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.Step 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.Lists and Numbers are examples of Primitive Data Types

240,0240,100-240,00,-100240,0