The DATASTRUCTRUE homework --- 随笔啦

本文深入探讨了程序设计的核心原则,包括数据结构、算法选择、模块化设计、代码复用等,强调了大型项目中组织数据和算法的重要性,并提出了有效的编程方法论。同时,文章还讨论了使用C++进行编程的优势,以及如何通过C++来实现更高效、更清晰的代码。最后,总结了编程过程中的关键原则,如精确的预后条件、精心命名变量和函数、简洁明了的文档编写等。

The principles ofprogram design


Data Structuresaim to describe the programming methods and tools. As for a program, the biggerit is, the more difficult to solve the large problems.

Therefore, thereshould be a consistent、unified and logical approach, which shouldfollow the principles of program design.

When we started aprogram, first of all, we need think of the major problem we will meet, andtrying to make it more clear; And then find ways that can handle the problemefficiently as many as you can, in which you need to choose the best methodcarefully. Usually, we will separate the bigger problems into several smallerissues, which is much more convenient to program design for the programmers.

For the programdesign, many programmers believe the principle: “First make your program work,then make it pretty.” However, I give you my opinion that the above principlemay be effective for small programs, but not for the large ones. Each part of alarge program is supposed to be well-organized , clearly written, andthoroughly understood.

Even with verylarge projects, difficulties usually arise not from the inability to find asolution but, rather, from the fact that there can be so many different methodsand algorithms that might work that it can be hard to decide which is best,which may lead to programming difficulties, or which may be hopelesslyinefficient. The greatest room for variability in algorithm design is generallyin the way in which the data of the program are stored:

A. How they arearranged in relation to each other.

B. Which data arekept in memory.

C. Which arecalculated when needed.

D. Which are keptin files, and how the files are arranged.

When there areseveral different methods to organize data and device algorithms, it’s vital todevelop criteria to recommend a choice.

Testing andverification:  program correctness:

  a. Reduce the number of errors, making iteasier to spot those that remain.

  b. Enable us to verify in advance that ouralgorithm are correct.

  c. Provide us with ways to test our programsso that we can be reasonably confident that they will not misbehave.

Maintenance: Please see it thata large project be written to make it as easy as to understand and modify aspossible.

Using C++ toprogramming: We can learn from the features of C++, such as :

a.    Dataabstraction.

b.    Objected-orienteddesign.

c.     Thetop-down approach.

d.    Codereuse.

e.     C++improves on several of the inconvenient and dangerous aspects of C.

f.      C++maintains the efficiency that is the hallmark of the C language.

By the way, we getthose principle:

a.               Includeprecise preconditions and post conditions with every program, function, andmethod that you write.

b.               Alwaysname your classes, variables and functions with the greatest care, and explainthem thoroughly.

c.                Keepyour documentation concise but descriptive.

d.               Thereading time for programming is much more than the writing time.

e.                Don’tlose sight of the forest for its trees.

f.                 Useclasses to model the fundamental concepts of the program.

g.               Eachfunction should do only one task, but do it well.

h.               Eachclass or function should hide something.

i.                 Keepyour connections simple. Avoid global variables whenever possible.

j.                 If youmust use global variables as input, document them thoroughly.

 

内容概要:本文系统介绍了算术优化算法(AOA)的基本原理、核心思想及Python实现方法,并通过图像分割的实际案例展示了其应用价值。AOA是一种基于种群的元启发式算法,其核心思想来源于四则运算,利用乘除运算进行全局勘探,加减运算进行局部开发,通过数学优化器加速函数(MOA)和数学优化概率(MOP)动态控制搜索过程,在全局探索与局部开发之间实现平衡。文章详细解析了算法的初始化、勘探与开发阶段的更新策略,并提供了完整的Python代码实现,结合Rastrigin函数进行测试验证。进一步地,以Flask框架搭建前后端分离系统,将AOA应用于图像分割任务,展示了其在实际工程中的可行性与高效性。最后,通过收敛速度、寻优精度等指标评估算法性能,并提出自适应参数调整、模型优化和并行计算等改进策略。; 适合人群:具备一定Python编程基础和优化算法基础知识的高校学生、科研人员及工程技术人员,尤其适合从事人工智能、图像处理、智能优化等领域的从业者;; 使用场景及目标:①理解元启发式算法的设计思想与实现机制;②掌握AOA在函数优化、图像分割等实际问题中的建模与求解方法;③学习如何将优化算法集成到Web系统中实现工程化应用;④为算法性能评估与改进提供实践参考; 阅读建议:建议读者结合代码逐行调试,深入理解算法流程中MOA与MOP的作用机制,尝试在不同测试函数上运行算法以观察性能差异,并可进一步扩展图像分割模块,引入更复杂的预处理或后处理技术以提升分割效果。
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