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Like the N-convex algorithm, this algorithm attempts to find a set of candidates whose centroid is close to . The key difference is that instead of taking unique candidates, we allow candidates to populate the set multiple times. The result is that the weight of each candidate is simply given by its frequency in the list, which we can then index by random selection:

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Prototype pollution defense: One test patches Object.prototype.then to intercept promise resolutions, then verifies that pipeTo() and tee() operations don't leak internal values through the prototype chain. This tests a security property that only exists because the spec's promise-heavy internals create an attack surface.

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