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@ -37,7 +37,7 @@ mogloe ofikasno pristupiti i mijenjati. Preciznije, struktura podataka je zbirka
vrijednosti, odnosa među njima, funkcije ili operacije koje se mogu primijeniti na vrijednosti, odnosa među njima, funkcije ili operacije koje se mogu primijeniti na
podatke. podatke.
`B` - Beginner, `A` - Advanced `B` - Pocetnik - Beginner, `A` - Napredni - Advanced
* `B` [Linked List](src/data-structures/linked-list) * `B` [Linked List](src/data-structures/linked-list)
* `B` [Doubly Linked List](src/data-structures/doubly-linked-list) * `B` [Doubly Linked List](src/data-structures/doubly-linked-list)
@ -62,11 +62,11 @@ podatke.
Algoritam je nedvosmislena specifikacija kako riješiti klasu problema. To je Algoritam je nedvosmislena specifikacija kako riješiti klasu problema. To je
skup pravila koja precizno definiraju niz operacija. skup pravila koja precizno definiraju niz operacija.
`B` - Beginner, `A` - Advanced `B` - Pocetnik - Beginner, `A` - Napredni - Advanced
### Algoritmi po temama ### Algoritmi po temama
* **Math** * **Matematika**
* `B` [Bit Manipulation](src/algorithms/math/bits) - postaviti / dobiti / ažurirati / očistiti bitove, množenje / dijeljenje sa dva, napraviti negativne itd * `B` [Bit Manipulation](src/algorithms/math/bits) - postaviti / dobiti / ažurirati / očistiti bitove, množenje / dijeljenje sa dva, napraviti negativne itd
* `B` [Factorial](src/algorithms/math/factorial) * `B` [Factorial](src/algorithms/math/factorial)
* `B` [Fibonacci Number](src/algorithms/math/fibonacci) - klasične verzije i verzije zatvorenog oblika * `B` [Fibonacci Number](src/algorithms/math/fibonacci) - klasične verzije i verzije zatvorenog oblika
@ -87,7 +87,7 @@ skup pravila koja precizno definiraju niz operacija.
* `A` [Square Root](src/algorithms/math/square-root) - Newton's method * `A` [Square Root](src/algorithms/math/square-root) - Newton's method
* `A` [Liu Hui π Algorithm](src/algorithms/math/liu-hui) - approximate π calculations based on N-gons * `A` [Liu Hui π Algorithm](src/algorithms/math/liu-hui) - approximate π calculations based on N-gons
* `A` [Discrete Fourier Transform](src/algorithms/math/fourier-transform) - decompose a function of time (a signal) into the frequencies that make it up * `A` [Discrete Fourier Transform](src/algorithms/math/fourier-transform) - decompose a function of time (a signal) into the frequencies that make it up
* **Sets** * **Setovi**
* `B` [Cartesian Product](src/algorithms/sets/cartesian-product) - product of multiple sets * `B` [Cartesian Product](src/algorithms/sets/cartesian-product) - product of multiple sets
* `B` [Fisher–Yates Shuffle](src/algorithms/sets/fisher-yates) - random permutation of a finite sequence * `B` [Fisher–Yates Shuffle](src/algorithms/sets/fisher-yates) - random permutation of a finite sequence
* `A` [Power Set](src/algorithms/sets/power-set) - all subsets of a set (bitwise and backtracking solutions) * `A` [Power Set](src/algorithms/sets/power-set) - all subsets of a set (bitwise and backtracking solutions)
@ -99,7 +99,7 @@ skup pravila koja precizno definiraju niz operacija.
* `A` [Knapsack Problem](src/algorithms/sets/knapsack-problem) - "0/1" and "Unbound" ones * `A` [Knapsack Problem](src/algorithms/sets/knapsack-problem) - "0/1" and "Unbound" ones
* `A` [Maximum Subarray](src/algorithms/sets/maximum-subarray) - "Brute Force" and "Dynamic Programming" (Kadane's) versions * `A` [Maximum Subarray](src/algorithms/sets/maximum-subarray) - "Brute Force" and "Dynamic Programming" (Kadane's) versions
* `A` [Combination Sum](src/algorithms/sets/combination-sum) - find all combinations that form specific sum * `A` [Combination Sum](src/algorithms/sets/combination-sum) - find all combinations that form specific sum
* **Strings** * **Stringovi**
* `B` [Hamming Distance](src/algorithms/string/hamming-distance) - number of positions at which the symbols are different * `B` [Hamming Distance](src/algorithms/string/hamming-distance) - number of positions at which the symbols are different
* `A` [Levenshtein Distance](src/algorithms/string/levenshtein-distance) - minimum edit distance between two sequences * `A` [Levenshtein Distance](src/algorithms/string/levenshtein-distance) - minimum edit distance between two sequences
* `A` [Knuth–Morris–Pratt Algorithm](src/algorithms/string/knuth-morris-pratt) (KMP Algorithm) - substring search (pattern matching) * `A` [Knuth–Morris–Pratt Algorithm](src/algorithms/string/knuth-morris-pratt) (KMP Algorithm) - substring search (pattern matching)
@ -107,12 +107,12 @@ skup pravila koja precizno definiraju niz operacija.
* `A` [Rabin Karp Algorithm](src/algorithms/string/rabin-karp) - substring search * `A` [Rabin Karp Algorithm](src/algorithms/string/rabin-karp) - substring search
* `A` [Longest Common Substring](src/algorithms/string/longest-common-substring) * `A` [Longest Common Substring](src/algorithms/string/longest-common-substring)
* `A` [Regular Expression Matching](src/algorithms/string/regular-expression-matching) * `A` [Regular Expression Matching](src/algorithms/string/regular-expression-matching)
* **Searches** * **Pretrage**
* `B` [Linear Search](src/algorithms/search/linear-search) * `B` [Linear Search](src/algorithms/search/linear-search)
* `B` [Jump Search](src/algorithms/search/jump-search) (or Block Search) - search in sorted array * `B` [Jump Search](src/algorithms/search/jump-search) (or Block Search) - search in sorted array
* `B` [Binary Search](src/algorithms/search/binary-search) - search in sorted array * `B` [Binary Search](src/algorithms/search/binary-search) - search in sorted array
* `B` [Interpolation Search](src/algorithms/search/interpolation-search) - search in uniformly distributed sorted array * `B` [Interpolation Search](src/algorithms/search/interpolation-search) - search in uniformly distributed sorted array
* **Sorting** * **Sortiranje**
* `B` [Bubble Sort](src/algorithms/sorting/bubble-sort) * `B` [Bubble Sort](src/algorithms/sorting/bubble-sort)
* `B` [Selection Sort](src/algorithms/sorting/selection-sort) * `B` [Selection Sort](src/algorithms/sorting/selection-sort)
* `B` [Insertion Sort](src/algorithms/sorting/insertion-sort) * `B` [Insertion Sort](src/algorithms/sorting/insertion-sort)
@ -122,13 +122,13 @@ skup pravila koja precizno definiraju niz operacija.
* `B` [Shellsort](src/algorithms/sorting/shell-sort) * `B` [Shellsort](src/algorithms/sorting/shell-sort)
* `B` [Counting Sort](src/algorithms/sorting/counting-sort) * `B` [Counting Sort](src/algorithms/sorting/counting-sort)
* `B` [Radix Sort](src/algorithms/sorting/radix-sort) * `B` [Radix Sort](src/algorithms/sorting/radix-sort)
* **Linked Lists** * **Linkovane Liste**
* `B` [Straight Traversal](src/algorithms/linked-list/traversal) * `B` [Straight Traversal](src/algorithms/linked-list/traversal)
* `B` [Reverse Traversal](src/algorithms/linked-list/reverse-traversal) * `B` [Reverse Traversal](src/algorithms/linked-list/reverse-traversal)
* **Trees** * **Trees**
* `B` [Depth-First Search](src/algorithms/tree/depth-first-search) (DFS) * `B` [Depth-First Search](src/algorithms/tree/depth-first-search) (DFS)
* `B` [Breadth-First Search](src/algorithms/tree/breadth-first-search) (BFS) * `B` [Breadth-First Search](src/algorithms/tree/breadth-first-search) (BFS)
* **Graphs** * **Grafovi**
* `B` [Depth-First Search](src/algorithms/graph/depth-first-search) (DFS) * `B` [Depth-First Search](src/algorithms/graph/depth-first-search) (DFS)
* `B` [Breadth-First Search](src/algorithms/graph/breadth-first-search) (BFS) * `B` [Breadth-First Search](src/algorithms/graph/breadth-first-search) (BFS)
* `B` [Kruskal’s Algorithm](src/algorithms/graph/kruskal) - finding Minimum Spanning Tree (MST) for weighted undirected graph * `B` [Kruskal’s Algorithm](src/algorithms/graph/kruskal) - finding Minimum Spanning Tree (MST) for weighted undirected graph
@ -144,18 +144,18 @@ skup pravila koja precizno definiraju niz operacija.
* `A` [Hamiltonian Cycle](src/algorithms/graph/hamiltonian-cycle) - Visit every vertex exactly once * `A` [Hamiltonian Cycle](src/algorithms/graph/hamiltonian-cycle) - Visit every vertex exactly once
* `A` [Strongly Connected Components](src/algorithms/graph/strongly-connected-components) - Kosaraju's algorithm * `A` [Strongly Connected Components](src/algorithms/graph/strongly-connected-components) - Kosaraju's algorithm
* `A` [Travelling Salesman Problem](src/algorithms/graph/travelling-salesman) - shortest possible route that visits each city and returns to the origin city * `A` [Travelling Salesman Problem](src/algorithms/graph/travelling-salesman) - shortest possible route that visits each city and returns to the origin city
* **Cryptography** * **Kriptografija**
* `B` [Polynomial Hash](src/algorithms/cryptography/polynomial-hash) - rolling hash function based on polynomial * `B` [Polynomial Hash](src/algorithms/cryptography/polynomial-hash) - rolling hash function based on polynomial
* `B` [Rail Fence Cipher](src/algorithms/cryptography/rail-fence-cipher) - a transposition cipher algorithm for encoding messages * `B` [Rail Fence Cipher](src/algorithms/cryptography/rail-fence-cipher) - a transposition cipher algorithm for encoding messages
* `B` [Caesar Cipher](src/algorithms/cryptography/caesar-cipher) - simple substitution cipher * `B` [Caesar Cipher](src/algorithms/cryptography/caesar-cipher) - simple substitution cipher
* `B` [Hill Cipher](src/algorithms/cryptography/hill-cipher) - substitution cipher based on linear algebra * `B` [Hill Cipher](src/algorithms/cryptography/hill-cipher) - substitution cipher based on linear algebra
* **Machine Learning** * **Masinsko ucenje**
* `B` [NanoNeuron](https://github.com/trekhleb/nano-neuron) - 7 simple JS functions that illustrate how machines can actually learn (forward/backward propagation) * `B` [NanoNeuron](https://github.com/trekhleb/nano-neuron) - 7 simple JS functions that illustrate how machines can actually learn (forward/backward propagation)
* `B` [k-NN](src/algorithms/ml/knn) - k-nearest neighbors classification algorithm * `B` [k-NN](src/algorithms/ml/knn) - k-nearest neighbors classification algorithm
* `B` [k-Means](src/algorithms/ml/k-means) - k-Means clustering algorithm * `B` [k-Means](src/algorithms/ml/k-means) - k-Means clustering algorithm
* **Image Processing** * **Procesiranje slika**
* `B` [Seam Carving](src/algorithms/image-processing/seam-carving) - content-aware image resizing algorithm * `B` [Seam Carving](src/algorithms/image-processing/seam-carving) - content-aware image resizing algorithm
* **Uncategorized** * **Nekategorizirani**
* `B` [Tower of Hanoi](src/algorithms/uncategorized/hanoi-tower) * `B` [Tower of Hanoi](src/algorithms/uncategorized/hanoi-tower)
* `B` [Square Matrix Rotation](src/algorithms/uncategorized/square-matrix-rotation) - in-place algorithm * `B` [Square Matrix Rotation](src/algorithms/uncategorized/square-matrix-rotation) - in-place algorithm
* `B` [Jump Game](src/algorithms/uncategorized/jump-game) - backtracking, dynamic programming (top-down + bottom-up) and greedy examples * `B` [Jump Game](src/algorithms/uncategorized/jump-game) - backtracking, dynamic programming (top-down + bottom-up) and greedy examples
@ -166,26 +166,26 @@ skup pravila koja precizno definiraju niz operacija.
* `A` [N-Queens Problem](src/algorithms/uncategorized/n-queens) * `A` [N-Queens Problem](src/algorithms/uncategorized/n-queens)
* `A` [Knight's Tour](src/algorithms/uncategorized/knight-tour) * `A` [Knight's Tour](src/algorithms/uncategorized/knight-tour)
### Algorithms by Paradigm ### Algoritmi Paradigme
An algorithmic paradigm is a generic method or approach which underlies the design of a class Algoritmička paradigma je generička metoda ili pristup koji leži u osnovi dizajna klase
of algorithms. It is an abstraction higher than the notion of an algorithm, just as an algoritama. To je apstrakcija viša od pojma algoritma, baš kao i
algorithm is an abstraction higher than a computer program. sto je i algoritam viša apstrakcija od računarskog programa.
* **Brute Force** - look at all the possibilities and selects the best solution * ** Brute Force ** - sagledajte sve mogućnosti i odaberite najbolje rješenje
* `B` [Linear Search](src/algorithms/search/linear-search) * `B` [Linear Search](src/algorithms/search/linear-search)
* `B` [Rain Terraces](src/algorithms/uncategorized/rain-terraces) - trapping rain water problem * `B` [Rain Terraces](src/algorithms/uncategorized/rain-terraces) - trapping rain water problem
* `B` [Recursive Staircase](src/algorithms/uncategorized/recursive-staircase) - count the number of ways to reach to the top * `B` [Recursive Staircase](src/algorithms/uncategorized/recursive-staircase) - count the number of ways to reach to the top
* `A` [Maximum Subarray](src/algorithms/sets/maximum-subarray) * `A` [Maximum Subarray](src/algorithms/sets/maximum-subarray)
* `A` [Travelling Salesman Problem](src/algorithms/graph/travelling-salesman) - shortest possible route that visits each city and returns to the origin city * `A` [Travelling Salesman Problem](src/algorithms/graph/travelling-salesman) - shortest possible route that visits each city and returns to the origin city
* `A` [Discrete Fourier Transform](src/algorithms/math/fourier-transform) - decompose a function of time (a signal) into the frequencies that make it up * `A` [Discrete Fourier Transform](src/algorithms/math/fourier-transform) - decompose a function of time (a signal) into the frequencies that make it up
* **Greedy** - choose the best option at the current time, without any consideration for the future * **Greedy** - odaberite najbolju opciju u ovom trenutku, bez ikakvog razmatranja za budućnost
* `B` [Jump Game](src/algorithms/uncategorized/jump-game) * `B` [Jump Game](src/algorithms/uncategorized/jump-game)
* `A` [Unbound Knapsack Problem](src/algorithms/sets/knapsack-problem) * `A` [Unbound Knapsack Problem](src/algorithms/sets/knapsack-problem)
* `A` [Dijkstra Algorithm](src/algorithms/graph/dijkstra) - finding the shortest path to all graph vertices * `A` [Dijkstra Algorithm](src/algorithms/graph/dijkstra) - finding the shortest path to all graph vertices
* `A` [Prim’s Algorithm](src/algorithms/graph/prim) - finding Minimum Spanning Tree (MST) for weighted undirected graph * `A` [Prim’s Algorithm](src/algorithms/graph/prim) - finding Minimum Spanning Tree (MST) for weighted undirected graph
* `A` [Kruskal’s Algorithm](src/algorithms/graph/kruskal) - finding Minimum Spanning Tree (MST) for weighted undirected graph * `A` [Kruskal’s Algorithm](src/algorithms/graph/kruskal) - finding Minimum Spanning Tree (MST) for weighted undirected graph
* **Divide and Conquer** - divide the problem into smaller parts and then solve those parts * **Divide and Conquer** - podijeli problem na manje dijelove, a zatim riješi te dijelove
* `B` [Binary Search](src/algorithms/search/binary-search) * `B` [Binary Search](src/algorithms/search/binary-search)
* `B` [Tower of Hanoi](src/algorithms/uncategorized/hanoi-tower) * `B` [Tower of Hanoi](src/algorithms/uncategorized/hanoi-tower)
* `B` [Pascal's Triangle](src/algorithms/math/pascal-triangle) * `B` [Pascal's Triangle](src/algorithms/math/pascal-triangle)
@ -200,7 +200,7 @@ algorithm is an abstraction higher than a computer program.
* `B` [Best Time To Buy Sell Stocks](src/algorithms/uncategorized/best-time-to-buy-sell-stocks) - divide and conquer and one-pass examples * `B` [Best Time To Buy Sell Stocks](src/algorithms/uncategorized/best-time-to-buy-sell-stocks) - divide and conquer and one-pass examples
* `A` [Permutations](src/algorithms/sets/permutations) (with and without repetitions) * `A` [Permutations](src/algorithms/sets/permutations) (with and without repetitions)
* `A` [Combinations](src/algorithms/sets/combinations) (with and without repetitions) * `A` [Combinations](src/algorithms/sets/combinations) (with and without repetitions)
* **Dynamic Programming** - build up a solution using previously found sub-solutions * **Dynamic Programming** - izgraditi rješenje koristeći prethodno pronađena podrešenja
* `B` [Fibonacci Number](src/algorithms/math/fibonacci) * `B` [Fibonacci Number](src/algorithms/math/fibonacci)
* `B` [Jump Game](src/algorithms/uncategorized/jump-game) * `B` [Jump Game](src/algorithms/uncategorized/jump-game)
* `B` [Unique Paths](src/algorithms/uncategorized/unique-paths) * `B` [Unique Paths](src/algorithms/uncategorized/unique-paths)
@ -218,9 +218,8 @@ algorithm is an abstraction higher than a computer program.
* `A` [Bellman-Ford Algorithm](src/algorithms/graph/bellman-ford) - finding the shortest path to all graph vertices * `A` [Bellman-Ford Algorithm](src/algorithms/graph/bellman-ford) - finding the shortest path to all graph vertices
* `A` [Floyd-Warshall Algorithm](src/algorithms/graph/floyd-warshall) - find the shortest paths between all pairs of vertices * `A` [Floyd-Warshall Algorithm](src/algorithms/graph/floyd-warshall) - find the shortest paths between all pairs of vertices
* `A` [Regular Expression Matching](src/algorithms/string/regular-expression-matching) * `A` [Regular Expression Matching](src/algorithms/string/regular-expression-matching)
* **Backtracking** - similarly to brute force, try to generate all possible solutions, but each time you generate next solution you test * **Backtracking** - slično kao brute force, pokušaj generirati sva moguća rješenja, ali svaki put kada generiramo sljedeće rješenje testiramo
if it satisfies all conditions, and only then continue generating subsequent solutions. Otherwise, backtrack, and go on a da li zadovoljava sve uvjete, a tek onda nastavimo s generiranjem sljedećih rješenja. U suprotnom, vrati se i idi dalje trazeci drugi put pronalaženja rješenja. Uobičajeno se koristi DFS traversal of state-space.
different path of finding a solution. Normally the DFS traversal of state-space is being used.
* `B` [Jump Game](src/algorithms/uncategorized/jump-game) * `B` [Jump Game](src/algorithms/uncategorized/jump-game)
* `B` [Unique Paths](src/algorithms/uncategorized/unique-paths) * `B` [Unique Paths](src/algorithms/uncategorized/unique-paths)
* `B` [Power Set](src/algorithms/sets/power-set) - all subsets of a set * `B` [Power Set](src/algorithms/sets/power-set) - all subsets of a set
@ -228,13 +227,13 @@ different path of finding a solution. Normally the DFS traversal of state-space
* `A` [N-Queens Problem](src/algorithms/uncategorized/n-queens) * `A` [N-Queens Problem](src/algorithms/uncategorized/n-queens)
* `A` [Knight's Tour](src/algorithms/uncategorized/knight-tour) * `A` [Knight's Tour](src/algorithms/uncategorized/knight-tour)
* `A` [Combination Sum](src/algorithms/sets/combination-sum) - find all combinations that form specific sum * `A` [Combination Sum](src/algorithms/sets/combination-sum) - find all combinations that form specific sum
* **Branch & Bound** - remember the lowest-cost solution found at each stage of the backtracking * **Branch & Bound** - pamti se najjefikasnije rješenje pronađeno u svakoj fazi povratka unatrag,
search, and use the cost of the lowest-cost solution found so far as a lower bound on the cost of pretraži i upotrijebi cijenu tog rješenja pronađenog do sada kao donju granicu cijene
a least-cost solution to the problem, in order to discard partial solutions with costs larger than the za najjeftinije/najefikasnije (koje trosi najmanje resursa) rješenje problema, kako bi se odbacila djelomična rješenja s troškovima većim od
lowest-cost solution found so far. Normally BFS traversal in combination with DFS traversal of state-space do sada pronađenog najjeftinijeg/najefikasnijeg rješenja. Uobicajeno se koristi BFS traversal u kombinaciji sa DFS traversal of state-space
tree is being used. tree.
## How to use this repository ## Kako koristiti ovaj repozitorij
**Install all dependencies** **Install all dependencies**