The Longevity of Interim Solutions

本文探讨了在软件开发中创建临时解决方案的原因及影响。通常这些方案为了解决紧迫问题而诞生,尽管它们不符合长期标准,但因为有用且被广泛接受而常常成为永久方案。

Why do we create interim solutions?

Typically there is some immediate problem to solve. It might be internal to the development team, some tooling that fills a gap in the tool chain. It might be external, visible to end users, such as a workaround that addresses missing functionality.

In most systems and teams you will find some software that is somewhat dis-integrated from the system, that is considered a draft to be changed sometime, that does not follow the standards and guidelines that shaped the rest of the code. Inevitably you will hear developers complaining about these. The reasons for their creation are many and varied, but the key to an interim solution's success is simple: It is useful.

Interim solutions, however, acquire inertia (or momentum, depending on your point of view). Because they are there, ultimately useful and widely accepted, there is no immediate need to do anything else. Whenever a stakeholder has to decide what action adds the most value, there will be many that are ranked higher than proper integration of an interim solution. Why? Because it is there, it works, and it is accepted. The only perceived downside is that it does not follow the chosen standards and guidelines — except for a few niche markets, this is not considered to be a significant force.

So the interim solution remains in place. Forever.

And if problems arise with that interim solution, it is unlikely there will be provision for an update that brings it into line with accepted production quality. What to do? A quick interim update on that interim solution often does the job. And will most likely be well received. It exhibits the same strengths as the initial interim solution... it is just more up to date.

Is this a problem?

The answer depends on your project, and on your personal stake in the production code standards. When the systems contains too many interim solutions, its entropy or internal complexity grows and its maintainability decreases. However, this is probably the wrong question to ask first. Remember that we are talking about a solution. It may not be your preferred solution — it is unlikely to be anyone's preferred solution — but the motivation to rework this solution is weak.

So what can we do if we see a problem?

  1. Avoid creating an interim solution in the first place.
  2. Change the forces that influence the decision of the project manager.
  3. Leave it as is.

Let's examine these options more closely:

  1. Avoidance does not work in most places. There is an actual problem to solve, and the standards have turned out to be too restrictive. You might spend some energy trying to change the standards. An honorable albeit tedious endeavor... and that change will not be effective in time for your problem at hand.
  2. The forces are rooted in the project culture, which resists volitional change. It could be successful in very small projects — especially if it's just you — and you just happen to clean the mess without asking in advance. It could also be successful if the project is such a mess that it is visibly stalled and some time for cleaning up is commonly accepted.
  3. The status quo automatically applies if the previous option does not.

You will create many solutions, some of them will be interim, most of them will be useful. The best way to overcome interim solutions is to make them superfluous, to provide a more elegant and useful solution. May you be granted the serenity to accept the things you cannot change, courage to change the things you can, and wisdom to know the difference.

By Klaus Marquardt


This work is licensed under a Creative Commons Attribution 3

标题基于Python的自主学习系统后端设计与实现AI更换标题第1章引言介绍自主学习系统的研究背景、意义、现状以及本文的研究方法和创新点。1.1研究背景与意义阐述自主学习系统在教育技术领域的重要性和应用价值。1.2国内外研究现状分析国内外在自主学习系统后端技术方面的研究进展。1.3研究方法与创新点概述本文采用Python技术栈的设计方法和系统创新点。第2章相关理论与技术总结自主学习系统后端开发的相关理论和技术基础。2.1自主学习系统理论阐述自主学习系统的定义、特征和理论基础。2.2Python后端技术栈介绍DjangoFlask等Python后端框架及其适用场景。2.3数据库技术讨论关系型和非关系型数据库在系统中的应用方案。第3章系统设计与实现详细介绍自主学习系统后端的设计方案和实现过程。3.1系统架构设计提出基于微服务的系统架构设计方案。3.2核心模块设计详细说明用户管理、学习资源管理、进度跟踪等核心模块设计。3.3关键技术实现阐述个性化推荐算法、学习行为分析等关键技术的实现。第4章系统测试与评估对系统进行功能测试和性能评估。4.1测试环境与方法介绍测试环境配置和采用的测试方法。4.2功能测试结果展示各功能模块的测试结果和问题修复情况。4.3性能评估分析分析系统在高并发等场景下的性能表现。第5章结论与展望总结研究成果并提出未来改进方向。5.1研究结论概括系统设计的主要成果和技术创新。5.2未来展望指出系统局限性并提出后续优化方向。
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