A searching algorithm is the step-by step procedure used to locate specific data among a collection of data. There are two types of searching are.
(i) Linear Search
(ii) Binary Search

Algorist may refer to,
1. A person skilled in the technique of performing basic decimal arithmetic, known as algorism.
2. A person skilled in the design of algorithms.
3. An algorithmic artist.

An algorithm is a finite set of instructions to accomplish a particular task. It is a step-by-step procedure for solving a given problem.

(i) Dynamic programming is an algorithmic design method that can be used when the solution to a problem can be viewed as the result of a sequence of decisions.
(ii) Dynamic programming approach is similar to divide and conquer. The given problem is divided into smaller and yet smaller possible sub-problems.
(iii) Dynamic programming is used whenever problems can be divided into similar sub-problems. So that their results can be re-used to complete the process.
(iv) Dynamic programming approaches are used to find the solution in optimized way. For every inner subproblem, dynamic algorithm will try to check the results of the previously solved sub-problems. The solutions of overlapped sub-problems are combined in order to get the better solution.

(i) Time Factor -Time is measured by counting the number of key operations like comparisons in the sorting algorithm.
(ii) Space Factor -Space is measured by the maximum memory space required by the algorithm.

(i) Input
(ii) Output
(iii) Finiteness
(iv) Definiteness
(v) Effectiveness
(vi) Correctness
(vii) Simplicity
(viii) Unambiguous
(ix) Feasibility
(x) Portable
(xi) Independent

(i) Dynamic programming is an algorithmic design method that can be used when the solution to a problem can be viewed as the result of a sequence of decisions.
(ii) Dynamic programming approach is similar to divide and conquer. The given problem is divided into smaller and yet smaller possible sub-problems.
(iii) Dynamic programming is used whenever problems can be divided into similar subproblems. so that their results can be reused to complete the process.
(iv) Dynamic programming approaches are used to find the solution in optimized way. For every inner subproblem, dynamic algorithm will try to check the results of the previously solved sub-problems.
(v) The solutions of overlapped sub-problems are combined in order to get a better solution.
Steps to doDynamic programming :
(i) The given problem will be divided into smaller overlapping sub-problems.
(ii) An optimum solution for the given problem can be achieved by using result of smaller sub-problem.
(iii) Dynamic algorithms uses Memoization
Fibonacci Series - An example :
(i) Fibonacci series generates the subsequent number by adding two previous numbers. Fibonacci series starts from two numbers -Fib 0 & Fib 1. The initial values of Fib 0 & Fib l can be taken as 0 and 1.
(ii) Fibonacci series satisfies the following conditions:
Fibn = Fib_a-1 + Fib_a-2
(iii) Hence, a Fibonacci series for the n value 8 can look like this
Fib₈ = 0 1 1 2 3 5 8 13
Fibonaeci Iterative Algorithm with Dynamic programning approach : The following example shows a simple Dynamic programning approach for the generation ot Fibonacci series.
Initialize f0 = 0, f1 = 1.
Step- 1: Print the initial values of Fibonacci f0 and f1 
Step- 2: Calculate Fibonacci fib \(\leftarrow \) f0+ f1 
Step- 3: Assign f0 \(\leftarrow \) f1, f1 \(\leftarrow \) fib
Step- 4: Print the next consecutive value of Fibonacci fib
Step- 5: Go to step-2 and repeat until the specified number of terms generated
Example:
if we generate Fibonacci series up to 10 digits, the algorithm will generate the series as shown below:
The Fibonacci series is:
0 1 1 2 3 5 8 13 21 34 55.

Bubble sort algorithm:
(i) Bubble sort algorithm simple sorting algorithm. The algorithm starts at the beginning of the list of values stored in an array. It compares each pair of adjacent elements and swaps them if they are in the unsorted order.
(ii) This comparison and passed to be continued until no swaps are needed, which indicates that the list of values stored in an array is sorted. The algorithm is a comparison sort, is named for the way smaller elements "bubble" to the top of the list.
(iii) Although the algorithm is simple, it is too slow and less efficient when compared to insertion sort and other sorting methods.
(iv) Assume list is an array of n elements. The swap function swaps the values of the given array elements.
Procedure :
(i) Start with the first element i.e., index = 0, compare the current element with the next element of the array.
(ii) If the current element is greater than the next element of the array, swap them.
(iii) If the current element is less than the next or right side of the element, move to the next element. Go to Step 1 and repeat until the end of the index is reached.
(iv) Let's consider an array with values {15, 11, 16, 12, 14, 13} Below, we have a pictorial representation of how bubble sort will sort the given array.

(v) The above pictorial example is for iteration-d. Similarly, remaining iteration can be done. The final iteration will give the sorted array. At the end of all the iterations we will get the sorted values in an array as given below: