A Message to the Future

本文探讨了编程中代码的美感与理解性之间的关系,通过一个具体的例子,强调了编写易于理解、维护性高的代码的重要性。文章提出将每行代码视为未来某位开发者(可能是当前作者的弟弟或其他开发者)的指南,鼓励作者用简洁、优雅的代码风格进行编程,以提升代码的可读性和可维护性。

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Maybe it's because most of them are smart people, but in all the years I've taught and worked side-by-side with programmers, it seems that most of them thought that since the problems they were struggling with were difficult that the solutions should be just as difficult for everyone (maybe even for themselves a few months after the code was written) to understand and maintain.

I remember one incident with Joe, a student in my data structures class, who had to come in to show me what he'd written. "Betcha can't guess what it does!" he crowed.

"You're right," I agreed without spending too much time on his example and wondering how to get an important message across. "I'm sure you've been working hard on this. I wonder, though, if you haven't forgotten something important. Say, Joe, don't you have a younger brother?"

"Yep. Sure do! Phil! He's in your Intro class. He's learning to program, too!" Joe announced proudly.

"That's great," I replied. "I wonder if he could read this code."

"No way!" said Joe. "This is hard stuff!"

"Just suppose," I suggested, "that this was real working code and that in a few years Phil was hired to make a maintenance update. What have you done for him?" Joe just stared at me blinking. "We know that Phil is really smart, right?" Joe nodded. "And I hate to say it, but I'm pretty smart, too!" Joe grinned. "So if I can't easily understand what you've done here and your very smart younger brother will likely puzzle over this, what does that mean about what you've written?" Joe looked at his code a little differently it seemed to me. "How about this," I suggested in my best 'I'm your friendly mentor' voice, "Think of every line of code you write as a message for someone in the future — someone who might be your younger brother. Pretend you're explaining to this smart person how to solve this tough problem.

"Is this what you'd like to imagine? That the smart programmer in the future would see your code and say, 'Wow! This is great! I can understand perfectly what's been done here and I'm amazed at what an elegant — no, wait — what a beautiful piece of code this is. I'm going to show the other folks on my team. This is a masterpiece!'

"Joe, do you think you can write code that solves this difficult problem but will be so beautiful it will sing? Yes, just like a haunting melody. I think that anyone who can come up with the very difficult solution you have here could also write something beautiful. Hmm... I wonder if I should start grading on beauty? What do you think, Joe?"

Joe picked up his work and looked at me, a little smile creeping across his face. "I got it, prof, I'm off to make the world better for Phil. Thanks."

By Linda Rising

This work is licensed under a Creative Commons Attribution 3

内容概要:该PPT详细介绍了企业架构设计的方法论,涵盖业务架构、数据架构、应用架构和技术架构四大核心模块。首先分析了企业架构现状,包括业务、数据、应用和技术四大架构的内容和关系,明确了企业架构设计的重要性。接着,阐述了新版企业架构总体框架(CSG-EAF 2.0)的形成过程,强调其融合了传统架构设计(TOGAF)和领域驱动设计(DDD)的优势,以适应数字化转型需求。业务架构部分通过梳理企业级和专业级价值流,细化业务能力、流程和对象,确保业务战略的有效落地。数据架构部分则遵循五大原则,确保数据的准确、一致和高效使用。应用架构方面,提出了分层解耦和服务化的设计原则,以提高灵活性和响应速度。最后,技术架构部分围绕技术框架、组件、平台和部署节点进行了详细设计,确保技术架构的稳定性和扩展性。 适合人群:适用于具有一定企业架构设计经验的IT架构师、项目经理和业务分析师,特别是那些希望深入了解如何将企业架构设计与数字化转型相结合的专业人士。 使用场景及目标:①帮助企业和组织梳理业务流程,优化业务能力,实现战略目标;②指导数据管理和应用开发,确保数据的一致性和应用的高效性;③为技术选型和系统部署提供科学依据,确保技术架构的稳定性和扩展性。 阅读建议:此资源内容详尽,涵盖企业架构设计的各个方面。建议读者在学习过程中,结合实际案例进行理解和实践,重点关注各架构模块之间的关联和协同,以便更好地应用于实际工作中。
资 源 简 介 独立分量分析(Independent Component Analysis,简称ICA)是近二十年来逐渐发展起来的一种盲信号分离方法。它是一种统计方法,其目的是从由传感器收集到的混合信号中分离相互独立的源信号,使得这些分离出来的源信号之间尽可能独立。它在语音识别、电信和医学信号处理等信号处理方面有着广泛的应用,目前已成为盲信号处理,人工神经网络等研究领域中的一个研究热点。本文简要的阐述了ICA的发展、应用和现状,详细地论述了ICA的原理及实现过程,系统地介绍了目前几种主要ICA算法以及它们之间的内在联系, 详 情 说 明 独立分量分析(Independent Component Analysis,简称ICA)是近二十年来逐渐发展起来的一种盲信号分离方法。它是一种统计方法,其目的是从由传感器收集到的混合信号中分离相互独立的源信号,使得这些分离出来的源信号之间尽可能独立。它在语音识别、电信和医学信号处理等信号处理方面有着广泛的应用,目前已成为盲信号处理,人工神经网络等研究领域中的一个研究热点。 本文简要的阐述了ICA的发展、应用和现状,详细地论述了ICA的原理及实现过程,系统地介绍了目前几种主要ICA算法以及它们之间的内在联系,在此基础上重点分析了一种快速ICA实现算法一FastICA。物质的非线性荧光谱信号可以看成是由多个相互独立的源信号组合成的混合信号,而这些独立的源信号可以看成是光谱的特征信号。为了更好的了解光谱信号的特征,本文利用独立分量分析的思想和方法,提出了利用FastICA算法提取光谱信号的特征的方案,并进行了详细的仿真实验。 此外,我们还进行了进一步的研究,探索了其他可能的ICA应用领域,如音乐信号处理、图像处理以及金融数据分析等。通过在这些领域中的实验和应用,我们发现ICA在提取信号特征、降噪和信号分离等方面具有广泛的潜力和应用前景。
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