data:image/png;base64,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

data:image/png;base64,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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.Abstract 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 3: Create a list that stores the necessary Coordinte Points to draw your specified shape 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 2.240,00,100-240,0240,0