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Ever since Valorant's official launch, the shooter hasn't seen as many error codes as it's closed beta did.
From error code 12 to 46, 7, and 40, Valorant's closed beta was subject to a lot of scrutiny because of all the errors that ruined a player's day.
Now, even though the errors are not as recurrent after Valorant's official launch as they used to be, there are a few bugs here and there that recur, and error code 68 has become one of the most persistent ones.
So if you're facing this error code, then we have the perfect guide to fix it.
What is error code 68 in Valorant?
Error code 68 arises when the Valorant client is experiencing connection issues with the servers, and it can either be a fault from your end or on Riot's, more specifically Cloudflare's end, which is Valorant's DDoS protection provider.
If the fault is at your end:
If error code 68 is happening because of an internet issue from your end, here are a few things you can do to fix it:
1. Restarting the game
Restarting the Valorant client will fix almost every error code, and the same goes for error code 68. Edgeview 2 2 24. So try logging out and back into the game to see if it fixes the issue.
2. Restarting your computer
Even though error code 68 is primarily a network issue, Valorant's anti-cheat software Vanguard can be the real culprit behind it. To fix any problem related to the Vanguard, a quick PC reboot is the best solution.
3. Checking your network connection.
As error 68 is a server connection issue, the problem might just be with your router and internet connection. So restarting your router and checking your internet connection might just be able to do the trick.
4. Contact Riot's support desk.
Riot has a promising support team, who give out prompt replies to complaints and queries. Hence, you can go to Riot's support page for Valorant and lodge your complaints.
If the problem is at the end of Cloudflare:
Now, Cloudflare being the root of the error code 68 problem has a very high possibility, and their servers have recently undergone a lot of outages, leading to a lot of games, websites, and services crashing.
So, if error code 68 is happening because of them, then all you have to do is wait it out.
How to achieve clean structures, readability and maintainability
Refactorable code is mandatory to react to changing requirements, adding new features, integrating user feedback, but also tuning performance, getting rid of old, redundant code and making the source code more readable.
But what is refactorable code? In my eyes, a code base is refactorable if a developer can confidently read, understand and then either extend the application as in adding new features or reduce it by eliminating lines of code. This goes beyond the extend which I assumed a refactorable code base to be before: reducing technical debt. It is part of it, but by far not all!
During the last year it became obvious to me that the three following tools and practises are my corner stones when trying to achieve refactrobility:
- Unit tests
- Clean Code
- Proper code commits
In this post, I will focus on unit tests the most, but I want to make clear that the other two can be just as important and might appear in another post in more detail ;-)
Unit tests can help overcome and prevent many bad coding practises and instead enforce better or even best practises on your code, while yielding other benefits for free.
Messy internal code structure
One example where unit tests can help recognize and eliminate problems, is messy internal code structure. Some of the attributes of bad internal code are:
- Deeply nested code
- Many dependencies (for a class or a method)
Imagine the following example: You have an application that produces PDFs based on some content. So far, your application has one method writePdf which gets all the information it needs to produce the PDF. Now, imagine you requested to add a header to each PDF page created, which contains the name of the board of directors and thus is mission critical! The business logic for the formatting and the content of the header is super complex: You face over 20 possible edge cases and non must go wrong — this is mission critical!
You come to realize that you can never test all these edge cases by hand and thus want to apply unit tests to do it for you. You quickly see a few problems:
- I need to mock all the other input parameters of writePdf()
- I need to ensure all other values are set correctly to reach my new code
- The unit tests for the header are all part of the parent PdfWriter class
Creating the tests feels terrible, a lot of overhead is needed and it looks super heavy and hacky! This might be the first time you recognize how messy the APIs and classes actually are — by seeing your own code from a distance! To overcome this, you have to break your code apart and separate it into different scopes, which might end up looking similar to this:
What happened? The sub tasks of creating the footer, the metadata and other parts of the PDF moved into dedicated classes. Same goes for your header data, which now offers a single public method. And this is like christmas for your unit tests: You can write unit tests dedicated for this class and method, no need to provide all these dependencies, only necessary parameters are required to be given and the output can be described in a lot more detail. Writing the unit tests forced you to re-structure your code and apply a clear separation of concerns, which will be highly benefitial for future changes and add-ons.
Thinking broader
Now that you have the freedom to write small, dedicated unit tests you come to realize how much there is to test about a particular function or part of your code. Did you think about exceptions? How is the user notified when an errors occurs? What about invalid inputs like null, undefined or empty strings? You might check the following snippet for null, empty string and blank string, non-digit inputs and keep i18n in mind in regards to decimal separators.
Development speed
Now you might question the points above, especially under consideration of possible time constraints in your project. And yes, you are right: Writing tests takes time, you need to learn how to properly do that too. But the investment in absolutely worth it as it will quickly pay out. I see the following 3 points to be arguments in big favor of writing tests:
- Define once — run repeatedly
- No manual debugging or console printing
- All tests green means the feature is done
Let's go back to the example with the PDF header above that is now well tested. These tests will not disappear anymore, they are here to stay! Everytime someone now changes the functionality of the PDF header, the tests will quickly provide feedback to know when things break and they do so in a speaking way: Each test has a method name, maybe a description, clearly defined inputs and outputs. On a technical (and maybe even functional) level, this is a well-documented feature now! Other developers get a clear message on what broke and why, which enables them to fix the issue.
Keep It 1 68 Cent
On top of that, these checks are executed automatically. There is simply no need for you to set breakpoints across the application or print something to console in order to check specific variable values. You'll save a lot of time here across the length of a project.
Finally, specifically if you think in a test-driven development approach, it's valid to say that a feature is complete when all the tests are passing. You will only miss those cases, that you forgot to write tests for. Everything else is now clearly documented and checked automatically within seconds.
- I need to mock all the other input parameters of writePdf()
- I need to ensure all other values are set correctly to reach my new code
- The unit tests for the header are all part of the parent PdfWriter class
Creating the tests feels terrible, a lot of overhead is needed and it looks super heavy and hacky! This might be the first time you recognize how messy the APIs and classes actually are — by seeing your own code from a distance! To overcome this, you have to break your code apart and separate it into different scopes, which might end up looking similar to this:
What happened? The sub tasks of creating the footer, the metadata and other parts of the PDF moved into dedicated classes. Same goes for your header data, which now offers a single public method. And this is like christmas for your unit tests: You can write unit tests dedicated for this class and method, no need to provide all these dependencies, only necessary parameters are required to be given and the output can be described in a lot more detail. Writing the unit tests forced you to re-structure your code and apply a clear separation of concerns, which will be highly benefitial for future changes and add-ons.
Thinking broader
Now that you have the freedom to write small, dedicated unit tests you come to realize how much there is to test about a particular function or part of your code. Did you think about exceptions? How is the user notified when an errors occurs? What about invalid inputs like null, undefined or empty strings? You might check the following snippet for null, empty string and blank string, non-digit inputs and keep i18n in mind in regards to decimal separators.
Development speed
Now you might question the points above, especially under consideration of possible time constraints in your project. And yes, you are right: Writing tests takes time, you need to learn how to properly do that too. But the investment in absolutely worth it as it will quickly pay out. I see the following 3 points to be arguments in big favor of writing tests:
- Define once — run repeatedly
- No manual debugging or console printing
- All tests green means the feature is done
Let's go back to the example with the PDF header above that is now well tested. These tests will not disappear anymore, they are here to stay! Everytime someone now changes the functionality of the PDF header, the tests will quickly provide feedback to know when things break and they do so in a speaking way: Each test has a method name, maybe a description, clearly defined inputs and outputs. On a technical (and maybe even functional) level, this is a well-documented feature now! Other developers get a clear message on what broke and why, which enables them to fix the issue.
Keep It 1 68 Cent
On top of that, these checks are executed automatically. There is simply no need for you to set breakpoints across the application or print something to console in order to check specific variable values. You'll save a lot of time here across the length of a project.
Finally, specifically if you think in a test-driven development approach, it's valid to say that a feature is complete when all the tests are passing. You will only miss those cases, that you forgot to write tests for. Everything else is now clearly documented and checked automatically within seconds.
By now you'll have a well-tested and technically documented code base on the lowest level, which however can still be hard to read and understand for other developers, thus preventing them from adjusting it with confidence. From pratical experience and Uncle Bobs 'Clean Code' I took away these 3 major points about clean coding:
- Separation of concerns
- Speaking names
- ‘It works' is not enough
Keep It 1 68 Online
We've seen the separation of concerns already when we talked about messy internal code. This is where both topics go hand in hand and actually support one another. Thinking about what a class is meant to do and the scope of this task is a critical part of writing software as it will help to break down complex features into substeps in clearly defined chunks with proper interfaces to other parts of the application. If you now, on top of that, implement speaking names for classes, methods and variables, your code can be read like proper sentences. This makes it easier for fellow developers to read and understand your code in order to adjust it with more confidence!
For me personally, wrapping if statements into methods is one of the best examples for the improved readability as it makes your code more expressive. Check the following two examples and try to read them from top-to-botton:
The second example contains a lot more code, I agree. But it's a trade I am willing to make in almost all cases. I always just read over the public method first to get an idea of what it's doing and proper if-methods that I can just read definetly help to achieve that.
Keep It 1 68 Hour
Finally, the third statement is something I try to shift to as much as possible. Defending bad code with 'but it works' and pushing code into common branches with a mind set of 'it works, I'm done' is like an architect that designs your house, but doesn't insert windows. It works, you can sleep in there, but it will take a lot of effort from you to keep it warm, dry and clean.
Making code work can surely be your personal first goal when working on a feature, but it should not be the last. Did you think about all edge cases we discussed above? Can you make methods and variables more expressive? Are there still ToDos in the code or comments you made? Can classes be separated better, can redundant code be removed? Clean up your work in progess instead of pushing that burding onto someone else in the distant future as it might even be yourself.
As the last topic, I want to talk about proper code commits to source code repositories. For me, this includes the following attributes:
- Each and every commit is deployable
- A commit is well-scoped
- A commit tells about its reason
Every commit you and your team mates make should be deployable and thus be compilable, pass all tests and finally be able to start on the server or the client. This enables automated pipelines and deployments to shine as in case of error, a rollback is at hand and quickly running. The commit might not be feature complete from a business perspective and that is fine. Otherwise you will break the second point, well-scoped commits.
A commit should have a limited scope, like handling only one of multiple parts of a feature. The reason for this is simple and of great benefit for you personally: Think of a commit as a checkpoint in a game. You work on a new feature, have different approaches in mind and start with the first one. Quickly you realize that this approach does not work as intended and you want to start from the last checkpoint. If this is severals hours or even days back, it will be tough to re-create the state of this checkpoint. If however the checkpoint is just a few changes away, you can simply drop all the work in progress and try another approach.
Finally, a commit adds documentation to your code base and in some terms does it better than any code comment or method/class name could: It can explain where you come from, WHY you did a certain change, what problems you might have faced, what flaws the code has and so on. It is one great way to spread knowledge within the team without the need to do actual knowledge transfer meetings. Leverage this feature and creating speaking commit messages!
Applying the 3 practises of unit testing, clean code and commit-scoping can make your code more refactorable.
Clean code makes the code approachable through expressive names, clear structure and proper craftmanship. Unit tests constantly provide feedback on your changes with clear, detailed documentation on what failed why. And finally, well-scoped commits not only keep you from swearing in case you want to jump back to a previous checkpoint, but also allow for rollbacks and offer a unique opportunity to document the why and what of your changes.
Keep It 1 68 Years
Use these 3 practises daily to boost the confidence of your teammates and yourself when working on a software project.
