Data structures

Data structures

1. STATIC: size is fixed when the structure is created and cannot be changed. e.g arrays

   • ADVANTAGE: easier to program because there is no need to check on the data structure at any point.
   • DISADVANTAGE: inefficient use of memory has been set aside even when the program is not being executed

2. DYNAMIC: size is variable, will inevitably change during processing. e.g lists

   • ADVANTAGE: uses up as much space in memory as it needs to, e.g adding information to lists
   • DISADVANTAGE: the structure could overflow if it exceeds the limit or underflow if it is empty

3. ARRAY: stores multiple items of the same data type under a shared common name.

   • One dimensional: has one index. Two dimensional: 2 axis- like a timetable. Three dimensional: height, width and depth-like a 2 week timetable
   • LIMITATIONS
     • Must have the same data type- can have integers or strings but not both.
     • Arrays have a static data type, which means that items cannot change in size once they have been declared.

4. Tuples: are immutable lists. This means that they cannot be edited (cannot change contents once created).

   • Lists: are mutable. This means that they can be edited-you can add and delete items from lists.

5. Stacks: LIFO- last in first out. Data can be pushed into the stack or popped out of the stack. An example of this is a pile of books.

   • Stack uses: storing return addresses, passing parameters

6. Queues: FIFO-first in first out. An example is a shopping queue- customers get pushed to the back and popped at the front.

   • Uses: job queue in batch processing

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