Introduction

The insurance company intends to computerize their records. Customers can purchase life and education insurance policies for their children. The customer base of the company currently stands at 200, and the company expects growth of no more than 10% over the following decade. In total there are 200 customers, of which 150 have life insurance, and the rest have education insurance. Customer information includes name, address, contact information, age, health condition record, beneficiary information, and yearly payment schedule for life insurance policies. To maintain the education policy, the system needs to maintain the name of the customer, the address, contact information, the child`s age, the policy`s type, and the child`s name. This insurance company wishes to develop these processes into a management system, so that task data can be easily stored and updated. There will be detailed information in the following sections, focusing primarily on the planning, and design sections of the insurance policy management and tracker system. The report will begin with a brief overview of the background information that will be necessary to successfully design the system. The next section will discuss the case study and the design of the system. Finally, the report will conclude with a conclusion.

Background

The development of the tracking system requires an understanding of the basic concepts of sorting and searching, as discussed in the above section. Any time you need to sort a great deal of data you will need to use the most frequently used sort, namely a merge sort. While insertion sort is extremely important when entering data into the system, if a value needs to be added to the array list that is already sorted, this is not a feasible option. Last but not least, the binary search is one of the most commonly used algorithms in order to search any item and retrieve information from the system. This can then be used to update any particular data into the system.

Merge Sort – Merge sort is a sorting technique that uses the divide and conquer strategy. It is one of the more popular and efficient sorting algorithms, dividing the given list into two half, calling itself for each half, and finally merging the sorted halves. Each sub-list is divided into halves several times until there are no more halves to divide. Next, we merge the two-element lists, sorting them as we do so[1]. Once the two-element pairs have been sorted, they are merged to form four-element lists, and so on until we have the sorted list. It is same as the divide and conquer strategy[2]. In the Divide and Conquer approach, one can divide a problem into subproblems and build solutions for each subproblem separately[3]. Once the solutions to the subproblems are ready, we combine their results to solve the main problem. Let us assume a subproblem in sorting an array A would be to sort a subset that starts at index p and ends at index r, called A[p..r]. In dividing section, by splitting the subarray A[p..r] into A[p..q] and A[q+1, r], we can achieve the same result as splitting the subarray A[p..r]. As part of the conquer step, it can again be divided both these subarrays and again attempt to sort them[4]. If the furrent form are not yet at the base case, it is then divided repeatedly. As soon as the conquer step reaches the base step for array A[p..r], two sorted subarrays A[p..q] and A[q+1, r] for array A[p..r]is created by creating a sorted array A[p..r] by combining two sorted subarrays A[p..q] and A[q+1, r].

Insertion Sort – A sorting algorithm that is easy to implement and is very simple is insertion sort. The concept is very close to that of sorting playing cards, where the selected card is compared to its previous cards[5]. It is done until all of the cards have been sorted. If they are smaller than the selected card, the smaller card is swapped, otherwise the next card in the row is checked. Furthermore, once a card has been checked and placed in the correct place, it is considered to be sorted[6]. Next, another card will be selected from the unsorted section, which will also be checked to be placed in the sorted part.

Binary Search – Binary searches work primarily based on divide and conquer rule based algorithms. They are also known as half interval search algorithms. It basically divides the data into half then checks the middle value of each two-part set[7]. Basically, if the value (middle position) is less than the data to be searched, it searches for segments left of the value in the leftward direction[8]. If the value (middle position) is more than the data to be searched, the algorithm searches by leftward division. Until all the elements in the list have been searched for the data to be searched or until all the data is found, this process continues[9]. In addition, a certain prerequisite must also be met in order for the binary search algorithm to work correctly; namely, the list must be arranged in ascending order before beginning the process.