+ 48
Could you explain axioms and the big (O), and how to calculate it from java code?
My professor isn't very good at explaining these things 😅
11 Réponses
+ 52
try looking here for Big O
https://www.sololearn.com/learn/6362/?ref=app
+ 13
A really good explanation with examples can be found here:
http://examcrazy.com/Engineering/Computer-Science/Determining_the_Efficiency_of_an_Algorithm_Big_O_Notation.asp
+ 10
I would like to recommend a classic book:
Introduction to algorithms by Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L.; Stein, Clifford.
+ 8
I found this website very useful in my data structures and algorithms class:
http://bigocheatsheet.com
+ 8
Since algorithms are studied by mathematics, I suppose the meaning of axioms here is the same as in mathematics.
Mathematics is about logic, and mathematicians try to demonstrate things with absolute certainty from different assumptions. Those assumptions are called axioms. For example, once defined what is a set, and different operations between them, an axiom says that if you have two sets of things called S1 and S2, and every element in S1 is in S2 and the other way around, boths sets contain the same elements. (the real axiom uses definitions such as equal and contained but states exactly the same).
As you can see, everyone would agree with this, and mathematicians try to prove that something will always/never happen if the axiom is true. (Also they prove that something can't be proven with the other axioms they believe to be true before stating a new one)
+ 8
thanks to all for links and also thanks to Margie 🐣
+ 7
I think u don't know it's importance dear Margie 🐣
if u r just trying to pass classes, it is the thing that's why "Google" search faster than any other search engines, but ok dear I wish you could understand it's importance in programming .
+ 3
thnks
+ 3
thanks for all the links and help on this question, it helped a lot 🌻 AnnA lol just trying to pass classes, I'm glad if it could help someone else too🐣🐣
+ 3
When you are at it. Don't forget to check also a small o(n)
+ 2
bigocheatsheet.com is good for the visual understanding of the difficulty of algorithms.But now, I read the book Career of the programmer by G.Luckman McDowell. And she on several pages very understandable explains graduation of the difficulty of algorithms by O(n) and etc.