Linda is a parallel programming model based on tuple space, which allows processes to communicate and coordinate by placing data in a shared space. Unlike traditional message-passing or object-oriented models, Linda focuses on data creation and sharing rather than process control. It enables processes to create and share data objects (tuples) without needing to know about each other, making it highly flexible and efficient for parallel programming. Linda has been implemented in various languages and environments, including C, Fortran, C++, and Scheme, and runs on a wide range of parallel machines. It has been used for applications such as matrix multiplication, DNA sequence comparison, and parallel database search. Linda's model is simple, elegant, and powerful, and it has been shown to be effective for both coarse-grained and fine-grained parallelism. While it is not widely adopted in research, it has been used in practical applications, including ray-tracing displays and parameter sensitivity analysis. Linda's approach to parallel programming is distinct from concurrent object-oriented, logic, and functional programming models, and it offers a more flexible and efficient alternative for certain types of parallel tasks. The model is based on generative communication, where processes create data objects (tuples) and share them in a shared space, allowing for efficient coordination and data sharing. Linda's simplicity and flexibility make it a valuable tool for parallel programming, and it has the potential to be widely adopted in the future.Linda is a parallel programming model based on tuple space, which allows processes to communicate and coordinate by placing data in a shared space. Unlike traditional message-passing or object-oriented models, Linda focuses on data creation and sharing rather than process control. It enables processes to create and share data objects (tuples) without needing to know about each other, making it highly flexible and efficient for parallel programming. Linda has been implemented in various languages and environments, including C, Fortran, C++, and Scheme, and runs on a wide range of parallel machines. It has been used for applications such as matrix multiplication, DNA sequence comparison, and parallel database search. Linda's model is simple, elegant, and powerful, and it has been shown to be effective for both coarse-grained and fine-grained parallelism. While it is not widely adopted in research, it has been used in practical applications, including ray-tracing displays and parameter sensitivity analysis. Linda's approach to parallel programming is distinct from concurrent object-oriented, logic, and functional programming models, and it offers a more flexible and efficient alternative for certain types of parallel tasks. The model is based on generative communication, where processes create data objects (tuples) and share them in a shared space, allowing for efficient coordination and data sharing. Linda's simplicity and flexibility make it a valuable tool for parallel programming, and it has the potential to be widely adopted in the future.