data:image/png;base64,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 Data Types (ADT) is a custom data type created by the programmer to provide meaning to the data in your program. It is not built into the programming language. ADT are created with custom constructor and selector functions (blocks). ADT are a form of abstraction because they make are program easier to understand, read, and debug.Lists and Numbers are examples of Primitive Data TypesStep 1: Create A Reporter block (the constructor) that will take two numbers as the domain (x and y coordinates) and output a list as the range.Step 2: Create two report blocks (the selectors) that will take the list created by the contructor block as the domain and output a single number as the range (one the x coordinate the second block the y coordinate).Step 4: Create a Draw Shape Command Block whose domain will be the list of Coordinate Points create in step 3. The command block will draw the shape on the screen by using a the for each item block and the selector blocks created in Step 2.The list of numbers is confusing because it is not obvious which numbers are x and which are y coordinates. It will also be difficult to maintain (add or delete coordinates to the lists). It would be better to create a matrix (a list of list). Each item in the list will be a list of x and y coordinates.Step 3: Create a list that stores the necessary Coordinte Points to draw your specified shape 240,00,100-240,00,-100240,0