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Data structures are ways of organizing and storing data in a computer so that it can be accessed and modified efficiently. They are essential for managing and processing data dynamically and play a crucial role in software development and computer science. Common data structures include arrays, linked lists, stacks, queues, hash tables, trees, and graphs. Each structure has its advantages and is suited to specific tasks; for example, arrays allow fast access to elements using indices, linked lists facilitate easy insertion and removal of elements, and trees are ideal for hierarchical data representation. Hash tables offer efficient data retrieval through key-value mapping. Understanding and choosing the right data structure is key to optimizing algorithms and solving complex computational problems efficiently.
Data structures are fundamental components in computer science. They provide a way to organize data and store data efficiently, allowing programs to access and manipulate information effectively. Let’s delve into the world of data structures:
Definition: A data structure is a logical or mathematical representation of data, along with its implementation in a computer program. It encompasses both the arrangement of data values and the relationships among them12.
Purpose: Data structures serve as the foundation for abstract data types (ADTs). While the ADT defines the logical form of a data type, the data structure implements its physical form. Different types of data structures cater to various applications, and some are specialized for specific tasks. For instance:
B-tree indexes are commonly used in relational databases for data retrieval.
Hash tables are prevalent in compiler implementations for looking up identifiers.
Efficient Algorithms: Well-designed data structures are key to efficient algorithms. * They allow us to manage large amounts of data effectively, whether it’s in main memory or secondary memory1.
Implementation: Data structures can be implemented using various programming languages and techniques. They all share the common goal of organizing and storing data efficiently. Some examples include:
Arrays: Contiguous memory allocation facilitates rapid access and modification operations.
Linked lists: Store addresses of data items within the structure itself1.
Types: There are numerous data structures, each built upon simpler primitive data types. Some common ones include:
In summary, data structures empower us to harness the power of data, making our algorithms smarter and more effective.
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Snippet from Wikipedia: Data structure
In computer science, a data structure is a data organization and storage format that is usually chosen for efficient access to data. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data, i.e., it is an algebraic structure about data.
Template for programming language
In computer science, a data structure is a data organization, management and storage format that enables Algorithmic efficiency | efficient access and modification. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data.
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Snippet from Wikipedia: Data structure
In computer science, a data structure is a data organization and storage format that is usually chosen for efficient access to data. More precisely, a data structure is a collection of data values, the relationships among them, and the functions or operations that can be applied to the data, i.e., it is an algebraic structure about data.
Main article is List of data structures
There are numerous types of data structures, generally built upon simpler primitive data types:<ref>
</ref>
An
array data structure |
''array'' is a number of elements in a specific order, typically all of the same type (depending on the language, individual elements may either all be forced to be the same type, or may be of almost any type). Elements are accessed using an integer index to specify which element is required. Typical implementations allocate contiguous memory words for the elements of arrays (but this is not always a necessity). Arrays may be fixed-length or resizable.
A
linked list (also just called
list) is a linear collection of data elements of any type, called nodes, where each node has itself a value, and points to the next node in the linked list. The principal advantage of a linked list over an array, is that values can always be efficiently inserted and removed without relocating the rest of the list. Certain other operations, such as
random access to a certain element, are however slower on lists than on arrays.
A
Record (computer science) |
''record'' (also called
tuple or
struct) is an aggregate data structure. A record is a value that contains other values, typically in fixed number and sequence and typically indexed by names. The elements of records are usually called
fields or
members.
A
Union (computer science) |
''union'' is a data structure that specifies which of a number of permitted primitive types may be stored in its instances, e.g.
float or
long integer. Contrast with a
record (computer science) |
record, which could be defined to contain a float
and an integer; whereas in a union, there is only one value at a time. Enough space is allocated to contain the widest member datatype.
A
tagged union (also called
variant type |
''variant'',
variant record,
discriminated union, or
disjoint union) contains an additional field indicating its current type, for enhanced type safety.
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In addition, Graph (computer science) | ''graphs'' and binary trees are other commonly used data structures.