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Suffix Array is a sorted array of all suffixes of a given (usually long) text string T of length n characters (n can be in order of hundred thousands characters).


Suffix Array is a simple, yet powerful data structure which is used, among others, in full text indices, data compression algorithms, and within the field of bioinformatics.


This data structure is very related to the Suffix Tree data structure. Both data structures are usually studied together.


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The visualization of Suffix Array is simply a table where each row represents a suffix and each column represents the attributes of the suffixes.


The four (basic) attributes of each row i are:

  1. index i, ranging from 0 to n-1,
  2. SA[i]: the i-th lexicographically smallest suffix of T is the SA[i]-th suffix,
  3. LCP[i]: the Longest Common Prefix between the i-th and the (i-1)-th lexicographically smallest suffixes of T is LCP[i] (we will see the application of this attribute later), and
  4. Suffix T[SA[i]:] - the i-th lexicographically smallest suffix of T is from index SA[i] to the end (index n-1).

Some operations may add more attributes to each row and are explained when that operations are discussed.


Pro-tip 1: Since you are not logged-in, you may be a first time visitor (or not an NUS student) who are not aware of the following keyboard shortcuts to navigate this e-Lecture mode: [PageDown]/[PageUp] to go to the next/previous slide, respectively, (and if the drop-down box is highlighted, you can also use [→ or ↓/← or ↑] to do the same),and [Esc] to toggle between this e-Lecture mode and exploration mode.

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All available operations on the Suffix Array are listed below.

  1. Construct Suffix Array (SA) is the O(n log n) Suffix Array construction algorithm based on the idea by Karp, Miller, & Rosenberg (1972) that sort prefixes of the suffix in increasing length (1, 2, 4, 8, ...).
  2. Search utilizes the fact that the suffixes in Suffix Array are sorted and call two binary searches in O(m log n) to find the first and the last occurrence(s) of pattern string P of length m.
  3. Longest Common Prefix (LCP) between two adjacent suffixes (excluding the first suffix) can be computed in O(n) using the Permuted LCP (PLCP) theorem. The name of this algorithm is Kasai's algorithm.
  4. Longest Repeated Substring (LRS) is a simple O(n) algorithm that finds the suffix with the highest LCP value.
  5. Longest Common Substring (LCS) is a simple O(n) algorithm that finds the suffix with the highest LCP value that comes from two different strings.

Pro-tip 2: We designed this visualization and this e-Lecture mode to look good on 1366x768 resolution or larger (typical modern laptop resolution in 2021). We recommend using Google Chrome to access VisuAlgo. Go to full screen mode (F11) to enjoy this setup. However, you can use zoom-in (Ctrl +) or zoom-out (Ctrl -) to calibrate this.

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In this visualization, we show the proper O(n log n) construction of Suffix Array based on the idea of Karp, Miller, & Rosenberg (1972) that sort prefixes of the suffix in increasing length (1, 2, 4, 8, ...), a.k.a. the prefix doubling algorithm.


We limit the input to only accept 12 (cannot be too long due to the available drawing space — but in the real application of Suffix Tree, n can be in order of hundred thousand to million characters) UPPERCASE (we delete your lowercase input) alphabet and the special terminating symbol '$' characters (i.e., [A-Z$]). If you do not write a terminating symbol '$' at the back of your input string, we will automatically do so. If you place a '$' in the middle of the input string, they will be ignored. And if you enter an empty input string, we will resort to the default "GATAGACA$".


For convenience, we provide a few classic test case input strings usually found in Suffix Tree/Array lectures, but to showcase the strength of this visualization tool, you are encouraged to enter any 12-characters string of your choice (ending with character '$').


Note that the LCP Array column remains empty in this operation. They are to be computed separately via the Longest Common Prefix operation.


Pro-tip 3: Other than using the typical media UI at the bottom of the page, you can also control the animation playback using keyboard shortcuts (in Exploration Mode): Spacebar to play/pause/replay the animation, / to step the animation backwards/forwards, respectively, and -/+ to decrease/increase the animation speed, respectively.

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This Prefix Doubling Algorithm runs in O(log n) iterations, where for each iteration, it compares substring T[SA[i]:SA[i+k]] with T[SA[i+k]:SA[i+2*k]], i.e., first compare two pairs of characters, then compare first two characters with the next two, then compare the first four characters with the next four, and so on.


This algorithm is best explored via visualization, see ConstructSA("GATAGACA$") in action.


Time complexity: There are O(log n) prefix doubling iterations, and each iteration we call O(n) Radix Sort, thus it runs in O(n log n) — good enough to handle up to n ≤ 200K characters in typical programming competition problems involving long strings.

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After we construct the Suffix Array of T in O(n log n), we can search for the occurrence of Pattern string T in O(m log n) by binary searching the sorted suffixes to find the lower bound (the first occurrence of P as a prefix of any suffix of T) and the upper bound positions (thelast occurrence of P as a prefix of any suffix of T).


Time complexity: O(m log n) and it will return an interval of size k where k is the total number of occurrences.


For example, on the Suffix Array of T = "GATAGACA$" above, try these scenarios:

  1. P returns a range of rows: Search("GA"), occurrences = {4, 0}
  2. P returns one row only: Search("CA"), occurrences = {2}
  3. P is not found in T: Search("WONKA"), occurrences = {NIL}
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We can compute the Longest Common Prefix (LCP) of two adjacent suffixes (in Suffix Array order) in O(n) time using three phases of Kasai's algorithm. This algorithm takes advantage that if we have a long LCP between two adjacent suffixes (in Suffix Array order), that long LCP has lots of overlap with another suffix in positional order when its first character is removed.


The first phase: Compute the value of Phi[], where Phi[SA[i]] = SA[i-1] in O(n). This is to help the algorithm knows in $O(1) time of which Suffix is behind Suffix-SA[i] in Suffix Array order.


The second phase: Compute the PLCP[] values between a Suffix-i in positional order with Suffix-Phi[i] (the one behind Suffix-i in Suffix Array order). When we advance to the next index i+1 in positional order, we will remove the front most character of the suffix, but possibly retain lots of LCP value between Suffix-(i+1) and Suffix-Phi[(i+1)]. PLCP Theorem (not proven) shows that the LCP values can only be incremented up to n times, and thus can only be decremented at most n times too, making the overall complexity of the second phase to be also O(n).


The third phase: We compute the value of LCP[], where LCP[i] = PLCP[SA[i]] in O(n). This LCP values are the one that we use for other Suffix Array applications later.


Time complexity: Kasai's algorithm utilizes the PLCP theorem where the total number of increase (and decrease) operations of the value of the LCP is at most O(n). Thus Kasai's algorithm runs in O(n) overall. Thus, the combination of O(n log n) Suffix Array construction (via the Prefix Doubling algorithm) and the O(n) computation of LCP Array using this Kasai's algorithm is good enough to handle up to n ≤ 200K characters in typical programming competition problems involving long strings.

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After we construct the Suffix Array of T in O(n log n) and compute its LCP Array in O(n), we can find the Longest Repeated Substring (LRS) in T by simply iterating through all LCP values and reporting the largest one.


This is because each value LCP[i] the LCP Array means the longest common prefix between two lexicographically adjacent suffixes: Suffix-i and Suffix-(i-1). This corresponds to an internal vertex of the equivalent Suffix Tree of T that branches out to at least two (or more) suffixes, thus this common prefix of these adjacent suffixes are repeated.


The longest common (repeated) prefix is the required answer, which can be found in O(n) by going through the LCP array once.


Without further ado, try LRS("GATAGACA$"). We have LRS = "GA".


It is possible that T contains more than one LRS, e.g., try LRS("BANANABAN$").
We have LRS = "ANA" (actually overlap) or "BAN" (without overlap).

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After we construct the generalized Suffix Array of the concatenation of both strings T1$T2# of length n = n1+n2 in O(n log n) and compute its LCP Array in O(n), we can find the Longest Repeated Substring (LRS) in T by simply iterating through all LCP values and reporting the largest one that comes from two different strings.


Without further ado, try LCS("GATAGACA$", "CATA#") on the generalized Suffix Array of string T1 = "GATAGACA$" and T2 = "CATA#". We have LCS = "ATA".

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You are allowed to use/modify our implementation code for fast Suffix Array+LCP: sa_lcp.cpp | py | java | ml to solve programming contest problems that need it.


You have reached the last slide. Return to 'Exploration Mode' to start exploring!

Note that if you notice any bug in this visualization or if you want to request for a new visualization feature, do not hesitate to drop an email to the project leader: Dr Steven Halim via his email address: stevenhalim at gmail dot com.

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Buat Larik Akhiran

Akhiran Sama Terpanjang

Substring Berulang Terpanjang

Substring Sama Terpanjang

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GATAGACA$

BANANABAN$

MISSISSIPPI$

ABRACADABRA$

RATATAT$

AAAAAAA$

ABCDE$

AABBCC$

T =

Lakukan

T1 =
T2 =

Lakukan

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Tentang Tim Syarat Guna Kebijakan Privasi

Tentang

VisuAlgo digagas pada tahun 2011 oleh Dr Steven Halim sebagai alat untuk membantu murid-muridnya mengerti struktur-struktur data dan algoritma-algoritma, dengan memampukan mereka untuk mempelajari dasar-dasarnya secara otodidak dan dengan kecepatan mereka sendiri.


VisuAlgo mempunya banyak algoritma-algoritma tingkat lanjut yang dibahas didalam buku Dr Steven Halim ('Competitive Programming', yang ditulis bersama adiknya Dr Felix Halim dan temannya Dr Suhendry Effendy) dan lebih lagi. Hari ini, beberapa dari visualisasi/animasi algoritma-algoritma tingkat lanjut ini hanya ditemukan di VisuAlgo.


Meskipun pada khususnya didesain untuk murid-murid National University of Singapore (NUS) yang mengambil berbagai kelas-kelas struktur data dan algoritma (contoh: CS1010/setara, CS2040/setara, CS3230, CS3233, dan CS4234), sebagai pendukung pembelajaran online, kami berharap bahwa orang-orang di berbagai belahan dunia menemukan visualisasi-visualisasi di website ini berguna bagi mereka juga.


VisuAlgo tidak didesain untuk layar sentuh kecil (seperti smartphones) dari awalnya karena kami harus membuat banyak visualisasi-visualisasi algoritma kompleks yang membutuhkan banyak pixels dan gestur klik-dan-tarik untuk interaksinya. Resolusi layar minimum untuk pengalaman pengguna yang lumayan adalah 1024x768 dan hanya halaman utama VisuAlgo yang secara relatif lebih ramah dengan layar kecil. Tetapi, kami sedang bereksperimen dengan versi mobil (kecil) dari VisuAlgo yang akan siap pada April 2022.


VisuAlgo adalah proyek yang sedang terus berlangsung dan visualisasi-visualisasi yang lebih kompleks sedang dibuat.


Perkembangan yang paling menarik adalah pembuatan pertanyaan otomatis (sistem kuis online) yang bisa dipakai oleh murid-murid untuk menguji pengetahuan mereka tentang dasar struktur-struktur data dan algoritma-algoritma. Pertanyaan-pertanyaan dibuat secara acak dengan semacam rumus dan jawaban-jawaban murid-murid dinilai secara instan setelah dikirim ke server penilai kami. Sistem kuis online ini, saat sudah diadopsi oleh banyak dosen Ilmu Komputer diseluruh dunia, seharusnya bisa menghapuskan pertanyaan-pertanyaan dasar tentang struktur data dan algoritma dari ujian-ujian di banyak Universitas. Dengan memberikan bobot kecil (tapi tidak kosong) supaya murid-murid mengerjakan kuis online ini, seorang dosen Ilmu Komputer dapat dengan signifikan meningkatkan penguasaan materi dari murid-muridnya tentang pertanyaan-pertanyaan dasar ini karena murid-murid mempunyai kesempatan untuk menjawab pertanyaan-pertanyaan ini yang bisa dinilai secara instan sebelum mereka mengambil kuis online yang resmi. Mode latihan saat ini mempunyai pertanyaan-pertanyaan untuk 12 modul visualisasi. Kami akan segera menambahkan pertanyaan-pertanyaan untuk 12 modul visualisasi yang lainnya sehingga setiap setiap modul visualisasi di VisuAlgo mempunyai komponen kuis online.


Kami telah menerjemahkan halaman-halaman VisuALgo ke tiga bahasa-bahasa utama: Inggris, Mandarin, dan Indonesia. Saat ini, kami juga telah menulis catatan-catatan publik tentang VisuAlgo dalam berbagai bahasa:

id, kr, vn, th.

Tim

Pemimpin & Penasihat Proyek (Jul 2011-sekarang)
Dr Steven Halim, Senior Lecturer, School of Computing (SoC), National University of Singapore (NUS)
Dr Felix Halim, Senior Software Engineer, Google (Mountain View)

Murid-Murid S1 Peniliti 1 (Jul 2011-Apr 2012)
Koh Zi Chun, Victor Loh Bo Huai

Murid-Murid Proyek Tahun Terakhir/UROP 1 (Jul 2012-Dec 2013)
Phan Thi Quynh Trang, Peter Phandi, Albert Millardo Tjindradinata, Nguyen Hoang Duy

Murid-Murid Proyek Tahun Terakhir/UROP 2 (Jun 2013-Apr 2014)
Rose Marie Tan Zhao Yun, Ivan Reinaldo

Murid-Murid S1 Peniliti 2 (May 2014-Jul 2014)
Jonathan Irvin Gunawan, Nathan Azaria, Ian Leow Tze Wei, Nguyen Viet Dung, Nguyen Khac Tung, Steven Kester Yuwono, Cao Shengze, Mohan Jishnu

Murid-Murid Proyek Tahun Terakhir/UROP 3 (Jun 2014-Apr 2015)
Erin Teo Yi Ling, Wang Zi

Murid-Murid Proyek Tahun Terakhir/UROP 4 (Jun 2016-Dec 2017)
Truong Ngoc Khanh, John Kevin Tjahjadi, Gabriella Michelle, Muhammad Rais Fathin Mudzakir

Murid-Murid Proyek Tahun Terakhir/UROP 5 (Aug 2021-Dec 2022)
Liu Guangyuan, Manas Vegi, Sha Long, Vuong Hoang Long

List of translators who have contributed ≥100 translations can be found at statistics page.

Ucapan Terima Kasih
Proyek ini dimungkinkan karena Hibah Pengembangan Pengajaran dari NUS Centre for Development of Teaching and Learning (CDTL).

Syarat Guna

VisuAlgo is free of charge for Computer Science community on earth. If you like VisuAlgo, the only "payment" that we ask of you is for you to tell the existence of VisuAlgo to other Computer Science students/instructors that you know =) via Facebook/Twitter/Instagram/TikTok posts, course webpages, blog reviews, emails, etc.

If you are a data structure and algorithm student/instructor, you are allowed to use this website directly for your classes. If you take screen shots (videos) from this website, you can use the screen shots (videos) elsewhere as long as you cite the URL of this website (https://visualgo.net) and/or list of publications below as reference. However, you are NOT allowed to download VisuAlgo (client-side) files and host it on your own website as it is plagiarism. As of now, we do NOT allow other people to fork this project and create variants of VisuAlgo. Using the offline copy of (client-side) VisuAlgo for your personal usage is fine.

Note that VisuAlgo's online quiz component is by nature has heavy server-side component and there is no easy way to save the server-side scripts and databases locally. Currently, the general public can only use the 'training mode' to access these online quiz system. Currently the 'test mode' is a more controlled environment for using these randomly generated questions and automatic verification for real examinations in NUS.

List of Publications

This work has been presented briefly at the CLI Workshop at the ICPC World Finals 2012 (Poland, Warsaw) and at the IOI Conference at IOI 2012 (Sirmione-Montichiari, Italy). You can click this link to read our 2012 paper about this system (it was not yet called VisuAlgo back in 2012) and this link for the short update in 2015 (to link VisuAlgo name with the previous project).

This work is done mostly by my past students. 

Bug Reports or Request for New Features

VisuAlgo is not a finished project. Dr Steven Halim is still actively improving VisuAlgo. If you are using VisuAlgo and spot a bug in any of our visualization page/online quiz tool or if you want to request for new features, please contact Dr Steven Halim. His contact is the concatenation of his name and add gmail dot com.

Kebijakan Privasi

Versi 1.1 (Dimutakhirkan Jum, 14 Jan 2022).

Pemberitahuan kepada semua pengunjung: Kami saat ini menggunakan Google Analytics untuk mendapatkan pengertian garis besar tentang pengunjung-pengunjung situs kami. Kami sekarang memberikan opsi kepada pengguna untuk Menerima atau Menolak pelacak ini.

Sejak Rabu, 22 Des 2021, hanya staff-staff/murid-murid National University of Singapore (NUS) dan dosen-dosen Ilmu Komputer diluar dari NUS yang telah menulis kepada Steven dapat login ke VisuAlgo, orang-orang lain di dunia harus memakai VisuAlgo sebagai pengguna anonim yang tidak benar-benar terlacak selain apa yang dilacak oleh Google Analytics.

Untuk murid-murid NUS yang mengambil mata kuliah yang menggunakan VisuAlgo: Dengan menggunakan akun VisuAlgo (sebuah tupel dari alamat email NUS resmi, nama murid resmi NUS seperti dalam daftar kelas, dan sebuah kata sandi yang dienkripsi pada sisi server — tidak ada data personal lainnya yang disimpan), anda memberikan ijin kepada dosen modul anda untuk melacak pembacaan slide-slide kuliah maya dan kemajuan latihan kuis online yang dibutuhkan untuk menjalankan modul tersebut dengan lancar. Akun VisuAlgo anda akan juga dibutuhkan untuk mengambil kuis-kuis VisuAlgo online resmi sehingga memberikan kredensial akun anda ke orang lain untuk mengerjakan Kuis Online sebagai anda adalah pelanggaran akademis.. Akun pengguna anda akan dihapus setelah modul tersebut selesai kecuali anda memilih untuk menyimpan akun anda (OPT-IN). Akses ke basis data lengkap dari VisuAlgo (dengan kata-kata sandi terenkripsi) dibatasi kepada Steven saja.

Untuk murid-murid NUS lainnya, anda dapat mendaftarkan sendiri sebuah akun VisuAlgo (OPT-IN).

Untuk dosen-dosen Ilmu Komputer di seluruh dunia yang telah menulis kepada Steven, sebuah akun VisuAlgo (alamat email (bukan-NUS), anda dapat menggunakan nama panggilan apapun, dan kata sandi terenkripsi) dibutuhkan untuk membedakan kredensial online anda dibandingkan dengan orang-orang lain di dunia. Akun anda akan dilacak seperti seorang murid NUS biasa diatas tetapi akun anda akan mempunya fitur-fiture spesifik untuk dosen-dosen Ilmu Komputer, yaitu kemampuan untuk melihat slide-slide tersembunyi yang berisi jawaban-jawaban (menarik) dari pertanyaan-pertanyaan yang dipresentasikan di slide-slide sebelumnya sebelum slide-slide tersembunyi tersebut. Anda juga dapat mengakses setingan Susah dari Kuis-Kuis Online VisuAlgo. Anda dapat dengan bebas menggunakan materi-materia untuk memperkaya kelas-kelas struktur-struktur data dan algoritma-algoritma anda. Catatan: Mungkin ada fitur-fitur khusus tambahan untuk dosen Ilmu Komputer di masa mendatang.

Untuk siapapun dengan akun VisuAlgo, anda dapat membuang akun anda sendiri bila anda tidak mau lagi diasosiasikan dengan tool VisuAlgo ini.