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  2. Comparison of Java and C++ - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_Java_and_C++

    Compiled Java code files are generally smaller than code files in C++ as Java bytecode is usually more compact than native machine code and Java programs are never statically linked. C++ compiling features an added textual preprocessing phase, while Java does not. Thus some users add a preprocessing phase to their build process for better ...

  3. Rope (data structure) - Wikipedia

    en.wikipedia.org/wiki/Rope_(data_structure)

    In computer programming, a rope, or cord, is a data structure composed of smaller strings that is used to efficiently store and manipulate longer strings or entire texts. For example, a text editing program may use a rope to represent the text being edited, so that operations such as insertion, deletion, and random access can be done efficiently.

  4. Computational complexity of mathematical operations - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    Here, complexity refers to the time complexity of performing computations on a multitape Turing machine. [1] See big O notation for an explanation of the notation used. Note: Due to the variety of multiplication algorithms, () below stands in for the complexity of the chosen multiplication algorithm.

  5. Comparison of programming languages (string functions)

    en.wikipedia.org/wiki/Comparison_of_programming...

    Most programming languages that have a string datatype will have some string functions although there may be other low-level ways within each language to handle strings directly. In object-oriented languages, string functions are often implemented as properties and methods of string objects.

  6. Time complexity - Wikipedia

    en.wikipedia.org/wiki/Time_complexity

    [1]: 226 Since this function is generally difficult to compute exactly, and the running time for small inputs is usually not consequential, one commonly focuses on the behavior of the complexity when the input size increases—that is, the asymptotic behavior of the complexity. Therefore, the time complexity is commonly expressed using big O ...

  7. Comparison of data structures - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data_structures

    Here are time complexities [5] of various heap data structures. The abbreviation am. indicates that the given complexity is amortized, otherwise it is a worst-case complexity. For the meaning of "O(f)" and "Θ(f)" see Big O notation. Names of operations assume a max-heap.

  8. List of unsolved problems in computer science - Wikipedia

    en.wikipedia.org/wiki/List_of_unsolved_problems...

    Does linear programming admit a strongly polynomial-time algorithm? (This is problem #9 in Smale's list of problems.) How many queries are required for envy-free cake-cutting? What is the algorithmic complexity of the minimum spanning tree problem? Equivalently, what is the decision tree complexity of the MST problem?

  9. String interning - Wikipedia

    en.wikipedia.org/wiki/String_interning

    In computer science, string interning is a method of storing only one copy of each distinct string value, which must be immutable. [1] Interning strings makes some string processing tasks more time-efficient or space-efficient at the cost of requiring more time when the string is created or interned.