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Recursion-writing Gessica Mohr #29
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GEM | ||
remote: https://rubygems.org/ | ||
specs: | ||
ansi (1.5.0) | ||
builder (3.2.4) | ||
coderay (1.1.3) | ||
method_source (1.0.0) | ||
minitest (5.14.2) | ||
minitest-reporters (1.4.2) | ||
ansi | ||
builder | ||
minitest (>= 5.0) | ||
ruby-progressbar | ||
minitest-skip (0.0.3) | ||
minitest (~> 5.0) | ||
minitest-spec (0.0.2.1) | ||
minitest (>= 3.0) | ||
pry (0.13.1) | ||
coderay (~> 1.1) | ||
method_source (~> 1.0) | ||
rake (13.0.1) | ||
ruby-progressbar (1.10.1) | ||
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PLATFORMS | ||
ruby | ||
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DEPENDENCIES | ||
minitest | ||
minitest-reporters | ||
minitest-skip | ||
minitest-spec | ||
pry | ||
rake | ||
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BUNDLED WITH | ||
2.1.4 |
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# Authoring recursive algorithms. Add comments including time and space complexity for each method. | ||
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# Time complexity: ? | ||
# Space complexity: ? | ||
# Time complexity: O(n) it depends on the size of n to run | ||
# Space complexity: O(n) it creates a stack every time it calls the recursive method | ||
def factorial(n) | ||
raise NotImplementedError, "Method not implemented" | ||
raise ArgumentError if n < 0 | ||
return 1 if n == 0 | ||
return n * factorial(n - 1) | ||
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end | ||
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# Time complexity: ? | ||
# Space complexity: ? | ||
# Time complexity: O(n^2) - the slice method in the reverse method creates another array so that counts for O(n) and then the method runs n times depending on the size of array, O(n). Total of O(n^2). | ||
# Space complexity: O(n^2) - because we are creating a new array when using the slice method and it creates a stack to run the recursion method. | ||
def reverse(s) | ||
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raise NotImplementedError, "Method not implemented" | ||
if s.length <= 1 | ||
return s | ||
end | ||
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return s[-1] + reverse(s[1..-2]) + s[0] | ||
end | ||
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# Time complexity: ? | ||
# Space complexity: ? | ||
def reverse_inplace(s) | ||
raise NotImplementedError, "Method not implemented" | ||
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# Time complexity: O(n) it depends on the size of s to run | ||
# Space complexity: O(n) it creates a stack every time if calls the recursive method | ||
def reverse_inplace(s, i = 0, j = s.length - 1) | ||
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return s if s.length == 0 || s.length == 1 | ||
return s if i >= j | ||
temp = s[i] | ||
s[i] = s[j] | ||
s[j] = temp | ||
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return reverse_inplace(s, i + 1, j - 1) | ||
end | ||
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# Time complexity: ? | ||
# Space complexity: ? | ||
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# Time complexity: O(n) it depends on the size of n to run | ||
# Space complexity: O(n) it creates a stack every time if calls the recursive method | ||
def bunny(n) | ||
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raise NotImplementedError, "Method not implemented" | ||
return 0 if n <= 0 | ||
return 2 + bunny(n - 1) | ||
end | ||
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# Time complexity: ? | ||
# Space complexity: ? | ||
def nested(s) | ||
raise NotImplementedError, "Method not implemented" | ||
# Time complexity: O(n) it depends on the size of s to run | ||
# Space complexity: O(n) it creates a stack every time if calls the recursive method | ||
def nested(s, i = 0, j = s.length - 1) | ||
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 👍 Very compact! |
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return true if s.empty? || i > j && s[i] != s[j] | ||
return false if s.length == 1 || s[i] == s[j] | ||
return nested(s, i + 1, j - 1) | ||
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end | ||
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# Time complexity: ? | ||
# Space complexity: ? | ||
def search(array, value) | ||
raise NotImplementedError, "Method not implemented" | ||
# Time complexity: O(n) it depends on the size of the array to run | ||
# Space complexity: O(n) it creates a stack every time if calls the recursive method | ||
def search(array, value, index = 0) | ||
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return false if index >= array.length | ||
return true if array[index] == value | ||
return search(array, value, index + 1) | ||
end | ||
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# Time complexity: ? | ||
# Space complexity: ? | ||
def is_palindrome(s) | ||
raise NotImplementedError, "Method not implemented" | ||
# Time complexity: O(n) it depends on the size of s to run | ||
# Space complexity: O(n) it creates a stack every time if calls the recursive method | ||
def is_palindrome(s, i = 0, j = s.length - 1) | ||
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return true if s.empty? || i >= j | ||
return false if s[i] != s[j] | ||
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return is_palindrome(s, i + 1, j - 1) | ||
end | ||
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# Time complexity: ? | ||
# Space complexity: ? | ||
# Time complexity: O(log n) | ||
# Space complexity: O(log n) | ||
def digit_match(n, m) | ||
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raise NotImplementedError, "Method not implemented" | ||
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return 1 if n == 0 && m == 0 | ||
return 0 if n <= 1 || m <= 1 | ||
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if n % 10 == m % 10 | ||
return 1 + digit_match(n / 10, m / 10) | ||
else | ||
return digit_match(n / 10, m / 10) | ||
end | ||
end | ||
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# Time complexity: O(2^n) it depends on the size of n to run | ||
# Space complexity: O(2^n) it creates a stack every time if calls the recursive method | ||
def fibonacci(n) | ||
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There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. 👍 However the space complexity is O(n) |
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return 0 if n == 0 | ||
return 1 if n == 1 | ||
return fibonacci(n - 1) + fibonacci(n - 2) | ||
end |
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👍