data:image/png;base64,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KBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECByxcQFpoRMBzwAAAABJRU5ErkJggg==You finished. Good Job!variable,sequencing,condition,debug,selection,procedure,abstraction,algorithminput2