Disclaimer:
I am a beginner in competitive programming, and this is me documenting my learnings. So, anything I say is just what I think at the moment and should not be taken as hard truths.
It has been a long time now that I practiced my competitive programming skills. Not super good at it. Last I practiced thoroughly was during interview preparation in July 2020.
Phase 1: Base Building
I have planned to solve at least two implementation
based problems everyday for a month starting today and additionally learning one new algorithm daily. I personally like string algorithms so I will start from there.
Problem 1: Do Not Be Distracted!
main() {
int n;
cin >> n;
string s;
cin >> s;
s.erase(unique(begin(s), end(s)), end(s));
sort(begin(s), end(s));
auto it = unique(begin(s), end(s));
if(it != end(s)) cout << "NO";
else cout << "YES";
}
Time Complexity: O(nlog(n))
Space Complexity: O(1) # not considering the space to hold the data
Another solution:
main() {
int n;
cin >> n;
string s;
cin >> s;
unordered_set<char> se;
bool yes = true;
for(int i = 0; i < n; i++) {
if(i && s[i] == s[i-1]) continue;
if(se.count(s[i])) {
yes = false;
break;
}
se.insert(s[i]);
}
if(yes) cout << "YES";
else cout << "NO";
}
Time Complexity: O(n)
Space Complexity: O(n) # the unordered set
used to contain
elements for checking.
Problem 2: Black Square
main() {
vector<int> v(4);
for(auto& e: v) cin >> e;
string s;
cin >> s;
long long total = 0;
for(auto& c: s) {
int p = c - '0' - 1; // additional -1 for zero based indexing
total += v[p];
}
cout << total;
}
This would be more fun to write in Python.
v = list(map(int, input().split()))
s = input()
s = [int(c)-1 for c in s] # -1 for zero based indexing
total = sum(v[i] for i in s)
print(total)
I am sure we could use find STL algorithm for the C++ code.
That is all for today 2 implementation problem solving.
Let us hop on to learning one new/old string algorithm.
String Algorithm
The basic question when it comes to string is about, whether a given pattern
of length m
occurs in a text
of length n
.
The problem can be solved using naive method in O(n*m) time.
main() {
string text = "abcabc";
string pattern = "abc";
int n = text.length(), m = pattern.length();
bool found = false;
// looping through all starting position of the pattern
for(int i = 0; i < n-m+1; i++) {
// checking if the substring matches
if(text.substr(i, m) == pattern) {
found = true;
break;
}
}
if(found) cout << "YES";
else cout << "NO";
}
Now there are algorithms that can solve the above pattern matching in O(n+m) time. The first one that comes in mind is the famous
Knuth Morris Pratt
or better known as KMP algorithm.
Here is a video of Donald Knuth talking about KMP algorithm.
vector<int> prefix_func(string s) {
int n = s.length();
vector<int> pi(n, 0);
for(int i = 1; i < n; i++) {
int j = pi[i-1];
while(j > 0 && s[i] != s[j])
j = pi[j-1];
if(s[i] == s[j])
j++;
pi[i] = j;
}
return pi;
}
To use KMP algorithm, pre-compute the table using above prefix_func
.
So for given pattern
and text
, the string that should be passed to prefix_func
is pattern + x + text
, where 'x' is some character which doesn't belong to neither pattern nor text.
The different questions that can be answered are:
- Does the pattern occur in the text?
- How many times does the pattern occur in the text?
- If pattern occurs, find the starting position in text.
- Find maximum non-overlapping occurrence of the pattern in the text. And many more.
Most of the time, pattern matching is used as a part for solving a problem, and not a whole problem.
Sources:
-
prefix_function
:- cp-algorithms
Resources for additonal learning and practicing:
Dated: 13th July 2021
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