Liangxu, a self‑taught IT professional now working as a Linux development engineer at a Fortune 500 multinational, shares extensive Linux knowledge—fundamentals, applications, tools, plus Git, databases, Raspberry Pi, etc. (Reply “Linux” to receive essential resources.)
The article recommends a progression of open‑source projects—starting with libevent, then muduo, Redis, and finally nginx—to help developers master C/C++ network programming through hands‑on exploration, performance tuning, and debugging techniques.
The article examines how AI‑driven code completion boosts productivity but can erode fundamental programming skills, illustrated with anecdotes, a real‑world TCP server failure, and practical advice for balancing tool use with deep understanding.
The article examines the feasibility of adding programming to China's college entrance exam, weighing benefits such as fostering computational thinking against challenges like teacher readiness, curriculum volatility, and potential widening of educational inequality.
The article explains that C’s lasting dominance stems from its extreme simplicity with only 32 keywords, low‑level hardware access, and its deep ties to Unix, which together created an ecosystem that outlasted newer languages despite C’s lack of modern features.
The article examines the niche programming game Screeps, explains why its code‑driven mechanics appeal to developers yet deter casual gamers, and proposes lowering barriers, improving feedback, and fostering community to make such “legal cheat” MMOs mainstream.
Big tech companies use LeetCode algorithm tests as a standardized, quantifiable filter to gauge learning potential and problem‑solving skills, even though these tests do not reflect real engineering ability, leading to a paradox where strong algorithm performers may lack practical coding quality and vice versa.
The article explains that Chinese programmers rarely write unit tests because tight schedules, low managerial emphasis, high workload, legacy code complexity, and a culture that values rapid feature delivery over testing, leading to systemic resistance despite occasional recent shifts toward coverage mandates.
The article explores how computer science students spend hours coding, from repetitive homework on basic algorithms in early years to full‑stack project development, competition‑level embedded systems, relentless debugging, personal passion projects, and sometimes merely pretending to work hard.
The author argues that successful programming relies 70% on understanding, 20% on practice, and only 10% on memorization, emphasizing that developers should focus on grasping core concepts, building muscle memory through repeated coding, and using documentation as needed rather than trying to memorize every API.
The article examines MoonBit's proposal to add optional Chinese keywords, discussing technical feasibility through a mapping table, potential advantages for beginners and non‑English speakers, and counterarguments about internationalization, developer workflow, and AI tooling compatibility.
