When to use which Sorting algorithm and when definitely shouldn't

Question

We see lot of sorting techniques like Merge, quick, Heap. Could you help me decide which of these sorting techniques to be used in which kind of environment(as in the problem)? When should we use which of these sorting algorithms and where not(their disadvantages in time and space)? I am expecting answer something in this form: a) We would use Merge sort when... we should definitely not use Merge Sort when... b) We would use Quick sort when... we should definitely not use quick Sort when... JavaScript questions and answers, JavaScript questions pdf, JavaScript question bank, JavaScript questions and answers pdf, mcq on JavaScript pdf, JavaScript questions and solutions, JavaScript mcq Test , Interview JavaScript questions, JavaScript Questions for Interview, JavaScript MCQ (Multiple Choice Questions)

Answer 1

There are a few basic parameters that characterize the behavior of each sorting algorithm: average case computational complexity worst case computational complexity memory requirements stability (i.e. is it a stable sort or not?) All of these are widely documented for all commonly used sorts, and this is all the information one needs to provide an answer in the format that you want. However, since even four parameters for each sort make for a lot of things -- not all of which will be relevant -- to consider, it isn't a very good idea to try and give such a "scripted" answer. Furthermore, there are even more advanced concepts that could come into consideration (such as behavior when run on almost-sorted or reverse-sorted data, cache performance, resistance to maliciously constructed input), making such an answer even more lengthy and error-prone. I suggest that you spend some time familiarizing yourself with the four basic concepts mentioned above, perhaps by visualizing how each type of sort works on simple input and reading an introductory text on sorting algorithms. Do this and soon enough you will be able to answer such questions yourself.