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Well maintained projects tend to address bugs, as well as stability and security flaws, quickly and often.
In most cases this can be a deal breaker when it comes to choosing the correct components for your project,
as every developer aims for the best of the best.
We have developed a way to evaluate Open Source community projects by looking at how many times changes and updates are published
in their Open Source repositories.
The Maintenance Score is calculated by looking at the average time gap between one source code update and the other.
The smaller the gap, the higher the score.
In modern-day software development, security is the key to success.
By looking at the history of a component’s safety you can predict how likely it could be open to new threats in the future.
Our Safety Score is the result of a deep comparison of vulnerable component versions and safe versions.
The score is the result of a progressive calculation.
Starting from the latest version, we analyse the threat level of each prior version and deduct points in case of a
vulnerable version and add points in case of a safe version.
Open source components are great tools to help minimize time and resource consumption.
However, they do not come without their downsides. There are hundreds of thousands of components.
Although some of them are easy to use and well documented, most of them are not straightforward.
Popular components used by bigger communities typically make it easier to find a solution for the issue at hand.
The Popularity Score is the result of a rich analysis of the component usage and the size of the community.
The score is computed by comparing the size of its community (e.g., Github forks, number of watchers) with a coefficient of popularity.
New vulnerabilities are discovered every day. Continuous monitoring and detection is critical to keep the window of opportunity for malicious exploits as short as possible. Meterian provides maximum coverage with its AI-powered security platform. Select a language to compare Meterian's coverage to other well-known industry databases.