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第39行：
第39行： − 最常被考虑的资源是时间。当不加限定地使用“复杂性”时，这通常意味着时间复杂性。+ 第47行：
第47行： − 通常的时间单位(秒、分等)在复杂性理论中没有使用，因为它们过于依赖于特定计算机的选择和技术的进化。例如，今天的计算机执行算法的速度明显快于20世纪60年代的计算机; 然而，这不是算法的固有特征，而是计算机硬件技术进步的结果。复杂性理论旨在量化算法的内在时间需求，也就是算法对任何计算机的基本时间约束。这是通过计算在计算过程中执行的基本操作的数量来实现的。这些操作假定在给定的机器上占用常量时间(即不受输入大小的影响) ，通常称为步骤。+ +
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The resource that is most commonly considered is time. When "complexity" is used without qualification, this generally means time complexity.
The resource that is most commonly considered is time. When "complexity" is used without qualification, this generally means time complexity.
最常被考虑的资源是时间。当不加限定地使用“复杂度”时，这通常意味着时间复杂度。
The usual units of time (seconds, minutes etc.) are not used in complexity theory because they are too dependent on the choice of a specific computer and on the evolution of technology. For instance, a computer today can execute an algorithm significantly faster than a computer from the 1960s; however, this is not an intrinsic feature of the algorithm but rather a consequence of technological advances in computer hardware. Complexity theory seeks to quantify the intrinsic time requirements of algorithms, that is, the basic time constraints an algorithm would place on any computer. This is achieved by counting the number of elementary operations that are executed during the computation. These operations are assumed to take constant time (that is, not affected by the size of the input) on a given machine, and are often called steps.
The usual units of time (seconds, minutes etc.) are not used in complexity theory because they are too dependent on the choice of a specific computer and on the evolution of technology. For instance, a computer today can execute an algorithm significantly faster than a computer from the 1960s; however, this is not an intrinsic feature of the algorithm but rather a consequence of technological advances in computer hardware. Complexity theory seeks to quantify the intrinsic time requirements of algorithms, that is, the basic time constraints an algorithm would place on any computer. This is achieved by counting the number of elementary operations that are executed during the computation. These operations are assumed to take constant time (that is, not affected by the size of the input) on a given machine, and are often called steps.
在'''<font color="#ff8000">复杂度理论 complexity theory</font>'''中不使用通常的时间单位(秒、分等)，因为它们过于依赖于特定计算机的选择和技术的演变。例如，今天的计算机执行算法的速度明显快于20世纪60年代的计算机; 然而，这不是算法的固有特征，而是计算机硬件技术进步的结果。复杂度理论旨在量化算法的内在时间需求，也就是算法对任何计算机的基本时间约束。这是通过计数在计算过程中执行的基本操作数量来实现的。这些操作假定在给定的机器上占用常量时间(即不受输入大小的影响) ，通常被称为步骤。
===Space===
===Space===
空间
Another important resource is the size of [[computer memory]] that is needed for running algorithms.
Another important resource is the size of [[computer memory]] that is needed for running algorithms.