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: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 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.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).

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