Hello everyone!
I will start a blog series focused on data structures and algorithms (DSA). The tutorial content is based on my study and experience.
I will write these tutorials in C and provide introductory tutorials for beginners in C.
Although DSA can be implemented in languages such as C, Java, or Python,
But I chose to use C.
This is a simple introduction, so don’t worry about not being able to understand it. The follow-up article will explain in detail.
This is just a preview of our discussion topic.
C language beginners are advised to learn the basics of C language first. If you are familiar with Java, it is even better.
My blog aims to help everyone learn C and DSA at the same time.
Original data structure
Raw data structures are the most basic data types in programming languages. Common raw data structures include:
- Int: Indicates an integer without a fractional part. For example: -1, 0, 4
- Float, double: represents a real number with a decimal part. For example: 3.14, -0.001, 2.71828
- Character (char): represents a single character, usually enclosed in single quotes. For example: 'a', 'z', '9', '#'
- Boolean value (bool): represents a true or false value, that is, true or false. Used for conditional statements and loops.
- String: Represents a sequence of characters, usually used to store text, enclosed in double quotes. For example: "Hello, world!", "python", "12345"
<code class="language-c ">#include <iostream> using namespace std; int main() { // Integer int age = 25; cout </iostream></code>
Non-original data structure
A non-primitive data structure, also known as a composite data structure or user-defined data structure, is more complex than the original data structure. They are combined from raw data structures to store and manage more complex data collections.
- Array: an ordered collection of elements of the same type, stored in continuous memory locations.
- Linked list: A collection of elements, each element pointing to the next element, allowing dynamic memory allocation.
- Stack: A linear data structure that follows the principle of last in first out (LIFO). For example: a pile of dishes that can only be added or removed from the top.
- Queue: A linear data structure that follows the first-in first-out (FIFO) principle. For example: wait in line, and the first person who comes will serve first.
- Tree: A hierarchical data structure with root nodes and child nodes, used to represent hierarchical relationships. For example: binary tree, binary search tree.
- Figure: A collection consisting of nodes (vertices) and edges to represent network relationships. For example: social networks, computer networks.
- Hash table: The data structure that stores key-value pairs, and uses a hash function to calculate the storage location.
<code class="language-c ">// ... (code examples for non-primitive data structures would go here)</code>
The above is the detailed content of DSA Day Introduction. For more information, please follow other related articles on the PHP Chinese website!

You can use the TinyXML, Pugixml, or libxml2 libraries to process XML data in C. 1) Parse XML files: Use DOM or SAX methods, DOM is suitable for small files, and SAX is suitable for large files. 2) Generate XML file: convert the data structure into XML format and write to the file. Through these steps, XML data can be effectively managed and manipulated.

Working with XML data structures in C can use the TinyXML or pugixml library. 1) Use the pugixml library to parse and generate XML files. 2) Handle complex nested XML elements, such as book information. 3) Optimize XML processing code, and it is recommended to use efficient libraries and streaming parsing. Through these steps, XML data can be processed efficiently.

C still dominates performance optimization because its low-level memory management and efficient execution capabilities make it indispensable in game development, financial transaction systems and embedded systems. Specifically, it is manifested as: 1) In game development, C's low-level memory management and efficient execution capabilities make it the preferred language for game engine development; 2) In financial transaction systems, C's performance advantages ensure extremely low latency and high throughput; 3) In embedded systems, C's low-level memory management and efficient execution capabilities make it very popular in resource-constrained environments.

The choice of C XML framework should be based on project requirements. 1) TinyXML is suitable for resource-constrained environments, 2) pugixml is suitable for high-performance requirements, 3) Xerces-C supports complex XMLSchema verification, and performance, ease of use and licenses must be considered when choosing.

C# is suitable for projects that require development efficiency and type safety, while C is suitable for projects that require high performance and hardware control. 1) C# provides garbage collection and LINQ, suitable for enterprise applications and Windows development. 2)C is known for its high performance and underlying control, and is widely used in gaming and system programming.

C code optimization can be achieved through the following strategies: 1. Manually manage memory for optimization use; 2. Write code that complies with compiler optimization rules; 3. Select appropriate algorithms and data structures; 4. Use inline functions to reduce call overhead; 5. Apply template metaprogramming to optimize at compile time; 6. Avoid unnecessary copying, use moving semantics and reference parameters; 7. Use const correctly to help compiler optimization; 8. Select appropriate data structures, such as std::vector.

The volatile keyword in C is used to inform the compiler that the value of the variable may be changed outside of code control and therefore cannot be optimized. 1) It is often used to read variables that may be modified by hardware or interrupt service programs, such as sensor state. 2) Volatile cannot guarantee multi-thread safety, and should use mutex locks or atomic operations. 3) Using volatile may cause performance slight to decrease, but ensure program correctness.

Measuring thread performance in C can use the timing tools, performance analysis tools, and custom timers in the standard library. 1. Use the library to measure execution time. 2. Use gprof for performance analysis. The steps include adding the -pg option during compilation, running the program to generate a gmon.out file, and generating a performance report. 3. Use Valgrind's Callgrind module to perform more detailed analysis. The steps include running the program to generate the callgrind.out file and viewing the results using kcachegrind. 4. Custom timers can flexibly measure the execution time of a specific code segment. These methods help to fully understand thread performance and optimize code.


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