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    copied!<p>Whether you want a perfect hashfunction (different value for each object that evaluates to equal) or just a pretty good one is always a performance tradeoff, it takes normally time to compute a good hashfunction and if your dataset is smallish you're better of with a fast function. The most important (as your second post points out) is correctness, and to achieve that all you need is to return the Length of the array. Depending on your dataset that might even be ok. If it isn't (say all your arrays are equally long) you can go with something cheap like looking at the first and last value and XORing their values and then add more complexity as you see fit for your data. </p> <p>A quick way to see how your hashfunction performs on your data is to add all the data to a hashtable and count the number of times the Equals function gets called, if it is too often you have more work to do on the function. If you do this just keep in mind that the hashtable's size needs to be set bigger than your dataset when you start, otherwise you are going to rehash the data which will trigger reinserts and more Equals evaluations (though possibly more realistic?)</p> <p>For some objects (not this one) a quick HashCode can be generated by ToString().GetHashCode(), certainly not optimal, but useful as people tend to return something close to the identity of the object from ToString() and that is exactly what GetHashcode is looking for</p> <p>Trivia: The worst performance I have ever seen was when someone by mistake returned a constant from GetHashCode, easy to spot with a debugger though, especially if you do lots of lookups in your hashtable</p>
 

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