green coding

A look at green coding

Green coding is a software development concept whose goal is to create programs with minimal energy consumption.

What is green coding?

Green coding is a programming concept aimed at developing software that is as environmentally friendly as possible . Background: Due to the advancement of digitalization, software development services play an increasingly important role in almost all areas of life. Power-intensive software contributes significantly to greenhouse gas emissions. Green coding is a solution.

The central pillar of green coding is not only about energy optimization of software, but also about more sustainable software development that, for example, uses renewable energy to power data centers or cloud systems.

How does green coding work?

Green coding is applied to all levels of the software development process : both the software architecture and its development approach and other additional factors can be optimized. In green programs, convoluted and poorly optimized code should be avoided. The reason is simple: poorly optimized code usually executes instructions that are not essential for the program’s logic, which causes unnecessary consumption of resources and, therefore, a waste of energy .

In the context of green coding, we often talk about the “green coding pillars”, which constitute the basis of more sustainable software.

Pillars of green coding

Green programming is based on four pillars. Each of them is essential for the custom software development service process, and offers the possibility of saving resources and emissions.

Green architecture

Software architecture is the first pillar. The architecture is the basic structure of the applications to be programmed . It can be optimized especially in terms of energy consumption: for example, the code can be packaged in such a way that optimal use of the hardware is achieved at all times and, therefore, less energy is required. Automatic shutdown systems that activate when the software is not in use are also part of the green architecture and contribute significantly to reducing the energy consumption of applications.

Green logic

Another fundamental pillar of green coding is program logic. In essence, it is about optimizing the program code so that its use is not slowed down by unnecessary statements. Other factors, such as choosing more efficient data structures or resource-saving file formats, also play an important role in writing efficient and environmentally friendly program code.

Green methodology

The methodology is a pillar of green programming that focuses less on the program code and more on the custom software development company . As an example, agile development is a method specifically designed to adapt code and applications to energy efficiency. The phased development and testing of agile programming ensures that program components with poor energy efficiency can be identified and modified at an early stage , so that the final product is as energy efficient as possible. .

Green platform

Green coding not only has to do with software, but also with hardware , from which there are a series of starting points that can be used to achieve systems that respect the environment more. Specifically, the use of servers is a factor that affects resource consumption: servers that operate with low load consume more energy than necessary. Cloud computing can remedy the hardware situation, as resources can be flexibly scaled and adapted to individual needs. In an ideal case, the energy needs of cloud computing servers are covered with renewable energy .

Energy efficient programming languages

The software design is not the only thing that affects the energy efficiency of the final product: the programming language chosen to carry out the project is also very important. Different programming languages ​​differ greatly in their resource consumption in terms of energy, memory and time.

C is the most energy efficient programming language . This fact is not surprising, since C is a hardware-oriented programming language and works at a low level of abstraction so that hardware resources can be used efficiently. Direct memory management is also a determining factor in the efficiency of C, as it allows programmers to develop efficient strategies for allocating and freeing memory (memory reservation). The C++ language is based on C, but it is object-oriented and also extremely resource efficient.

Analogous to C, Rust is a programming language well suited to green coding. Rust is a relatively young programming language, with a memory management system that allows efficient access to it. In this way, unnecessary accesses, which consume a lot of energy, are avoided. The high degree of concurrency that Rust allows is also a fundamental factor for energy efficiency, so that hardware resources are made the most of.

What may surprise you is that Python , despite being one of the most popular programming languages, scores extremely low in its energy efficiency rating . One reason is that Python programs at run time are only interpreted and not compiled , so there is no single compilation process. However, dynamic language typing also leads to increased program execution time, since variable types are determined dynamically during program execution. For similar reasons, JavaScript is also not very energy efficient and is therefore rather unsuitable for green coding.

Good green coding practices

There are a number of good practices you can follow during the process of developing your programs if you want them to be greener in the future.

  • Intelligent software architecture – avoids redundant and unnecessary code. Avoid loops and, if necessary, incorporate mechanisms that automatically end the program when it is not being used.
  • Choosing programming language : Choose a programming language for your project that is efficient from an energy perspective.
  • Continuous testing : Test the components of your project in stages during development and identify components that require a high amount of resources.
  • Data and networks : Reduce data consumption and the distance it has to travel on the network through, for example, caching.


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