Worst is an adjective.Example: A cyclone is one of the worst kinds of storms.If you want a related verb you could consider worsen.Example: He went to hospital but his health worsened.ALSOWorst is the superlative form of bad - bad, worse (comparative), worst (superlative).Worst can be a verb it means to defeat - He worsted his opponent easily.This use is not common.
Less. Eg. 'it is worse than that', 'it is the worst', and 'it is less than that', 'it is the least'.
The Worlds Worst Sheepwreck
the worlds worst sheepwreck
In the English Language The word 'worse' acts as Dative, Comparative. We do NOT say Dative ; Worse Comparative; Worser Superlative ; Worsest The Superlative is ' WORST'. In a jocular sense you may hear these words said. However, to describe the weather becoming more bad , we would say 'The weather is becoming worse and worse'. NOT worser. Or ' The werather is at its worst', when it cannot become any more worse.
Asymptotic
Can't say without some detail about the algorithm in question.
no it was the worst one
These are terms given to the various scenarios which can be encountered by an algorithm. The best case scenario for an algorithm is the arrangement of data for which this algorithm performs best. Take a binary search for example. The best case scenario for this search is that the target value is at the very center of the data you're searching. So the best case time complexity for this would be O(1). The worst case scenario, on the other hand, describes the absolute worst set of input for a given algorithm. Let's look at a quicksort, which can perform terribly if you always choose the smallest or largest element of a sublist for the pivot value. This will cause quicksort to degenerate to O(n2). Discounting the best and worst cases, we usually want to look at the average performance of an algorithm. These are the cases for which the algorithm performs "normally."
The worst fit algorithm is a means by which an operating system can choose which space in memory to store information (this algorithm can also be used for allocating hard disk space). The algorithm searches for free-space in memory in which it can store the desired information. The algorithm selects the largest possible free space that the information can be stored on (i.e., that is bigger than the information needing to be stored) and stores it there. This is directly opposed to the best fit algorithm which searches the memory in much the same way as before, only instead chooses the open memory space which is the smallest available which the information can be stored in (i.e., that is bigger than the information needing to be stored).
The worst case occurs when data is already sorted where the complexity is O(n^2) instead of the well known O(n log n)
Linear time. O(n).
It can be used in computer programming. It helps you to see which options are not viable and would not help out the situation.
There is no worst case for merge sort. Each sort takes the same amount of steps, so the worst case is equal to the average case and best case. In each case it has a complexity of O( N * log(N) ).
All algorithms have a best, worst and average case. Algorithms that always perform in constant time have a best, worst and average of O(1).
The worst fit algorithm is a means by which an operating system can choose which space in memory to store information (this algorithm can also be used for allocating hard disk space). The algorithm searches for free-space in memory in which it can store the desired information. The algorithm selects the largest possible free space that the information can be stored on (i.e., that is bigger than the information needing to be stored) and stores it there. This is directly opposed to the best fit algorithm which searches the memory in much the same way as before, only instead chooses the open memory space which is the smallest available which the information can be stored in (i.e., that is bigger than the information needing to be stored).
Merge sort (or mergesort) is an algorithm. Algorithms do not have running times since running times are determined by the algorithm's performance/complexity, the programming language used to implement the algorithm and the hardware the implementation is executed upon. When we speak of algorithm running times we are actually referring to the algorithm's performance/complexity, which is typically notated using Big O notation. Mergesort has a worst, best and average case performance of O(n log n). The natural variant which exploits already-sorted runs has a best case performance of O(n). The worst case space complexity is O(n) auxiliary.