Refactor whenever you see the need and have the chance. Programming is about abstractions, and the closer your abstractions map to the problem domain, the easier your code is to understand and maintain. As systems grow organically, they need to change structure for their expanding use case. Systems outgrow their abstractions and structure, and not changing them becomes technical debt that is more painful and slower and more buggy to work around.
Include the cost of clearing technical debt refactoring within the estimates for feature work. The longer you leave the debt around, the higher the interest it accumulates. Make code correct first and fast second.
When working on performance issues, always profile before making fixes. Usually the bottleneck is not quite where you thought it was. With the usual note that adding timing code always changes the performance characteristics of the code, making performance work one of the more frustrating tasks.
Smaller, more tightly scoped unit tests give more valuable information when they fail—they tell you specifically what is wrong. A test that stands up half the system to test behavior takes more investigation to determine what is wrong. Generally a test that takes more than 0. With tightly scoped unit tests testing behavior, your tests act as a de facto specification for your code.
Ideally if someone wants to understand your code, they should be able to turn to the test suite as "documentation" for the behavior.
On the other hand, code is the enemy, and owning more code than necessary is bad. Consider the trade-off when introducing a new dependency. Shared code ownership is the goal; siloed knowledge is bad. At a minimum, this means discussing or documenting design decisions and important implementation decisions. Code review is the worst time to start discussing design decisions as the inertia to make sweeping changes after code has been written is hard to overcome. Generators rock! Programming is a balancing act, however.
Over-engineering onion architecture is as painful to work with as under-designed code. Design Patterns is a classic programming book that every engineer should read. Fixing or deleting intermittently failing tests is painful, but worth the effort. Generally, particularly in tests, wait for a specific change rather than sleeping for an arbitrary amount of time.
Voodoo sleeps are hard to understand and slow down your test suite. Always see your test fail at least once. Put a deliberate bug in and make sure it fails, or run the test before the behavior under test is complete. And finally, a point for management: Constant feature grind is a terrible way to develop software. Not addressing technical debt slows down development and results in a worse, more buggy product.
Thanks to the Ansible team, and especially to Wayne Witzel , for comments and suggestions for improving the principles suggested in this list. Want to break free from the IT processes and complexities holding you back from peak performance?
Download this free eBook: Teaching an elephant to dance. The idea of comments degenerating over time into "lies" is one that I agree with. At one former job, working alongside the esteemed Mr Foord the article author , we were all in the habit of simply referring to all comments as "lies", without forethought or malice. As in "The module has some lies at the top explaining that behaviour. This is like saying that new tires end up being worn out, so drive only on smooth roads and only downhill, so you don't have to use tires.
Lazy developers find excuses for not writing comments. The fact is that there is no such thing as perfectly readable code. What's readable to one person is a complete ball of mud to others. To force someone to read code just as a form of documentation is an irresponsible idea that is inefficient and assumes that only developers of a certain level should be looking at your code.
I don't understand what you are saying in point number 2 - the first sentence, "tests don't need testing" seems to stand in contradiction to point A map without a legend and labels is "readable and self-documenting" but unnecessary torture.
Comment the start and end of logic blocks and loops. Comment "returns" with values. If you don't like comments, a good editor will strip the lies from your eyes. Every software developer should read this article.
How to deploy an application varies widely within the Bureau, and there is no one way that will suit every situation.
Deployment is related to the practice of DevOps, an efficient process for production level maintenance and deployment of software. DevOps is a complex process often requiring an established team effort and computing infrastructure meeting required USGS security controls. There are a number of best practices that should be followed whether the software will be deployed to local on-premise infrastructure, shared infrastructure, or a cloud hosting environment.
The best practices below represent the fundamental concepts of how to deploy code on FITARA compliant systems, for more advanced information, many educational resources are available on the web for industry standard techniques and technologies that assist in the deployment process. Your deployment environment may dictate which of these tools and techniques is most useful to your project. For more information, contact CHS cloudservices usgs. A principle best practice is to fully understand your deployment workflow to encourage efficient application deployment and updates.
The best practices below help achieve reliable and repeatable code deployment. Write down every step required to deploy code to your various environments to create a checklist. This list will ensure that nothing is forgotten and also serves as an excellent starting point to identify opportunities for improvement in your deployment process. The checklist should reference locations and helper scripts, commands and steps needed to deploy the application, sign-offs for release, and collaborators who need to be notified of updated releases.
Along with the deployment checklist should be a rollback checklist of what to do if things do not go as planned. The checklist should provide the steps to return the application to a previous working state. When people manually perform repeated tasks, errors are often introduced by mistake.
Automation is a best practice to reduce error. Automation can be achieved by simple or sophisticated tooling depending on your requirements. The variety of automation options and best practices can be an intimidating subject, the most important thing to keep in mind is to understand your own process and improve it with automation over time. Any project could benefit from an automated solution like a script that encapsulates the deployment checklist and may include prompts for deploying an application to a server.
Additional automated tools and solutions are available as well. For example, enterprise Development and Operations DevOps teams may use a number of enterprise tools including but not limited to: configuration management e.
While not a deployment requirement, using continuous integration will result in higher quality and more reliable code through risk mitigation, code confidence, team communication, and consistency of process. Code is automatically pulled from the repository and built on a server of a known and consistent configuration. When code is deployed to a runtime environment, it is always pulled from the object store. This ensures consistent versions of applications and libraries are deployed to each system appropriately.
If you are connecting to resources such as databases, you should store the configuration information, such as the specific database connection information, separate from the application. The application should bind with configuration information at runtime. The goal is to build the application code without having to include configuration information in the code itself. You could have more or fewer environments set up, for instance, some people prefer to have a Pre-production environment to further test the code before the final deployment to Production, and others maintain separate Staging and QA environments where developers perform further tests e.
If you've read this far, Version Control is obviously an issue for you. However, if you need to update more than one server, automation makes sense.
This is exactly what we offer with DeployBot. DeployBot integrates perfectly with the most popular tech. Learn how to get started with DeployBot here. As mentioned, one of the main reasons for maintaining multiple environments in your Software Development Life Cycle is to ensure that the final version of the product that gets deployed to users is as bug-free as possible. Other than this, there are some other advantages that using multiple environments offers that not only improves a team's overall workflow, but also helps them meet their business goals:.
DeployBot can help you easily set up and manage your development environments. First, you connect your git repositories to DeployBot and add users that can view the repositories and run deployments. After adding a repository, you can then set up your environment. You can have multiple environments to a single repository. You can associate a specific branch of your repository to a particular environment and set the environment's Deployment Mode to either Manual or Automatic.
0コメント