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Frameworks can introduce abstraction layers that may contribute to performance overhead, larger bundle sizes, and increased complexity. Modern frameworks, such as Vue 3, address these challenges with features like concurrent rendering, tree-shaking, and selective hydration.
Bootstrap (formerly Twitter Bootstrap) is a free and open-source CSS framework directed at responsive, mobile-first front-end web development. It contains HTML , CSS and (optionally) JavaScript -based design templates for typography , forms , buttons , navigation , and other interface components.
Bootstrap Studio was launched on October 19, 2015 with a post on Product Hunt where it reached number 4 in the Product of the Day category. [5] Version 2.0 of the software was released on January 22, 2016 and brought JavaScript editing, multi-page support and improved the CSS support. [6] Version 4.0 was launched on November 1, 2017.
To alleviate these issues, React was the first major library to adopt a virtual DOM in 2013, which removed both the performance bottlenecks (since diffing and reconciling the DOM was relatively cheap) and the difficulty of binding data (since components were effectively just objects). [9]
Carbon Design System is a free and open-source design system and library created by IBM, which implements the IBM Design Language, and licensed under Apache License 2.0. [9] [10] Its public development initially started on June 10, 2015. [11]
The high-performance Vue Red Line was joined in 2007 by the Green Line model. The Green Line was a mild hybrid, or "assist hybrid", using GM's belt alternator starter (BAS) system. [4] An electric motor connected to the crankshaft via a special accessory drive belt and the Green Line included a modified automatic transmission.
A key result in Efron's seminal paper that introduced the bootstrap [4] is the favorable performance of bootstrap methods using sampling with replacement compared to prior methods like the jackknife that sample without replacement. However, since its introduction, numerous variants on the bootstrap have been proposed, including methods that ...
One set, the bootstrap sample, is the data chosen to be "in-the-bag" by sampling with replacement. The out-of-bag set is all data not chosen in the sampling process. When this process is repeated, such as when building a random forest, many bootstrap samples and OOB sets are created. The OOB sets can be aggregated into one dataset, but each ...