts, which are used to specify the behavior of large and complex reactive systems. Statecharts extend standard state-transition diagrams by incorporating depth, orthogonality, and broadcast communication, allowing for more modular and efficient representation of system states and transitions. The chapter provides a detailed example of a digital watch using statecharts to illustrate these concepts. The author also discusses potential variations and extensions of higraphs, such as three-valued models, uncertainty handling, and richer edge interpretations. The conclusion emphasizes the potential of higraphs in representing intricate systems and the importance of combining visual and formal approaches in computer science.The chapter discusses the higraph, a visual formalism of topological nature, which is particularly suited for representing complex concurrent systems using statecharts. Higraphs are an extension of Euler circles and Venn diagrams, incorporating concepts like Cartesian products and hyperedges. The author emphasizes the importance of nonmetric information, such as connectedness, in higraphs, which differ from graphs and hypergraphs in their focus on structural and set-theoretical relationships. The chapter outlines the development of higraphs, starting with basic Euler circles and Venn diagrams, and then extending them to include unique contours for sets, Cartesian products, and hyperedges. These extensions allow for more complex representations of sets and their relationships, making higraphs suitable for various applications in computer science, such as entity-relationship diagrams, semantic networks, and dataflow diagrams. A key application of higraphs is in statecharts, which are used to specify the behavior of large and complex reactive systems. Statecharts extend standard state-transition diagrams by incorporating depth, orthogonality, and broadcast communication, allowing for more modular and efficient representation of system states and transitions. The chapter provides a detailed example of a digital watch using statecharts to illustrate these concepts. The author also discusses potential variations and extensions of higraphs, such as three-valued models, uncertainty handling, and richer edge interpretations. The conclusion emphasizes the potential of higraphs in representing intricate systems and the importance of combining visual and formal approaches in computer science.