Notes

This game is build in python with basic knowledge Here is Step by Step Info Grid Design: I have used turtle library of python to make grid with following code : penup() goto(-250,0) speed(0) for step in range(1,11): write(step) right(90) pendown() forward(140) penup() backward(140) left(90) forward(30)   Making Turtles : I have used four different... Continue Reading →

Drools: Rule Engine Notes

Drools Rule Engine The following is a description of the important libraries that make up JBoss Drools Knowledge-api.jar this provides the interfaces and factories. Knowledge-internal-api.jar this provides internal interfaces and factories. Drools-core.jar This is the core engine, runtime component. Contains both the RETE engine and the LEAPS engine. This is the only runtime dependency. Drools-compiler.jar... Continue Reading →

Greedy Algorithm

Greedy Algorithm Greedy is an algorithmic paradigm that builds up a solution piece by piece, always choosing the next piece that offers the most obvious and immediate benefit. At every step, we can make a choice that looks best at the moment, and we get the optimal solution of the complete problem. If a Greedy... Continue Reading →

Dynamic Programming

Dynamic Programming Solves complex problem by breaking it into subproblems and stores the results of subproblems to avoid computing the same results again. Required Properties Overlapping Sub problems Example of Fibonacci Numbers Memorise solution of sub number and store it then if required use that rather calculating again Ways to store value Memoization (Top -... Continue Reading →

Linear Data Structure

Array: Store homogenous elements. Store in contiguous locations. Fixed size not dynamic. Complexities Accessing O(1) Insertion and deletion O(n) worst case Searching O(n) sequential | O(nlogn) is sorted LinkedList Every entry is an object store data and reference of next object. Single LL Every node store reference of next node and last node NULL. Double... Continue Reading →

Hierarchical Data Structure

Hierarchical Data Structure: Binary Tree Node can have at most two children Contain ROOT Node Every Node have following Reference of Left Node Reference of Right Node Data Traversal Depth First Traversal : In Order (LRtR) | Pre Order (RtLR) | Post Order (LRRt) Breadth First Traversal: Level Order Traversal Properties Max no of node... Continue Reading →

Asymptotic Analysis

Evaluate performance of algorithm in term of input size Order of growth in performance in respective of no of elements. Cases to analyze algorithm Worst Case : upper bound O(n) Average Case Best Case: lower bound O(1)  Notations: Theta Notation Θ: Bound algo from above & below Big O Notation : defines Upper bound Omega... Continue Reading →

Searching

Searching: Linear Search Sequential search value in array | O(n) Binary Search Sequential Searching sorted array Find middle element if required element is more than middle then go to right arr and so on. O(nlogn) Jump Search Jump fixed no of steps If required no is less than new step ele do linear search from... Continue Reading →

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