Here is where I store my notes on data structures and algorithms

Algorithm Design

• Reasonable-looking algorithms can be easily be incorrect. Algorithms correctness must be proven.
• Proving correctness of algorithms need clear and precise modelling of the problem. We need the set of allowed input instances and the required properties of the algorithm's output.
• An important technique in algorithm design is to narrow the set of allowable instances until there is a correct and efficient algorithm.
• The heart of any algorithm is an idea. If your idea is not clearly revealed when you express an algorithm, then you are using too low-level a notation to describe it.
• Searching for counterexamples is the best way to disprove the correctness of a heuristic.
• Modeling your application in terms of well-defined structures and algorithms is the most important single step towards a solution.

Algorithm Analysis

• The Big Oh notation and worst-case analysis are tools that greatly simplify our ability to compare the efficiency of algorithms.
• Logarithms arise whenever things are repeatedly halved or doubled.

Data Structures