Essential Data Structures

Essential Data structures:

In each and every algorithm, there is a requirement to store data. Varying from storing a single value in a single variable to the more complex data structures. In programming contests, there are some aspects of data structures to consider when choosing the proper way to symbolize the data for a problem. This chapter will provide you some guidelines and list some fundamental data structures to begin with.

Will it work?

If data structures won't work, it is not obliging at all. Ask yourself what questions the algorithm will require to be able to ask the data structure, and ensure the data structure can handle it. When not, then either more data should be added to the structure, or you require to find a distinct representation. 

Can I code it?

When you do not know or cannot remember how to code a given data structure, pick a dissimilar one. Confirm that you have a superior idea of how each of the operations will influence the structure of data. 
The other consideration here is memory. Will the data structure fit into the available memory? If not, compact it or choose a new one. Or else, it is already apparent from the starting that it won't work.

Can I code it in time? Or my programming languages still support it?

As this is a timed competition, you have 3-5 programs to write in, say, five hrs. If it will take you an hr. and a half to code just the data structure for the initial problem, then you are almost certainly looking at wrong structure.

The other very significant consideration is, whether your programming language has really given you the necessary data structure. For C++ programmers, STL has a broad option of a very good built-in data structure, what you require to do is to master them, instead of trying to build your own data structure.

In contest time, this will be the one of winning strategy. Consider this scenario. All teams are provided a set of problems. Some of them needed the usage of 'stack'. The best programmer from team A directly implement the best recognized stack implementation, he require 10 minutes to do so. Astonishingly for them, other teams type in only two lines:

"#include <stack>" and "std::stack<int> s;” can you see who have 10 minutes benefit now?

Can I debug it?

It is simple to forget this specific aspect of data structure selection. Keep in mind that a program is ineffective unless it works. Do not forget that debugging time is a big portion of the contest time; therefore comprises its consideration in computing coding time.

What makes a data structure simple to debug? That is basically determined by the following two properties.

A) State is simple to examine: The smaller, more compact the presentation, in common, the simpler it is to observe. Also, statically assigned arrays are much simpler to observe than linked lists or even dynamically assigned arrays.

B) State can be displayed simply: For more complicated data structures, the simplest way to observe them is to write a small routine to output the data. Unfortunately, for given time constraints, you will probably want to restrict yourself to text output. This signifies that structures such as trees and graphs are going to be hard to observe.

Is it fast?

The utilization of more sophisticated data structure will decrease the amount of overall algorithm complexity. This will be better if you know certain advanced data structures.

Things to Avoid:  Dynamic Memory:

In common, you must avoid dynamic memory, since:

A) It is too simple to make mistakes by using dynamic memory. Overwriting past assigned memory, not freeing memory, and not assigning memory are merely some of the mistakes which are introduced whenever dynamic memory is employed. In addition, the failure modes for such errors are such that it is hard to tell where the error take place, as it is likely to be at a potentially much later memory operation.

B) It is so hard to observe the data structure's contents. The interactive development atmospheres available do not handle dynamic memory well, particularly for C. Consider parallel arrays as an choice to dynamic memory. One way to do a linked list, where rather than keeping a next point, you keep a second array that has the index of subsequent element. Sometimes you might have to dynamically assign these, however as it must only be done once, it is much simpler to get right than assigning and freeing the memory for each delete and insert.

All of this notwithstanding, sometimes dynamic memory is the means to go, particularly for big data structures where the size of the structure is not recognized until you have the input. 

Things to Avoid: Coolness Factor:

Try not to fall into the coolness trap. You might have just seen the efficient data structure, however keep in mind:

A) Cool ideas which do not work aren't.
B) Cool ideas which will take forever to code aren't, either

It is much more significant that your program and data structure work than how remarkable your data structure is.

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