Category Programming

The memory wall problem refers to a phenomenon that occurs in computer architecture when the processor’s speed outpaces the rate at which data can be transferred to and from the memory system. As a result, the processor must wait for the data to be fetched from memory, which slows down its performance and limits its speed. The memory wall problem has become increasingly significant as processors have become faster and more powerful while memory speeds have not kept pace with these advancements.

The else keyword is a commonly used control structure in programming. It allows us to execute a block of code if a condition is not true. However, overusing else statements can lead to less readable and maintainable code. In this article, we’ll explore why we should avoid using else clauses in our code and look at some alternatives that can make our code more concise and readable. Why Overusing else is a Bad Idea One of the main arguments against using else statements is that they can make our code more complex and harder to read.

There are many practices and tactics that tackle testing. Today, I’ll share with you how I write tests for my projects. Please notice that you may find it useful when starting a new project or an independent part of existing applications. You may find it difficult to apply in an already existing application. It’s not impossible but it may be challenging. Table of content General rules for tests Works out of the box Single responsible As simple as possible Irrelevant code should be extracted How does the architecture of the package look like?

I like having the core logic of our application free of distractions like too many technical “details” like logging or generating metrics. Of course, sometimes it’s hard to avoid it. I found in many projects a situation where we put the logger very deeply inside of the code. At the end of the day, we had the logger almost everywhere. In tests, we had to provide the mocked implementation everywhere as well.

Sometimes, we may want to use a library but a slightly modified version. It happens very often when we develop the library but test it in the context of an application. Go has a handy mechanism in go modules that can help us with it. To make it work, we have to clone the library somewhere near the target project and run the following command in the application’s folder. go mod edit -replace github.

gRPC supports authentication. Adding it to your project is simple. All you have to do is configure it with just a few lines of code. One of the authentication types that gRPC supports is SSL/TLS. From the server-side, the code looks like this: creds, err := credentials.NewServerTLSFromFile(certFile, keyFile) if err != nil { // handle the error - no ignore it! } s := grpc.NewServer(grpc.Creds(creds)) The client has to update the code as shown below.

Programs should be written for people to read, and only incidentally for machines to execute - Abelson and Sussman It is one of the most popular questions. You can find on the Internet attempts to answer this question. I’ve had concerns if I’m designing my packages or even the whole project correctly. Today, I’m not 100% sure about that! Some time ago, I had the pleasure to meet Robert Griesemer (one of Go’s authors) in person.

Writing linters is simple. I was surprised how it’s easy to write a Go linter. Today, we’ll write a linter that will calculate the cyclomatic complexity of the Go code. What is cyclomatic complexity? Cyclomatic complexity is a software metric used to indicate the complexity of a program. ref The idea is simple - every time we find any control flow statements we increase the complexity by one. I know I oversimplified it a bit but I don’t want to overwhelm you with unnecessary details.

The context package in Go is quite simple and well-known. On the other hand, there are some misunderstandings while using it. Today, I’ll try to explain all the most popular concerns and make more clear when and how use the Context. Let’s start with what the context is. Package context defines the Context type, which carries deadlines, cancellation signals, and other request-scoped values across API boundaries and between processes. ref: https://golang.

When I started my career as a software developer and published the first production application what I did was staring at logs and look for some fatal errors. It was a monolith application. Every log saying that something’s wrong had to be fixed. ASAP. This approach worked for some time. However, when the scale increased, and I started building microservices, I couldn’t get rid of all of them. Network issues, database failures, and more - it happens all the time.