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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 2.240,00,100-240,00,-100240,0