Oracle Linux kernel developer Daniel Jordan contributes this post on the initial support for multithreaded jobs in padata. The last padata blog described unbinding padata jobs from specific CPUs. This post will cover padata’s initial support for multithreading CPU-intensive kernel paths, which takes us to the memory management system. The Bottleneck During boot, the kernel needs to…
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Overview
With the help of software composition analysis (SCA) tools, software development teams can track and analyze any open source code brought into a project from a licensing compliance and security vulnerabilities perspective. Such tools discover open source code (at various levels of details and capabilities), their direct and indirect dependencies, licenses in effect, and the presence of any known security vulnerabilities and potential exploits. Several companies provide SCA suites, open source tools, and related services driven as community projects. The question of what tool is most suitable for a specific usage model and environment always comes up. It is difficult to answer given the lack of a standard method to compare and evaluate such tools.
The goal of this paper is to recommend a series of comparative metrics when evaluating multiple SCA tools.
