data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAKAAAAB4CAYAAAB1ovlvAAAAAXNSR0IArs4c6QAADcJJREFUeF7tnWlsFscZx+e1jW/HRzERl7nv+xSk+QCkLS2BFlJaWmgKoTGoEnwiCAkVhPiABAi+IWFMzX3fR1GFEP0S0hZKmraEO1C7CCFUBYhsY4xjt8/YM+zuu/vu7O7s7uy+z3zxsXP+57fPzDOzO5toa2trIw5DXV0dqaiocJgqftEXVy6ljaqpropf4wJqUQIBDEhpLMZUAQRQEhhgDaklXJdoz3Fdx8Bi+DvRcZmNO/C3dgwyXuf5SqqnatmYAvjw4UNy69YtAqNzIpFI+tnQ0EAKCgosr1ul8/v/2dnZZMiQIaR79+6+6MxgMUIDhVmCYgTSpmZGAH1piEKZJgF4+fJl0r9/f4Wq6Lwqly5dIosXL3aeUCCFGXw6AG0soLEILXDavNnvaWUBHzx4QDIzM7lla21tJQsWLCAHDhwgGRkZBP5mFhH+9tuiecm/V69etK6ygxWAsstJl/x0FvD8+fNk+PDhtO0wzI4YMYJMmjSJTJs2jcydO5eMHTuW9OjRg6xdu5ZUVlbSDgZoVQxQ/2HDhqlYNayTRgEdgGfPnqXQMcvTp08f8uTJE9LY2EiKiopIeXk5XX6BZRiYJ8J1+OnFUpnNMWXkB3VmNxP2uLoKJAEYl05DANWFTlszHYBnzpyhVoNaoNYWkn92JSHyp1G+KJPz5Avy9dI/8TlqU1MTWkBflJabaRKAbN7U+Py/pKC0XG5pPub29o6p5EnlZV7Cy5cv6XQCg9oK6AA8ffo0GTp0KK1x0zdfcwDnz59PnY9NmzYJtebGjRtSrA+Ue+3aNXLv3j3bcgHAx7+5xOO9evUKAbRVLfwIQgDu2LGDDstLl7bvfaYKsI4Icd977z27qLbXvQAIQ/DIkSNty8AI4SqgA/DkyZN06QIAaq5/zi3ggAEDhKwQNKWqqoqCCk5Afn6+p9bBGuTVq1eFygYL+Oiji3wO2NzcjAB6Uj+YxEkAsiFYC2AwVfFWCgOQ5YIAetMzqNQ6AE+cOEH3UiG0NH5j6oSUlpYGVTdH5WRvHE3qFv6Rp3n9+jUZNWqUozwwcvAKOAawX79+Umr54sULUlxcLC2vzA0jEEApagabiQ7A48ePk8GDB9MatDbVcwsIDyfcv3+f/t8KwOvXr5Nx48bROPCkzIQJE0hJSQkBz9osiAC4ceNG6pXPmjUrpSqQFwD47w8v8HgtLS1k9OjRwaqJpTlWQAfgsWPH+BCsBVC7rJLKAgIwN2/eJHv37iXLli2jSzerVq1yDeDy5cvJ6tWrSdeuXYUAfPirP/AHEBBAxyyEkkAH4NGjR7kFJM2NpnNAlYfgBwvOcxHhyR20gKEw5ajQWAH41fxz3AIigI44CC2yDsAjR46QQYMG0cpktDRFzgLe/+VZLiSsZY4ZMyY0YbFgMQV0AB4+fJgOwdB5md++ihyA935xhi9EQ/MRQDEIwoyVBODAgQNpfbJam3UAPn36lHTp0sXSC2aNcOI4pFqGmT17NunZsyd1QjZs2GDr0IAXfHee3uOGB2gxqK2ADsBDhw7xIVgLIIMPmmLnhDhZOrEDcPLkyXQZZuvWrXRJ59SpU5YeNQB45+endI/hI4Bqwwe10wF48OBBwixgNmmJ3BB8+2cnueLwzgoCGAEAa2tr+ckIFy9epEsXMAfMSXwbua24W3NP8Dngs2fP3iwpqd8PaVtDnQWEt9/gyRcIuRmtkbOAN396XGcBx48f70vHXrjQvuMyY8YM+tP4ty+FxjRTHYD79++nQzBYwLzMNkdbcaDPlClTyIoVK+jWWX19PX2RyeroGZGtOMgDHg+rra1NKT/bivvyg2PcAsLrpbIBhDcBq6uraV0++5SQd95NrpY2TkyZkdqsJADZS+n5WUT3RDTMD0WckHPnztF4U6dOJYWFhUS7R6ytuQiATjxqcEJuzDnKi8jKypICILx2Cs4P3FgAHQtm8Gnbt2XLFjJnzhzSt29fqR0Wt8x0AO7bt4+filDQKeHYAsIrlvDaJlisMCzgv2Yf4f3TqVMnTwBaAWRl+azA0AIcN3hktEcHIDxEwCxgYXZG5OaA//zJYR2A8ESO07BkyRICryCwwKweWDzt707zhfjGvN3kEbc0pgDCvK0oJzNyXvA/fnyIzwHhoCJRAEWcCKeWLxUoIuXFDTSr9ugA3LNnD19ofis3K3IW8ItZ7fNUCADgxIkTU/ajCg6DCnUIE3YdgLt37+YAFud14gCuXLmSbN68mdYzqJ0QcGbAkblz5w55/PgxmTlzJp9XGgVjXvDfZx7gl3JyckwBVHVOlq5OSxKAzGsryc/WvRUHniCcmmAHoBPP1Worjp3EBY4MhG3bttEHWwHEbt26Jd2wDMDP39/Pr+Xm5uoAjEoHq3qD+GUldQDu2rWLLxuUFuS4HoLZ4UKpKi2yDAPpjQcVmeXJALw+Yx+/nJeXRwGM8sQ/ynUXBVYHYE1NDQewrDDXNYAihYsCKJoXrAP+7Ud7eXQ4TQHmV3EIcXZakgCEI9cgfKcoL3IAXvvhHp0FhLMN4xbi5rToANy5cye3gJ3fyo8MgABZ/aoKcnX6bh2A8DhXXENU5rR2+icByCxgeXGB6dEcdk4IFMgeJg3qrThYQP/gy9+Rv/5gF28vHAsSZwBZQ6PutCQB2Lt3b9q2LiWFOgvIznqxAhA8Vtj7BacB9kCfP38eyHvB8B7LvHnzqAX8y/drOIDwbnI6AKi1MFEcnpPOhoEnWCC8XVqk/BDM4GMW8M/f+z3vD9iTZi9Y2Q0DcbseJadFByBYLTiNCqxY5+J8UlKevOamwtkwZWVlBHZtFi5cyH+CBbwyrZpvxU2fPj1uXLlqj+pWUQcgtHD79u308HEIEyaMJ2WlZa4aHnSi/zx6RE9lgACPYsk4nzDoNvhZnqpOSxKATIRU3zD042OFsgTy49sgfoIRdN6qOS2WAKYSRiaAqg8RQQMSZHkqaB8KgFGaJAcJRFhlhdkfgQKowh0XVidHpdyg+8h3AFWbc0QFhLDrKWtObtcO3wAMqgF2DcTr3hTw24BIBzBoE+5NXkztRAE/+lYKgGFOYp0IiHHlKCCzvz0BmA4PTMrpsvjm4pUBDqDol7lhTgBHeKxZs0ZYVdG8hTNUMKLXNnpN74ckTuokOuc35kkB1P0TPjm/7v/nFbGfHS3TFaC9pvmdfU083T49b6kfaAdaaoJWI/h3m/6yHxy5ylOECZqxgYUHv/6KniTxyScraNvsWLAGsKPaSRNPKFArrAmAZoI7uZtcKRZiItPOMnZOR/3MOiTEqlsWbdkmbQobFj7++M1ZOpCMtV2bt+kc0G6SadyKizNcsuCw08juuqx6+J0Pawc8N7p+/XoC3/tLxZMOQNEJpcy9YL8FwfzDUwAeTGbh7t279KNFV65cIYsWLeL/T3y46KO2UcOH0dOfRAMC2K4U3O0QaqqrRKVLu3haCFnj4dSKhoYGAgchIIAekEAA7cUzAxBSwcckKYDgBbNsUg7Bn3e8cTZ2EQnVAmrqYd/8mMcALca+Gc4Cby0r36IeWviAGfgMyO3bt3Xf/hN3QjSF1XWeRs8BDC2ELXxoDdcUHLYG2vJN6gJHqMB5Qjon5Or7yctSWgtopitdhvntd9vvtI6CAreA2juNVTLMOz9sAFWBz6YepnvHhqUb6604g3nVLkQHDiDr8LCFDxM8m+EukKpppz8WUyHbp2eEAYQWmXS4m6041+LgfM+1dL4ltOgToa04w+4a1DH1wwgWFodZQNF1Q89ipLPlU836G/rCKwPJAAp0tnEItts5cQWgQD1c5YuJPCsgs789PY5l6bR0fEvDc0sxA6UUUPaBVDOVhOYESsmLlTFTwNap8CibdAtorI/fDfDYfkxuoUBQBsR3ALXt8zphRVr8VyDoPgoUQCafzEms/10S/xLC7I9QANR2qR8T2/gjI6eFKmgfOoBMyqDmHHK6Lrq5qDYnVwZA1qWqCRRd1PQ1V/UGVw5AHJ7lIq/CMJuqRUoDiE6LOxjDdCqc1jgSAKJVFOtW1a2dWSsiByA6LfpujPqcObIAprvToqpTIWar38SKPIDpNjxHcZiNvBPi9K6K0iRcpG1xa4+2zbGygGadGfTepghQonGiXHfRNsYewKg5LVF3KkTBY/HSBkDVnZa4OBUIoAMFVJjQq1AHB5JJj5p2FtBMwaAn+UGXJ50aiRkigAYx/Zz4+5m3RCYCzQoBtJBb1pws3ZwKp/QigDaKuQVIFsBOOzRq8RFABz0m4jCIxHFQZOyjIoAuutjoRKBT4ULEjiQIoHvtMKUEBRBAFyJ+9ml7onfedZEYk+gUQABdAgEQIoAuxdMkQwAFNWTAMeuHFlBQOJtoCKBDHdHyORQMAfQmGM73vOlnlxotoJ1CHdfR8gkK5TAaAphCMITOIU0uoiOALkTDJPIUQADlaYk5uVAAAXQhGiaRpwACKE9LzMmFAgigC9EwiTwFEEB5WmJOLhRAAF2IhknkKYAAytMSc3KhAALoQjRMIk8BBFCelpiTCwUQQBeiYRJ5CiCA8rTEnFwogAC6EA2TyFMAAZSnJebkQgEE0IVoZkkWVy4lNdVVhBg+SW/8O5FoT93WZl0wxGHX2e88f0n1VSUbBFBST1gCYgDSCYBaECVVU7lsEEBJXSJqAUWLEwFVNC+V4yGAKveOpm44BGvEqKurIxUVFRHpOv+qCVBAoHM/DK4U+B+Zx6VOatbHGAAAAABJRU5ErkJggg==

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