data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAKAAAAB4CAYAAAB1ovlvAAAAAXNSR0IArs4c6QAADX1JREFUeF7tnXdsF8kVx9/P2BgwNgZMIAKs0MQfiQDRBOgQhJIQyhFCD1wwF5mj915NEyB6L9YBSSgJ9UgIJaKLEEKHVCBAsFAUpAgBuRDg7nDy1p5lZ3+//e1sn/393vzjslPefOezb+btzu5GiouLi8FiKioqgtzcXIulEi/7x/mfKJ3aXrg18TrnU48iBKBPSlMzMRUgAF0CA72h4gkLIiU1FpROLLq/I6WH2byDf2vnIP1xtV6X7JStmpgA3rhxAy5cuAA4O0cikVD9bNeuHTRt2tQTnRksemiwMUNQ9ECaWKYH0JOOSFRpFIBnzpyB+vXrS2SidVPu378PHTt2tF5QoEQs+DgATTygvgktcNq62e9J5QHR81WtWpXzeAhk586d4d27d6HyhM+ePfPEExoBKMAuZYmhAOcBV65cCb1791ayvXz5Etq2bQurV6+Gnj17wqVLl2D06NEwb9486NGjB8yZMwdOnDgB58+fV8CULR08eBAmTZokm1lkj04BDsDly5dDnz59VE+Hl1rwkktKSgpkZWVBZmYm4MB26dIFXrx4ATVr1lSOy7hWRDunTJlCAy65AlEAMg8oud2m5hGAphJJkYEDcNmyZaoHLJdWBt5e/BTSUkqvG0hhrrER5a7thBcjzqpROwI4bdo0ya0m86IAZB7w1Yt/QUZ2tdAoVH3bt+Gf+WdUewnAcAwdB+CSJUvUIOT1v5+pAHbr1g2GDBkC/fr1E+pVo0aN4M6dO0J542W6d+8ezJ8/H3bv3m1aFwL4jx+f4gCcMWOGaTnKEKwCQgCiiW/evIH09HRfrSUAfZU7kMY4ABcvXqyuAd/+57nqAYcOHQo7duwQMhCncJz+CgsLIT8/X6iMUSYEsKCgAPbs2WNaD3rAJ0N/w60BZ82aZVqOMgSrAAfgokWLFAAxaQEM1kSx1hmALDeeBASgmHZB5uIAXLhwoboG/PK/L2MGIVWqVAnSXsO205Y2hqIhJ7g1IF4spyS3ApYBrFevnpQ9+nxaLgEo5cjEN4oDECNOdhnm3ZvPVQ+4atUqmDhxolKTEYAnT56EZs2aQU5ODnTq1Em5C9G4cWOoUaOGbVmwTtE6EMC/f3SM84B425CS3AoIAbhx40YYNWpUXADx4M2bN+H48ePKfeS0tDTAKd1JwilUtA4E8NHgXytBCCZcAxKATtT3pywHIA6Yeivui1cx14AyT8EPBx3lPCB6dEpyK5BQAD744a84D0gAyg0fWscBiFMe84ApX70OnQf828Bfch5QdPqWf5gS10IOwNmzZ6sXosu8exM6AO8POKJeiD506JDw+jFxh1f+nnEA4oVb5gFTi9/aAhAhxgvaTtOWLVvgyZMnSl0idWIQcq//Z5wHxDs7lORWgANw5syZqgdMgy9UABGEWrVqmUbBmOH06dPQsGFDNb/d7iOADRo0UOq6e/euaZ0I4N1+hzkPSADaVd+/chyAuHuEecCykS9teUD/TOdbQgD/2vcQ5wFxdw8luRWIPH78WH2gY9OmTaoHTE/5KiaAlStXlrJHZZc1gb/0Och5wBEjRkhpKxn1XgHOA+IOYuYBy5UphozsnCitZL4O+OfeBzgPiDu8vUjHjpXccenatavyU/+3F20map0cgFOnTlU9YPlUUAHMy8uDnTt3mq4BcdtW9+7dFYiPHj0Kp06dgv79+0Pr1q1t6YcPO7Vv31558s4s4RT8px/s5zyg2wDi9jLcZobp0kWANh9EWzVs2DDYtm2bmbl0vFQBDkC8f8s8YIW0iArgwIEDYe/evaYAYoarV68CgsweiVyzZo0Cop00cuRIwGWBSEIA/9hrH+cB8Sk/p+nhw4dw+PBhpT8IHUux4NO2hY+49urVC+rWrevUhIQuzwE4efJkFcCMsikqgIMHD4Zdu3aZAli7dm1ls8K5c+cUD4g/BwwYAM2bN7clInrADh06wNmzZ03LI4B/+P4vOABXrFhhWs4ogxFARp7PqB4twLaNSeCCHIB4ljMPWDG9TOjWgHd6/pwDECGymvRTKPN66PG0v1utF/PT9BytGgcgbrliD6ZnlkuNCaDMG1Jvf7iX25KP28hEkkgQYdXzxWtXpD0RuxMhDwfghAkTVA+YVT4tdB7wVo/3z47gdix8rUi8pA0qghrMZPeKHIDjx49XAaxUoawK4IIFC2Du3Lmma0DMYGUTabxBx/2HuA8RHwfFRzzZo5645zBWwjXgze7vH99EADEA0idZ12TJGrRwAI4bN04FMDsj3ZYHtLKJ1AjAVq1aweXLl5XDGPwgSHhy4M9r164ZAni968+47Vhr165V84ZlgGU9QbyaITgAx44dqwJYuWI5WwB6ZahZvegBEUCW0AOuW7cu1Av/ZJieOQDHjBmjAlgls3zoALz2vZ9yAK5fv96M21AcT+SghQMQ3//HLsNUzaoQOgCvdvkJB+CGDRtCAZgVIxPNK3IA4p0H9mB6TqWM0AF45bsltwsx4RSMQUyiprCsac30jwKQecBq2RVVALWXK+JtRnjw4IFyJ2T69OmQmprqeGOqyEZU7CC2N7t4D/z+O+9fH4IAit7GMxNJ5uNhD1o4AHH7EgPwa5UzOQ/I3oJqBODz588hOzsbcFPrgQMHYPPmzaabSM0GVmRzK8K3dOlSwCDkcuftnAdEG5IphXF6jno5UcuWLZUxq14lS/opmMHHPODvOn2q8nblypWkfTdMmIIWDsCnT5/C7du3lXc+V6uUAZWqfT3KgeCtOPZScu03RDCj9l3RXnoe9LRa+NADvprxDfhth0L1VlyTJk2gevXqXpoRirpl94ocgKgoPotRp04dRdwWLVqArPd+9aOPJ8+tW7eUfz969AiGDx8eCkD8MlLWoCUKQBFBvPhYoawCiegRpjyyBS2BAyj7FBEmuKzaKoP2gQAYpkWy1UENY/4gx8NXAGXY/hRGQPy02W+v6DmAsq05/BzMMLfl15rcMwD96kCYBzkMtnvtQFwH0G8XHoZBTBQbvRhbVwAMchGbKIMbpn64Od6OAPTijAjTQJCtzp/0UwEU/TI3rgnw01lWPoEgWneYB9RpH52W90I7KzaJrvn1dSoAcv/ET84X/P99Rexnac+4BrTHNL+zr4kn26fnDfVD7VBLTdJqhP+W8FvfirUiTCgZdSw8/NED5U0SkydPUvpmxoIxgKWiRU2z2KBW2BgAxhLcytnkxdnsZZ0xB0s/OKUGxBoQL22zW7dhn7QVmrCQn8+/J4f1XVt3zDWg2SJTfy84keGyO4D6cmYamR13yw6v62H9wNex4HPmgwYNivv2MA5A0aDCi80IXgtD9fuvAL6ciSWMHfbv369s9+vbt6/6/8hHeUOLG3/rm+rbrETMJABLVMKzHdP2wq0isiVlHi2ETICUlBR4/fo1fHbkCBCADrAgAM3FMwIQvz+NwYr4FHyj9ImzpnkQqAfU2GHe/QTPgVo0zQuuk6x9Azu08OEm4X379sH169cB3zfJkngQommsKKcD5ObmBt/x4CwIvmVZ4EMlYtgSMwi50i36shReB4ynphKYDG9TcqaVNuS7B9SeaczYIM/8oPGTBT4TO2Juv9NdujG+Fadzr9oL0b4DyAY8aOGDBM9kuvPFNO3yx2ApZLp7RhhAA9dq51acbXFovWdbOs8KGoyJ0K043d01tDH+ZgQDj8M8oOh1Q8diJLPnk83768bCKQPRAAoMtn4KNrtzYgtAATts1UuFHCvg5ng72o4VqydOzwjH6lAFningxTM9rgPIei+0JvBMKqrYLQVMgwqHDXkGILPL6w447D8VN1DALwfiOYDa/tH0LD/vfo+RrwAy+d1cxMo/pPJbGOR4BAIgeUU5oPQiqLDas8ABpKDF6pA5yy/bmlwaAClocQaWWWm/ggozO/THpQOQpmerQxg/v99BhVXrpQaQgharw1mSP8igwqrFoQCQvKLYsMoQVIhZ+j5X6ACkoIUfYtmCiqQBMNmDFlmDiqQDMNmmZ9mDiqQGMFGDljAFFQSgToEwe4ww2y4KYmiDENEOhi1oCXtQYXVckgZA2YOWRAkqCEALCsgwxclggwXJXM+adB4wloJ+L/L9bs91alyskAD0MWhJdm8Xi1sC0OBsdmtNlmxBhVXnSACaKGYXILcAtjqgYctPAFoYMZEpVCSPhSYTPisBaGOI9UEEBRU2RCwtQgDa145KuqAAAWhDxEsXSwq1+cBGYSrCKUAA2gQCISQAbYqnKUYACmrIgGPejzygoHAm2QhAizqS57MoGAHoTDBa7znTz6w0eUAzhUqPk+cTFMpiNgIwjmAEnUWabGQnAG2IRkXcU4AAdE9LqsmGAgSgDdGoiHsKEIDuaUk12VCAALQhGhVxTwEC0D0tqSYbChCANkSjIu4pQAC6pyXVZEMBAtCGaFTEPQUIQPe0pJpsKEAA2hCNirinAAHonpZUkw0FCEAbolER9xQgAN3TkmqyoQABaEO0WEU+zv8EthduBdB9kl7/dyRSUrq42LhhzMOOs9/V+l2yV5ZqCECXRsIQEB2QVgDUguiSmdJVQwC6NCSiHlC0ORFQReuSOR8BKPPoaGyjKVgjRlFREeTm5oZk6LwzE6HApKz9KNlS4H8E8nWqU/F8XwAAAABJRU5ErkJggg==

data:image/png;base64,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 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 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 3: Create a list that stores the necessary Coordinte Points to draw your specified shape 240,00,100-240,00,-100240,0