Is a data structure a collection of data items with a structure?

A data structure is not a collection of data items with a structure. A data structure is a collection of data elements that have one or more specific relationships with each other. In data structures, data structures can be logically divided into: linear structures and non-linear structures.

Data structures are the way computers store and organize data. Data structure refers to a collection of data elements that have one or more specific relationships with each other. In other words, a data structure is a collection of data elements with "structure", and "structure" refers to the relationship between data elements.

Data structure is a collection of data elements with structural characteristics. It studies the logical structure of data and the physical structure of data and the relationship between them, and analyzes this The structure defines appropriate operations, designs corresponding algorithms, and ensures 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, by decomposing the processing requirements into various functions, and then discarding the implementation details through abstraction, the definition of the operation is obtained. 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, thereby completing the design task. This is a process from abstract (i.e. data structure) to concrete (i.e. specific implementation).

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