转: Good Programming, Bad Programming

Good Programming, Bad Programming

November 17, 2012

Some thoughts on Good Programming and Bad Programming:

Good Programming makes even complex things seem simple.
Bad Programming makes even simple things complex.

Good programming is self-explanatory.
Bad Programming requires explanation.

Good Programming takes more time now, but less time in future.
Bad Programming takes less time now, but more time in future.

Good Programming involves considering present and future requirements.
Bad Programming focuses only on the present and may not work in future.

Good Programs are easy to maintain.
Bad Programs are hard to maintain.

Good Programs have a longer lifespan, and may even outlast the purpose for which they were created.
Bad Programs have short lifespan and barely usable outside their working scope.

Good Programs are like good habits, whose effects last for a long time and solves the problem almost permanently.
Bad Programs are like painkillers, whose effects last for only short time and solves the problem mostly temporarily.

Good Programming is clean and disciplined.
Bad Programming is messy and chaotic.

Good Programming is learned, practiced and mastered over a period of years.
Bad Programming is self brought, and when practiced for long time makes it even more difficult to learn good programming.

Good Programming is knowing when to invent and when to reuse.
Bad Programming is inventing what's already invented, and reusing what can be better invented.

Good Programming is relying on your own instincts and knowledge, gained after years of good programming practice.
Bad Programming is relying blindly on others knowledge and experience, without applying your own understanding.

Good Programs can be transferred from one programmer to another programmer.
Bad Programs can only be understood and implemented by the same programmer.

Good Programmer doesn't memorize piece of code. He relies on his logical skills and understanding, and can enhance the code easily in future.
Bad Programmer memorizes the piece of code instead of taking right efforts to learn it, and has difficulty in making changes to the code.

Good Programs are good for similar reasons like simplicity, readability, and efficiency.
Every Bad Program is bad for its own reason.

Good Programming Concepts outlast the life of a programmer.
Bad Programming Concepts die with the programmer.

MATLAB主动噪声和振动控制算法——对较大的次级路径变化具有鲁棒性内容概要:本文主要介绍了一种在MATLAB环境下实现的主动噪声和振动控制算法,该算法针对较大的次级路径变化具有较强的鲁棒性。文中详细阐述了算法的设计原理与实现方法,重点解决了传统控制系统中因次级路径动态变化导致性能下降的问题。通过引入自适应机制和鲁棒控制策略,提升了系统在复杂环境下的稳定性和控制精度,适用于需要高精度噪声与振动抑制的实际工程场景。此外,文档还列举了多个MATLAB仿真实例及相关科研技术服务内容,涵盖信号处理、智能优化、机器学习等多个交叉领域。; 适合人群:具备一定MATLAB编程基础和控制系统理论知识的科研人员及工程技术人员,尤其适合从事噪声与振动控制、信号处理、自动化等相关领域的研究生和工程师。; 使用场景及目标:①应用于汽车、航空航天、精密仪器等对噪声和振动敏感的工业领域;②用于提升现有主动控制系统对参数变化的适应能力;③为相关科研项目提供算法验证与仿真平台支持; 阅读建议:建议读者结合提供的MATLAB代码进行仿真实验,深入理解算法在不同次级路径条件下的响应特性,并可通过调整控制参数进一步探究其鲁棒性边界。同时可参考文档中列出的相关技术案例拓展应用场景。
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