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  2. Best, worst and average case - Wikipedia

    en.wikipedia.org/wiki/Best,_worst_and_average_case

    But given a worst-case input, its performance degrades to O(n 2). Also, when implemented with the "shortest first" policy, the worst-case space complexity is instead bounded by O(log(n)). Heapsort has O(n) time when all elements are the same. Heapify takes O(n) time and then removing elements from the heap is O(1) time for each of the n elements.

  3. Worst-case circuit analysis - Wikipedia

    en.wikipedia.org/wiki/Worst-case_circuit_analysis

    Worst-case analysis is the analysis of a device (or system) that assures that the device meets its performance specifications. These are typically accounting for tolerances that are due to initial component tolerance, temperature tolerance, age tolerance and environmental exposures (such as radiation for a space device).

  4. Klee–Minty cube - Wikipedia

    en.wikipedia.org/wiki/Klee–Minty_cube

    In mathematical optimization, the Klee–Minty cube is an example that shows the worst-case computational complexity of many algorithms of linear optimization. It is a deformed cube with exactly 2 D corners in dimension D {\displaystyle D} .

  5. Differential privacy - Wikipedia

    en.wikipedia.org/wiki/Differential_privacy

    Differential privacy (DP) is a mathematically rigorous framework for releasing statistical information about datasets while protecting the privacy of individual data subjects. It enables a data holder to share aggregate patterns of the group while limiting information that is leaked about specific individuals.

  6. Bin packing problem - Wikipedia

    en.wikipedia.org/wiki/Bin_packing_problem

    They show that next-fit-increasing bin packing attains an absolute worst-case approximation ratio of at most 7/4, and an asymptotic worst-case ratio of 1.691 for any concave and monotone cost function. Cohen, Keller, Mirrokni and Zadimoghaddam [49] study a setting where the size of the items is not known in advance, but it is a random variable.

  7. Failure analysis - Wikipedia

    en.wikipedia.org/wiki/Failure_analysis

    Failure analysis is the process of collecting and analyzing data to determine the cause of a failure, often with the goal of determining corrective actions or liability.. According to Bloch and Geitner, ”machinery failures reveal a reaction chain of cause and effect… usually a deficiency commonly referred to as the symptom…”

  8. Amortized analysis - Wikipedia

    en.wikipedia.org/wiki/Amortized_analysis

    Amortized analysis requires knowledge of which series of operations are possible. This is most commonly the case with data structures, which have state that persists between operations. The basic idea is that a worst-case operation can alter the state in such a way that the worst case cannot occur again for a long time, thus "amortizing" its cost.

  9. Physics of failure - Wikipedia

    en.wikipedia.org/wiki/Physics_of_failure

    More recent work in the area of physics of failure has been focused on predicting the time to failure of new materials (i.e., lead-free solder, [18] [19] high-K dielectric [20]), software programs, [21] using the algorithms for prognostic purposes, [22] and integrating physics of failure predictions into system-level reliability calculations. [23]