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This article explains C++ polymorphism, shows how virtual functions and inheritance break tight coupling, improve code reuse, simplify extensions, and enhance maintainability, and demonstrates its role in common design patterns such as Strategy and Factory Method with clear code examples.
Choosing the right programming language depends on project requirements such as performance, development speed, platform compatibility, and team expertise, with C++ excelling in low‑level control, Java dominating enterprise back‑ends, Python leading in AI and rapid development, and C# powering Windows and Unity game applications.
This article explains C++ move semantics, covering the concepts of lvalues and rvalues, the syntax and rules of rvalue references, how std::move converts lvalues to rvalues, and demonstrates practical applications such as custom class move constructors, STL container optimizations, and return value optimization.
This article provides a comprehensive overview of glibc's heap memory management, explaining the role of brk and mmap, the organization of arenas, heaps, chunks, bin structures, allocation and deallocation strategies, and how these concepts are applied in security research and exploit development.
This article provides a comprehensive overview of heap memory management in C, explaining the concepts of heap versus stack, the usage and internal mechanisms of malloc and free, common pitfalls such as memory leaks and dangling pointers, and compares these functions with new/delete, calloc, and realloc.
The article shares detailed WeChat (wxg) interview experiences from Java and C++ candidates, highlighting the high difficulty, the blend of algorithmic depth and system design breadth, and the extensive range of technical questions that ultimately led both candidates to fail.
This article presents the LeetCode 1514 'Maximum Probability Path' problem, explains the algorithm using a priority‑queue approach, provides full Java and C++ implementations, and concludes with a promotional book giveaway encouraging readers to follow the public account.
This article presents LeetCode problem 1514, which asks for the path with the highest success probability in an undirected weighted graph, explains the problem statement, constraints, and provides detailed Java and C++ implementations using a priority‑queue based Dijkstra‑like algorithm.
This article explains what deadlocks are in C++ multithreaded programming, outlines their causes and four necessary conditions, presents common scenarios and code examples, and offers practical strategies such as consistent lock ordering, std::lock, std::scoped_lock, recursive mutexes, and lock hierarchies to avoid them.
This article benchmarks Python 3.11's speed with a Monte Carlo Pi estimation script, compares it to earlier Python releases and a C++ implementation, shows Docker‑based testing methodology, presents performance results, and extrapolates when Python might surpass C++ in execution time.
The article first highlights Tencent's Q1 2025 financial results and user metrics, then introduces the LeetCode 2013 'Detect Squares' problem, describing its requirements, example, and offering Java, C++, Python, and array‑based solutions along with time and space complexity analysis.
The article first critiques a hiring manager’s salary‑balance rationale for a 985‑master candidate, then presents LeetCode problem 1546 on finding the maximum number of non‑overlapping subarrays whose sums equal a target, explaining the solution using prefix sums and providing Java and C++ implementations.
This article explains how C++ implements runtime polymorphism through virtual function tables, detailing their structure, memory placement, how they enable dynamic binding, and illustrating usage with single, multiple inheritance and practical code examples.
The article first discusses how many large companies now filter candidates by strict academic degree requirements, then presents LeetCode problem 407 (Trapping Rain Water II) and provides a detailed Dijkstra‑variant solution using a min‑heap, including full Java and C++ implementations and complexity analysis.
This guide reviews common backend interview topics, explaining TCP TIME_WAIT behavior, multi‑port listening, full page load steps, Redis data types, Kafka consumer sizing and at‑most‑once semantics, the CAP theorem, Singleton usage, C++ std::map complexity, and an O(n) doubly‑linked list reversal algorithm.
The article outlines seven practical performance‑optimization techniques for high‑throughput back‑ends—including replacing protobuf with native C++ classes, adopting cache‑friendly data structures, using jemalloc/tcmalloc, implementing lock‑free double buffers, simplifying structs for specific scenarios, and leveraging profiling tools—while stressing balanced, incremental improvements.
The article reflects on why mid‑career engineers are often relegated to legacy‑maintenance work, argues that such roles can be leveraged for growth by modernizing systems and adopting AI, and then presents the classic Valid Parentheses coding challenge, explaining a stack‑based solution with implementations, complexity analysis, and common pitfalls.
Serialization in C++ bridges in‑memory objects and persistent or network formats, addressing challenges like byte order, data type compatibility, and complex structures, while the article reviews core principles, binary and text formats, major libraries such as Protobuf, Cereal, Cista++, ThorsSerializer, and offers guidance on selecting and using them effectively.
This article introduces the POSIX standard for portable multithreaded and network programming in C, explains thread creation, lifecycle, and synchronization mechanisms such as mutexes, semaphores and condition variables, and provides complete server‑client socket examples together with practical multithreaded file‑processing code and debugging tips.
This article explains the problems of memory fragmentation and allocation inefficiency in C++ programs, introduces the concept of memory pools, discusses their design principles, advantages, and common implementations, and provides a complete example of a thread‑safe fixed‑size memory pool with code.