“Green Coding” refers to an approach to software development whose objective is to create programming code with minimal energy consumption.
What is Green Coding?
Green Coding is a programming practice that aims to create software systems as eco-friendly as possible. For what ? Due to increasing digitalization, software plays an increasingly important role in almost all areas of daily life. However, software that consumes a lot of energy also contributes to greenhouse gas emissions. Green Coding helps resolve this dilemma.
The fundamental notion of Green Coding does not only consist of the energy optimization of software. It also includes the development of more sustainable software, which would for example use renewable energies to supply electricity to data centers or Cloud systems.
Green Coding constitutes only part of the efforts aimed at saving resources in Information and Communication Technologies. To find out more, see our article on Green IT.
Green Coding, how does it work?
Green Coding intervenes each level of the software development process : It is possible to optimize both the software architecture and the underlying development approach, as well as certain other factors. To avoid in green coding: confusing and poorly optimized code. Indeed, poorly optimized code tends to often execute instructions that are not strictly necessary for the logic of the program, with unnecessary access to resources and a waste of energy.
In the context of green coding, we often refer to the “Green Coding Pillars”, which form the basis of more sustainable software.
The pillars of Green Coding
Eco-responsible programming is based on four pillars. Each of these pillars is essential to the software development process and offers a lever for saving resources and emissions.
Greener architecture
The software architecture constitutes the first pillar. it’s about the basic structure of applications to program. This can be optimized, especially in terms of energy consumption: for example, it is possible to group the code in such a way as to guarantee optimal use of the hardware at all times and thus use less electricity. Automatic shutdown mechanisms when the software is not in use are also part of the so-called “green” architecture and contribute significantly to reducing the energy consumption of application programs.
A greener logic
Program logic is another pillar of Green Coding. It is mainly a question here optimize software code so that the application is not slowed down by unnecessary instructions. Other factors, such as choosing resource-efficient file formats or more efficient data structures, also play an important role in designing efficient, eco-friendly code.
A greener methodology
The methodology is a pillar of green coding which is more interested in software development process than the program code itself. Therefore, it is especially agile software development models that lend themselves to adapting code and applications with energy efficiency in mind. Small-scale development and testing as part of agile programming makes it possible toidentify and modify at an early stage program elements that are not energy efficient enough. Ultimately, the final product must be as energy-efficient as possible.
A greener platform
Green Coding does not only affect software, it also concerns material. In this area, certain prerequisites make it possible to guarantee more ecological systems as a whole. Server load, in particular, is a factor with a strong impact on resource consumption: servers running at low load consume more electricity than necessary. The Cloud computing solution also exists: resources are then scaled in a modular manner and adapted to individual needs. Ideally, the energy needs of cloud computing servers are covered by so-called renewable energies.
Energy efficient languages
Software design is not the only element that influences the energy efficiency of the final product. The choice of the project’s programming language is also decisive. We see that the different programming languages differ greatly in terms of consumption of energy, memory and time resources.
The programming language the most energy efficient is the C language. This is no surprise: C is a low-level programming language (which works with a low level of abstraction), which allows hardware resources to be used as efficiently as possible. Its direct memory management is also an important factor in the efficiency of the C language, because it allows programmers to develop efficient memory allocation and restitution strategies. The C++ object-oriented language, based on C, is also very resource-efficient.
Besides the C language, Rust is another programming language that lends itself well to Green Coding. Relatively young, Rust has the advantage to access memory efficiently thanks to its controlled management method. It helps avoid unnecessary and energy-consuming memory accesses. Its high degree of parallelization is also an essential factor in its energy efficiency because it uses hardware resources optimally.
A surprise in this comparison: the Python language, which is one of the most popular programming languages, obtains a extremely low score in energy efficiency ranking. This is explained on the one hand by the fact that programs in Python are interpreted and not compiled at the time of their execution, without going through a single compilation process. But dynamic language typing also has the effect of increasing the execution time of programs. Indeed, variable types are determined dynamically at program execution time. For similar reasons, JavaScript is also quite energy inefficient and is not a prime candidate for Green Coding.
Green Coding: best practices
Do you also want to make your programs more eco-responsible? So here are some best practices to follow in the development process:
- Intelligent software architecture: avoid redundant and superfluous code, as well as unnecessary loops. If possible, include mechanisms that shut down the program when not in use
- Choice of programming language: choose a low-power programming language for your project
- Continuous testing: test your project components in small steps during development and identify resource-intensive elements
- Data and networks: reduce data consumption and network travel distance, for example by using caching
