What are the main contents of data structure research?
What is the main content of data structure research?
Data structure research mainly includes three aspects, They are: the logical structure of the data, the storage structure of the data, and the operations of the data defined on it.
Introduction to data structures:
Data structures are the way computers store and organize data. A data structure refers to a collection of data elements that have one or more specific relationships with each other. Often, carefully selected data structures can lead to higher operating or storage efficiency. Data structures are often related to efficient retrieval algorithms and indexing techniques.
Definition
Data structure (data structure) is a collection of data elements with structural characteristics. It studies the logical structure of data and the physical structure of data. Interrelationships between them, define appropriate operations for this structure, design corresponding algorithms, and ensure that the new structure obtained after these operations still maintains the original structure type. In short, a data structure is a collection of data elements that have one or more specific relationships with each other, that is, a collection of data elements with a "structure". "Structure" refers to the relationship between data elements, which is divided into logical structure and storage structure.
The logical structure and physical structure of data are two closely related aspects of data structure. The same logical structure can correspond to different storage structures. The design of the algorithm depends on the logical structure of the data, and the implementation of the algorithm depends on the specified storage structure.
The research content of data structure is the basis for constructing complex software systems, and its core technology is decomposition and abstraction. Through decomposition, three levels of data can be divided; through abstraction, the specific content of the data elements is discarded, and the logical structure is obtained. Similarly, operations are defined by decomposing processing requirements into functions and discarding implementation details through abstraction.
The combination of the above two aspects can transform the problem into a data structure. This is a process from concrete (that is, concrete problems) to abstract (that is, data structures). Then, by adding consideration to the implementation details, the storage structure and implementation operations are further obtained to complete the design task. This is a process from abstract (i.e. data structure) to concrete (i.e. specific implementation).
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