👉 Markers computing, also known as marker-based computation, is a computational paradigm where data is processed through a series of markers or flags that indicate the presence, absence, or value of specific data elements. These markers can represent various types of information, such as boolean values (true/false), numerical indicators, or categorical labels. In this approach, operations are performed by manipulating these markers rather than directly processing the underlying data, which can simplify complex computations and enhance efficiency. For instance, in a scenario where you need to filter a list of items based on certain criteria, markers can be used to denote whether each item meets the condition. This method is particularly useful in scenarios involving large datasets or when dealing with probabilistic or uncertain data, as it allows for flexible and scalable computation without the need for complex arithmetic operations. Markers computing can be implemented in various programming languages and frameworks, making it a versatile tool for a wide range of computational tasks.
