Moved Big O notation.

plan.txt

@@ -114,11 +114,17 @@ Then test it out on a computer to make sure it's not buggy from syntax.
 
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+Algorithmic complexity
+    - nothing to implement
+    - math explanation: https://www.youtube.com/watch?v=ei-A_wy5Yxw&index=2&list=PL1BaGV1cIH4UhkL8a9bJGG356covJ76qN
+    - https://www.youtube.com/watch?v=V6mKVRU1evU
+    - http://discrete.gr/complexity/
+    - http://bigocheatsheet.com/
 arrays
-    No need to spend a whole day on this.
     * - Description:
-        - https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays
-        - https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays
+        - Arrays: https://www.coursera.org/learn/data-structures/lecture/OsBSF/arrays
+        - Dynamic Arrays: https://www.coursera.org/learn/data-structures/lecture/EwbnV/dynamic-arrays
+        - Resizing arrays: https://class.coursera.org/algs4partI-010/lecture/19
     - Implement:
         * - Practice coding using arrays and pointers, and pointer math to jump to an index instead of using indexing.
         * - new raw data array with allocated memory (can allocate int array under the hood, just not use its features)
@@ -126,13 +132,15 @@ arrays
         * - capacity() - number of items it can hold
         * - is_empty()
         - at(index) - returns item at given index
-        - cannot append or move if full - will not tackle allocating and copying to new memory
-        - append(item)
+        - append(item) - or push(item)
         - insert(index, item)
         - prepend(item) - can use insert above at index 0
         - delete(index)
         - remove(item)
         - find(item)
+        - resize(new_capacity) // private function
+            - when you reach capacity, resize to double the size
+            - when popping an item, if size is 1/4 of capacity, resize to half
     - Time
         - O(1) to add/remove at end (amortized for allocations for more space), index, or update
         - O(n) to insert/remove elsewhere
@@ -260,9 +268,6 @@ Other data structures:
     - Know what NP-complete means.
 Recursion
     -  when it is appropriate to use it
-Algorithmic complexity
-    - http://discrete.gr/complexity/
-    - http://bigocheatsheet.com/
 open-ended problems
     - manipulate strings
     - manipulate patterns