Data Structure and Algorithms Reviewer

Correctness

CHARACTERISTICS OF DATA STRUCTURE - Data structure implementation should implement its interface correctly.

Space Complexity

CHARACTERISTICS OF DATA STRUCTURE - Memory usage of a data structure operation should be as little as possible.

Time Complexity

CHARACTERISTICS OF DATA STRUCTURE - Running time or the execution time of operations of data structure must be as small as possible.

Multiple requests

COMMON PROBLEMS THE APPLICATION FACE NOW-A-DAYS - As thousands of users can search data simultaneously on a web server, even the fast server fails while searching the data. To solve the above-mentioned problems, data structures come to rescue. Data can be organized in a data structure in such a way that all items may not be required to be searched, and the required data can be searched almost instantly.

Data Search

COMMON PROBLEMS THE APPLICATION FACE NOW-A-DAYS - Consider an inventory of 1 million(106) items of a store. If the application is to search an item, it has to search an item in 1 million(106) items every time slowing down the search. As data grows, search will become slower.

Processor speed

COMMON PROBLEMS THE APPLICATION FACE NOW-A-DAYS - Processor speed although being very high, falls limited if the data grows to billion records.

IMPLEMENTATION

Foundation of Data Structure that provides the internal representation of a data structure. Implementation also provides the definition of the algorithms used in the operations of the data structure.

INTERFACE

Foundation of Data Structure that represents the set of operations that a data structure supports. An interface only provides the list of supported operations, type of parameters they can accept and return type of these operations.

is a systematic way to organize data in order to use it efficiently.

WHAT IS DATA STRUCTURE? Basic Terminologies ?Data - Data are values or set of values. ?Data Item - Data item refers to single unit of values. ?Group Items - Data items that are divided into sub items are called as Group Items. ?Elementary Items - Data items that cannot be divided are called as Elementary Items. ?Attribute and Entity - An entity is that which contains certain attributes or properties, which may be assigned values. ?Entity Set - Entities of similar attributes form an entity set. ?Field - Field is a single elementary unit of information representing an attribute of an entity. ?Record - Record is a collection of field values of a given entity. ?File - File is a collection of records of the entities in a given entity set. ALGORITHM -is a step-by-step procedure, which defines a set of instructions to be executed in a certain order to get the desired output. Algorithms are generally created independent of underlying languages, i.e. an algorithm can be implemented in more than one programming language. CATEGORIES OF ALGORITHMS Search - Algorithm to search an item in a data structure. Sort - Algorithm to sort items in a certain order. Insert - Algorithm to insert item in a data structure. Update - Algorithm to update an existing item in a data structure. Delete - Algorithm to delete an existing item from a data structure. CHARACTERISTICS OF ALGORITHM Unambiguous - Algorithm should be clear and unambiguous. Each of its steps (or phases), and their inputs/outputs should be clear and must lead to only one meaning. Input - An algorithm should have 0 or more well-defined inputs. Output - An algorithm should have 1 or more well-defined outputs, and should match the desired output. Finiteness - Algorithms must terminate after a finite number of steps. Feasibility - Should be feasible with the available resources. Independent - An algorithm should have step-by-step directions, which should be independent of any programming code. How to Write an Algorithm? There are no well-defined standards for writing algorithms. Rather, it is problem and resource dependent. Algorithms are never written to support a particular programming code. As we know that all programming languages share basic code constructs like loops (do, for, while), flow-control (if-else), etc. These common constructs can be used to write an algorithm. We write algorithms in a step-by-step manner, but it is not always the case. Algorithm writing is a process and is executed after the problem domain is well-defined. That is, we should know the problem domain, for which we are designing a solution. Example Let's try to learn algorithm-writing by using an example. Problem: Design an algorithm to add two numbers and display the result. Step 1 - START Step 2 - declare three integers a, b & c Step 3 - define values of a & b Step 4 - add values of a & b Step 5 - store output of step 4 to c Step 6 - print c Step 7 - STOP Alternatively the algorithm can be written as follows: Step 1 ? START ADD Step 2 ? get values of a & b Step 3 ? c �� a + b Step 4 ? display c Step 5 ? STOP ������In design and analysis of algorithms, usually the second method is used to describe an algorithm. It makes it easy for the analyst to analyze the algorithm ignoring all unwanted definitions. He can observe what operations are being used and how the process is flowing. Writing?step numbers, is optional. We design an algorithm to get a solution of a given problem. A problem can be solved in more than one ways. ������Hence, many solution algorithms can be derived for a given problem. The next step is to analyze those proposed solution algorithms and implement the best suitable solution. Algorithm Analysis Efficiency of an algorithm can be analyzed at two different stages, before implementation and after implementation. They are the following ? ������ Priori?Analysis?? This is a theoretical analysis of an algorithm. Efficiency of an algorithm is measured by assuming that all other factors, for example, processor speed, are constant and have no effect on the implementation. ������ Posterior?Analysis?? This is an empirical analysis of an algorithm. The selected algorithm is implemented using programming language. This is then executed on target computer machine. In this analysis, actual statistics like running time and space required, are collected. Algorithm Complexity ������Time Factor?? Time is measured by counting the number of key operations such as comparisons in the sorting algorithm. ������Space Factor?? Space is measured by counting the maximum memory space required by the algorithm. Space Complexity ������Space complexity of an algorithm represents the amount of memory space required by the algorithm in its life cycle. The space required by an algorithm is equal to the sum of the following two components ? 1.A fixed part that is a space required to store certain data and variables, that are independent of the size of the problem. For example, simple variables and constants used, program size, etc. 2.A variable part is a space required by variables, whose size depends on the size of the problem. For example, dynamic memory allocation, recursion stack space, etc.