This document discusses various data structures and their properties. It covers arrays, linked lists, stacks, queues, hash tables, sets, binary search trees, and heaps. Arrays allow direct indexing but are less efficient for inserting and deleting in the middle. Linked lists are more efficient for inserting and deleting but lack direct access. Stacks and queues are designed for LIFO and FIFO respectively. Hash tables provide fast insertion, deletion, and access but don't maintain order. Sets avoid duplicates and only allow membership checks. Binary search trees maintain sorted order and provide fast access, insertion, and deletion. Heaps are efficient for priority queues. The best data structure depends on the specific access, insertion, deletion and search needs of

1. DATA STRUCTURES - CAN THEY BE SERVED A LA CARTE?
Data structures often neglected.
Pseudo code should be used to help modularize
Impose systematic organization
!A record - group contains values (-tuple)
A record has fields - not just rows and columns
grouped collection
!data structure - C style “struct”.Very basic, though in Objective C, C++, C# etc.
not Java, Python, Ruby sort of
is it a class? struct simpler, no methods. just a package of variables
pointers
C is not oo
plain old data structures PODs
!point on screen
struct Point {
int x;
int y;
};
or color
struct Color {
rgb etc
};
!COLLECTIONS
!The Array - very fundamental (python its “list”)
An array ordered collection of items given a name, has index
Linear array. usually 0-based index. fixed size - immutable
dynamically add or remove items
data types. restrict size and type is smaller and faster. memory is allocated.
don’t keep your options open! Flexibility introduces overhead.
!One dimensional array
Multidimensional array - matrix or table - two dim is array of arrays,
rectangular array
three dim - [ 1, 3, 11 ] an array of array of array. nesting information.
not dimensions in the physical world, more like a phone bill
!Jagged Arrays of different lengths,
Resizable Arrays, mutable, like Java ArrayList, NSArray in Obj C, NSMutableArray
location? myArray.add(99) or myArray.add(99.2) reshuffled around
!Java
add(value)
Obj
addObject:value
JS
push(value)
Ruby
push(value)
Python
append(value) - append to list
!Insert at index
Java
add(index, value)
Obj
addObject:value atIndex:index
JS
splice(….)
Ruby
insert(index, value)
Python
insert(index, value)
!push, pop (delete last), etc
!FIVE Fundamental
1. How to ACCESS
2. INSERT
I Can dothis.
right?

2. 3. DELETE
4. FIND
5. SORT
!Sorting
myArray.sort(); innocent code can be a thunder quake via the SIZE of the array. some languages sort in place, others create a
COPY. How often? How thorough? Computationally intensive.
!Sorting custom arrays. Comparator / compare function. Easy.
!
!!!!!!!!!!Searching arrays
C has no search. use a for loop etc to manually find it
!!!!!!!!!!!linear or sequential search - slow brutish and inelegant. sux. is your built in search linear? “check
all the things”
!Built in search functionality.What type is it?
myArray.contains(99)
myArray.indexOf(99)
Not good if linear search.Alternative? Maybe there is no other option.
!Binary search only on ordered array
Ascending values. Divide in half. divide in half again.
Divide and conquer algorithm
!JS has NO binary search.
!When do I use a BINARY SEARCH or a LINEAR SEARCH?
!ARRAY Direct access = random access - located in contiguous place in memory
Arrays use contiguous memory
!LINKED LIST no direct access, just a collection. located anywhere in memory. the first node has link to second which has link to
3rd. Must be access sequentially. Changes pointers. Good for volatile and changing data.
!
!!!!!!!
Kind of over
my head here!

3. SINGLY LINKED LIST
DOUBLE LINKED LIST - link to pref and next
Null ref or terminator or sentenal node OR back to the first - CIRCULAR LINKED LIST
!Java - list is an INTERFACE. Class ArrayList is an array - direct access. LinkedList doubly linked list. Python “lists” are variable
length arrays. etc.
!Array vs Linked List?
!STACKS and QUEUES are collections
a stack of dirty plates. add to the top. take it from the top. last in, first out LIFO data structure
push / pop. Pop REMOVES element.What about read or touch element or peek
myStack.push();
myStack.pop();
myStack.peek();
!ADT Abstract Data Types
data types - boolean, integer, string, etc. formality, employee
ABSTRACT stacks queues, linked lists,
Abstract Class is a class that you cannot instantiate, must inherit from. NOT same thing.
!QUEUE
FIFO - First in First out. Deserts in refrigerator. Multi threading.There are no indexes. One does not insert / remove from
middle.
!enqueue add an object to end
!Priority Queue
relative importance. will jump ahead. compare function.
Deque = double ended queue. Can add/remove from either end. Dequeue is a verb, method
Arrays, Linked List, Stacks and Queues
!ASSOCIATIVE ARRAY
no numerical index. adds meaning. semantic.
Key /Value Pairs
!!!!!!!!!!!!no duplicate keys, must be unique. values can though.
A dictionary or hash is an associative.
!How are these handled in memory? Most Associative Arrays are a HASH TABLE
!HASH
chop em up and mix em together. Hash function
Hash Functions are not invertible are typically one-way
plate of corned beef hash cannot be turned back into cow and potato
!!!!!!
my brainjust
exploded.

4. !!!HASH TABLE - implement assoc arrays. fast. Buckets. add in pairs, key/value
Hash function
!SETS very simple data structure
Unordered collection of objects. No index. No sequence. No key.A bunch of objects in no particular order.What is a set good
at? No duplicates. Cannot add same item.VERY FAST. Fast lookup.
mySet.contains(obj2); check for membership.
!TREE data structure
nodes have links, connection. Like fixed sequence of linked list, this is more 3 dimensional. Logical.
root node - starting place/ pointers object
child nodes / parent / leaf node (no children) I AM TRYING, PEOPLE
!Binary tree - never more than 2 child nodes
BST Binary Search Tree. very searchable. 0, 1, 2. Left child and the right child
! !!!!!!Naturally SORTED
TREE or
Left child node MUST
be less than parent, right child is MORE than parent
!Unbalanced tree. Self-balancing binary trees - shift position of root node (right or left)
number of levels are more eq
Red Black trees
AVL trees
scapegoat trees
Splay tree
!!
!!!!!!!HEAP - data structure, heap sort, binary tree. Heap
implementation
min heap? or max heap?
Min heap child must be greater
Max heap child must be less
Left/right child doesn't matter
Swap nodes TOP TO BOTTOM LEFT TO RIGHT, can swap root node
not really sorted. good for priority queue
oyvey!

5. !GRAPH (not a visual chart)
A graph is a collection of nodes, where any node can link to any other node.And, a node can link to multiple other nodes.
Whatever is meaningful
!like a social network. No fixed root node.Transportation distance btw cities, complex system of interconnection
Vertices or edges. direction? Weight
SUMMARY
Arrays
+ direct indexing
+ easy to create and use
!- sorting and searching
- inserting and deleting, particularly in the middle
!Linked Lists
+ inserting and deleting elements
+ iterating through the collection
!- direct access
- searching and sorting
!Stacks and Queues
+ Designed for LIFO / FIFO
!- direct access
- search sort
!Hash Tables
+ speed of insertion and deletion
+ speed of access
!- overhead
- retrieving in sorted order
- searching for specific value
!Sets
+ membership
+ avoid duplicates
!- everything else
!Binary Search Trees
+ speed of insertion and deletion
+ speed of access
+ maintain sorted order
!- overhead
!Heaps
Fixed structures are faster/smaller. If speed and weight are a concern choose fixed as much as possible.
Well, it might be worth your while to copy the mutable version into an immutable fixed size version of that data structure. Copy
and change types.
Try changing from one structure to another. See if it improves performance.
!NoSQL Databases
DOCUMENT STORE
self-contained document, not rows/columns
XML, JSON very loose, no schema, flexibility. Like MongoDB, CouchDB

6. !KEY-VALUE again no predefined schema. whatever you want in either category
GRAPH DATABASE very inter relational like Neo4j
!XML nested
ORM object relational mapping. Like ActiveRecord (Ruby), Hibernate (Java)
!
!
DEEP DEVELOPMENT’S HANDSOME HELPING FROM TEAM ACTIVITY
One does not merely walk in Data Structures. Not with 10,000 men could you do that.
Therefore, the UX and the UI has to be considered. Moreover, the same, or at least similar
methodologies can be used to help make more nuanced and modularized decisions about
what to do with data, whether to process on client-side or server-side, distributed systems
and load, etc.
At this point, it may come as little surprise that the benefits of team
cohesion and activities make deep development and data decisions
more contextual. But the side benefit of being able to articulate WHY
they are ordering from the Tapas Menu, mixing and matching, as
opposed from the Big Plates, is a timely one. Americans are
struggling with obesity. And so are their servers.
It’s a teachable moment, as they say. Because there is common
ground, even the most technical blah blah blah can become a real
two-way conversation. And that is going to benefit not only out team,
but it is something tasty we can serve up to the larger company
culture. Other groups may enjoy the fruits of our labor. Bon Appétit!
!
!