Analyzing a particular algorithm falls under the field of analysis of algorithms. The Euclidean algorithm is one of the oldest algorithms in common use. They belong to the class of evolutionary algorithms and evolutionary computation. Clustering techniques based on Bayesian algorithms can help reduce false positives. Checksums are used as cryptographic primitives in larger authentication algorithms. Many problems can be solved by both direct algorithms or iterative approaches. MATLAB and Python implementations of these fast algorithms are available. There are several common algorithms for hashing integers. Examples for such clustering algorithms are CLIQUE and SUBCLU. Understanding data dependencies is fundamental in implementing parallel algorithms. Sudoku can be solved using stochastic (random-based) algorithms. HMACs are substantially less affected by collisions than their underlying hashing algorithms alone. Quantization also forms the core of essentially all lossy compression algorithms. The autocorrelation matrix is used in various digital signal processing algorithms. Techniques to deal with RFI range from filters in hardware to advanced algorithms in software.