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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.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.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.