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  2. Time complexity - Wikipedia

    en.wikipedia.org/wiki/Time_complexity

    Graphs of functions commonly used in the analysis of algorithms, showing the number of operations N as the result of input size n for each function. In theoretical computer science, the time complexity is the computational complexity that describes the amount of computer time it takes to run an algorithm.

  3. Best, worst and average case - Wikipedia

    en.wikipedia.org/wiki/Best,_worst_and_average_case

    Usually the resource being considered is running time, i.e. time complexity, but could also be memory or some other resource. Best case is the function which performs the minimum number of steps on input data of n elements. Worst case is the function which performs the maximum number of steps on input data of size n.

  4. Skip list - Wikipedia

    en.wikipedia.org/wiki/Skip_list

    function lookupByPositionIndex(i) node ← head i ← i + 1 # don't count the head as a step for level from top to bottom do while i ≥ node.width[level] do # if next step is not too far i ← i - node.width[level] # subtract the current width node ← node.next[level] # traverse forward at the current level repeat repeat return node.value end ...

  5. Worst-case complexity - Wikipedia

    en.wikipedia.org/wiki/Worst-case_complexity

    The order of growth (e.g. linear, logarithmic) of the worst-case complexity is commonly used to compare the efficiency of two algorithms. The worst-case complexity of an algorithm should be contrasted with its average-case complexity, which is an average measure of the amount of resources the algorithm uses on a random input.

  6. SQL syntax - Wikipedia

    en.wikipedia.org/wiki/SQL_syntax

    TIME WITH TIME ZONE: the same as TIME, but including details about the time zone in question. TIMESTAMP : This is a DATE and a TIME put together in one variable (e.g. 2011-05-03 15:51:36.123456 ). TIMESTAMP WITH TIME ZONE : the same as TIMESTAMP , but including details about the time zone in question.

  7. Interval scheduling - Wikipedia

    en.wikipedia.org/wiki/Interval_scheduling

    Interval scheduling is a class of problems in computer science, particularly in the area of algorithm design. The problems consider a set of tasks. Each task is represented by an interval describing the time in which it needs to be processed by some machine (or, equivalently, scheduled on some resource).

  8. Java (programming language) - Wikipedia

    en.wikipedia.org/wiki/Java_(programming_language)

    Java is a high-level, class-based, object-oriented programming language that is designed to have as few implementation dependencies as possible. It is a general-purpose programming language intended to let programmers write once, run anywhere (), [16] meaning that compiled Java code can run on all platforms that support Java without the need to recompile. [17]

  9. Programming complexity - Wikipedia

    en.wikipedia.org/wiki/Programming_Complexity

    The complexity of an existing program determines the complexity of changing the program. Problem complexity can be divided into two categories: [2] Accidental complexity relates to difficulties a programmer faces due to the software engineering tools. Selecting a better tool set or a higher-level programming language may reduce it.