Introduction to Fundamentals of Data Structure
Fundamentals of data structure mean the basic and general principles or the characteristics which are needed to understand and work on any data structure. Data structures are an important part of the field of computer science in order to efficiently handle and organize (store, process, and access) data in order to solve real-life problems. Some of the examples of data structures are Stack, Queue, Arrays, Tree, Heap, etc. While executing any data structure, it is important to understand various terminologies and the basic concepts which makes the choice of the right data structure according to the problem of the user.
Important Fundamentals of Data Structure
Choosing the right data structure is sometimes difficult for the programmer but understanding the basic and most important fundamentals/ characteristics of data structure makes it somewhat easier for the programmer to choose the appropriate one. Some of the basic principles of the data structure are discussed below:
- Static: Static is one of the basic yet important characteristics of the data structure. In the static data structure, size and structure of data items that need to be stored, processed, and accessed in the memory location are fixed at the compile time. For example, in Arrays, the size of the data items to be stored of a particular data type is defined in the starting only (at the compile time).
- Homogeneous: As understood by the name, Homogeneous is again an important characteristic of data structure which represents that all the data items of the particular data structure should be of the same data type be it an integer, float, string, etc. For example, in an Array, all the data items need to be of the same type be it an integer, float, string, etc.
- Non- homogeneous: Unlike homogeneous, non-homogeneous means that the data type of all the data elements of a data structure may or may not be the same.
- Linear: Linear in data structure means that all the elements of the data structure need to be in a sequential form. For example, Stack, Queue, Linked List, Array, are all linear data structures as all the data elements are stored sequentially (in a linear manner) in them.
- Non-linear: Non- linear data structure means all the data elements of the data structure are not in a sequential manner. For example, in the data structures like trees, graphs, data elements are not stored sequentially.
- Dynamic: ‘Dynamic’ is the characteristic of data structure means that the size of the structure, i.e. the number of the elements is defined at the runtime. This size of the data structure can be expanded and shrunk according to the requirement of the programmer. Dynamic data structures are very helpful when it comes to the saving of memory, as the allocation of memory is done only when needed and no unnecessary memory is allocated which allows others to use it efficiently. For example, in Stack, Queue, and Linked List the memory is allocated dynamically.
- Complexity: Complexity in the data structure can be:
- Time Complexity: Time Complexity specifies the time which is needed to execute that data structure. In order to have the best results, such data structure should be used where the execution time should be minimal. We can relatively define the complexity of the data structures as follows:
- Worst Case: Worst Case is basically the scenario when the data structure takes the maximum time to execute. If the worst-case complexity of any data structure is f(n), then no matter what but the complexity of that will not exceed more than it in any scenario.
- Best Case: Best Case is defined as the scenario where the execution time of the particular data structure takes the least/ minimal time.
- Average Case: It defines the average time that is needed to execute the data structure. Average Case time would be between the best case and the worst-case time complexity.
- Space Complexity: Space Complexity means that the memory space required to run the data structure should be minimum. No Unnecessary memory usage and occupy should be present.
- Correctness: Correctness in data structure means that the result/ output of the execution of the data structure needs to be correct. Moreover, the data structure needs to implement its interface correctly.
Fundamental Operations of Data Structures
- Insertion: As the name indicates, insertion means adding the data elements to the data structure. This is the first step after defining the data structure, the programmer needs to insert the elements in it according to the requirements. Generally, in any data structure, if the size of the data structure is n, then only (n-1) elements can be inserted (as it starts from 0).
- Deletion: Deletion is basically removing the data elements from the data structure. Programmers can delete the element from a particular location in the data structure.
- Traversing: Traversing means visiting each element of the data structure in order to perform the required operation, be it insertion, deletion, searching, etc.
- Searching: Searching in a data structure is one of the operations needed the most. The programmer needs to search for the particular element by traversing the whole structure. Various algorithms are used by the programmers in order to search the elements in a specific data structure like binary search, linear search, etc.
- Sorting: Sorting is basically arranging the data elements of the data structure in ascending order, descending order or in some logical order. Various sorting algorithms are defined in order to get the best results according to the data structure and its elements like Insertion sort, Selection sort, Bubble Sort, Quick Sort, etc.
- Merging: Merging in a data structure means joining the data elements of the same type. Consider an array having ‘n’ elements of integer type and another array of integer type having ‘m’ elements, they both can be merged in a single array (data structure) of integer type having (m+n) elements.
The above description clearly explains what are the basic data structures and their fundamentals which every programmer needs to well understand. The data structure is the main part of computer science algorithms and plays an important role in the fast storage and retrieval of data. In order to solve the real problem, appropriate data structure needs to be used by the programmer which should be simple and rich enough to satisfy the relationships of data and its structure.
This is a guide to Fundamentals of Data Structure. Here we also discuss the introduction and fundamental operations of data structures along with a detailed explanation. You may also have a look at the following articles to learn more –
- Heap Data Structure
- Hashing in Data Structure
- Circular Linked List in Data Structure
- Stack in Data Structure