Seasoned Java and mobile developer with years of experience, specializing in mini‑programs, public accounts, and full‑stack front‑end development. In the AI era, I continuously learn to broaden my knowledge and evolve. I revived a public account I started a decade ago during a dessert‑startup venture, using code as a vessel and knowledge as a companion. I share personal projects, technical articles, programming tips, and growth insights—let’s improve together and set sail.
This article introduces the stack data structure, explains its LIFO principle with everyday analogies like browser back and undo, compares it to arrays and linked lists, provides a complete Python implementation, demonstrates a simple undo simulation, and highlights common pitfalls for beginners.
This tutorial explains linked lists with a vivid array‑vs‑list analogy, outlines their core structure, shows real‑world scenarios, provides fully commented Python code with sample output, and highlights common pitfalls and a quick decision guide for choosing between arrays and linked lists.
This article explains arrays using a locker analogy, outlines their core characteristics and typical use cases, provides a complete Python example for basic operations with output, and highlights common beginner pitfalls such as zero‑based indexing and fixed length.
The article explains that MySQL’s EXPLAIN command acts as a SQL health check, detailing each of its 12 fields—especially type, key, rows, and Extra—while providing real‑world examples, a step‑by‑step diagnostic workflow, and common pitfalls to help developers reliably tune and troubleshoot queries.
This concluding tutorial walks beginners through SQL Server stored procedures, highlighting their speed, reusability, and automation advantages over single statements and views, and demonstrates creating, invoking (with and without parameters), altering, and dropping procedures while sharing naming conventions and common pitfalls.
This article explains how database views act as virtual tables that store only query logic, allowing developers to replace repetitive, multi‑join SQL statements with a single, reusable query while improving consistency, hiding sensitive fields, and boosting development efficiency.
The article explains why MySQL back‑table lookups (回表) double I/O and degrade performance, defines covering indexes that retrieve all needed columns from a secondary index, shows how to identify back‑table cases via EXPLAIN, and provides step‑by‑step commands to create, test, and verify covering indexes for high‑frequency queries.
The article explains how database transactions ensure atomicity, consistency, isolation, and durability, showing why they are essential for preventing data inconsistency, loss, and reconciliation errors, and provides step‑by‑step SQL examples of successful and rolled‑back transactions along with practical tips for safe usage.
This article explains MySQL InnoDB's MVCC mechanism, detailing how snapshot reads and current reads work, the hidden fields that drive versioning, the Read View rules for RC and RR isolation levels, and provides hands‑on SQL demos plus common pitfalls to avoid.
The article explains that indexes are the key to solving most database slow‑query problems, compares full‑table scans with indexed lookups, describes the two main index types in SQL Server, and provides step‑by‑step T‑SQL commands for creating, testing, and removing indexes while warning against over‑indexing.
