---- v1_introduction

Data Structures:
	Follows on from CS211
	C++, memory, etc.
	CS311 will also use C++
		cout, objects, new, delete, etc.
		We'll mostly avoid private data members
	I do have CS211 videos online
	4 different CS211 teachers might be represented here

Online class:
	Testing Center requirement
	Weekly schedule:  Content released Friday of the previous week
			
Syllabus and Calendar

---- v2_pointer_review

First:  A review of C++ pointers
	We'll use them more than CS211 did
	Remembering CS253 could be helpful too
	They'll be used in CS430 and CS435

Memory areas:  Heap vs. Stack allocation
	Picture on board
	Address range:  Three variables from each
	Code segment also, to be complete
	
We will be building data structures on the heap
	Why not the stack?
	Lifetime will not correlate with function calls
	Size will vary throughout the structure's lifetime
	A data structure contains a bunch of "normal" variables


---- v3_return_data_from_function

A demo here:  A function that concatenates two strings
	Yes, C++ does this
	But how?

---- v4_data_structure_intro

Structuring data, philisophical note:
	A lot of organizational schemes have a real-world analogy
		Trees, etc
	Retrieval time is usually important
		Just like in normal life
		Kitchens, projects, dentists, etc.
	
What do we really want out of a data structure?
	Quick retrieval
	Quick addition of new data
	Quick deletion of data that actually frees up space
	Quick search
	Efficient use of memory
	Parallel access from multiple threads
	Parallel modification from multiple threads	
	Simple enumeration of items (in sorted order)
	Doesn't lose data
	Accesses normally result in a CPU cache hit
	Low use of CPU resources (battery life)
	
We'll cover traditional staples of data organization
	More important is to learn to think through data organization
	There are good libraries for the structures we'll learn
	Sometimes a custom solution is better
		It might not be exactly any of what we've discussed in this class

---- v5_lab_1_equations

Lab 1:
	A lot of people kinda freak out about the equation bit
	If you run into trouble, feel free to ask me
		Also:  I teach a CS250 lab on Mondays at 3:00, feel free to drop in
	Pretty simple:
		Capital Sigma and capital Pi are both counting loops
		For capital Sigma, add all the terms up
		For capital Pi, multiply them
		Examples, in a math sense
		Example translating to code
	Computational Complexity related to n (and m in one case):
		How does the runtime scale increase as related to n?
		For each of the first four, it's one of these:
			Linear:  double n, runtime will double
			Squared:  Runtime is related to n squared
			Give it your best shot on 5