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A Suffix Tree is a compressed tree containing all the suffixes of the given text as their keys and positions in the text as their values. Suffix Tree provides a particularly fast implementation for many important string operations. This data structure is very related to Suffix Array data structure.


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The suffix i (or the i-th suffix) of a (usually long) text string T is a 'special case' of substring that goes from the i-th character of the string up to the last character of the string.


For example, if T = "STEVEN$", then suffix 0 of T is "STEVEN$" (0-based indexing), suffix 2 of T is "EVEN$", suffix 4 of T is "EN$", etc.


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The visualization of Suffix Tree of a string T is basically a rooted tree where path label (concatenation of edge label(s)) from root to each leaf describes a suffix of T. Each leaf vertex is a suffix and the integer value written inside the leaf vertex is the suffix number.


An internal vertex will branch to more than one child vertex, therefore there are more than one suffix from the root to the leaves via this internal vertex. The path label of an internal vertex is a common prefix among those suffix(es).


Another pro-tip: We designed this visualization and this e-Lecture mode to look good on 1366x768 resolution or larger (typical modern laptop resolution in 2017). 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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The Suffix Tree above is built from string T = "GATAGACA$" that have these 9 suffixes:

iSuffix
0GATAGACA$
1ATAGACA$
2TAGACA$
3AGACA$
4GACA$
5ACA$
6CA$
7A$
8$

Now verify that the path labels of suffix 7/6/2 are "A$"/"CA$"/"TAGACA$", respectively (there are 6 other suffixes). The internal vertices with path label "A"/"GA" branch out to 4 suffixes {7, 5, 3, 1}/2 suffixes {4, 0}, respectively (we ignore the trivial internal vertex = root vertex that branches out to all 9 suffixes).

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In order to ensure that every suffix of the input string T ends in a leaf vertex, we enforce that string T ends with a special terminating symbol '$' that is not used in the original string T and has ASCII value lower than the lowest allowable character in T (which is character 'A'). This way, edge label '$' always appear at the leftmost edge of an internal vertex of this Suffix Tree visualization.


For the Suffix Tree example above (for T = "GATAGACA$"), if we do not have terminating symbol '$', notice that suffix 7 "A" does NOT end in a leaf vertex and can complicate some operations later.

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As we have ensured that all suffixes end at a leaf vertex, there are at most n leaves/suffixes in a Suffix Tree. All internal vertices (including the root vertex if it is an internal vertex) are always branching thus there can be at most n-1 such vertices, as shown with one of the extreme test case on the right.


The maximum number of vertices in a Suffix Tree is thus = n (leaves) + (n-1) internal vertices = 2n-1 = O(n) vertices. As Suffix Tree is a tree, the maximum number of edges in a Suffix Tree is also (2n-1)-1 = O(n) edges.

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When all the characters in string T is all distinct (e.g. T = "ABCDE$"), we can have the following very short Suffix Tree with exactly n+1 vertices (+1 due to root vertex).

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All available operations on the Suffix Tree in this visualization are listed below:

  1. Build Suffix Tree (instant) — instant-build the Suffix Tree from string T.
  2. Search — Find the vertex in Suffix Tree of a (usually longer) string T that has path label containing the (usually shorter) pattern/search string P.
  3. Longest Repeated Substring (LRS) — Find the deepest internal vertex (as that vertex shares common prefix between two (or more) suffixes of T).
  4. Longest Common Substring (LCS) — Find the deepest internal vertex that contains suffixes from two different original strings.
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In this visualization, we only show the fully constructed Suffix Tree without describing the details of the O(n) Suffix Tree construction algorithm — it is a bit too complicated.


We limit the input to only accept 12 UPPERCASE alphabet and the special terminating symbol '$' characters (ie.g [A-Z$]). 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.

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Assuming that the Suffix Tree of a (usually longer) string T (of length n) has been built, we want to find all occurrences of pattern/search string P (of length m).


To do this, we search for the vertex x in the suffix Tree of T which has path label that represents P. Once we find this vertex x, all the leaves in the subtree rooted at x are the occurrences.


Time complexity: O(m+occ) where occ is the total number of occurrences.


For example, on the Suffix Tree of T = "GATAGACA$" above, let's try finding:

  1. Search("A"), occurrences = {7, 5, 3, 1}
  2. Search("GA"), occurrences = {4, 0}
  3. P = "T", should return occurrences = {2}, but there is a silly bug that we have not killed yet
  4. P = "Z", should return occurrences = {NIL}, but there is a silly bug that we have not killed yet
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Assuming that the Suffix Tree of a (usually longer) string T (of length n) has been built, we can find the Longest Repeated Substring (LRS) in T by simply finding the deepest internal vertex of the Suffix Tree of T.


This is because each internal vertex of the Suffix Tree of T branches out to at least two (or more) suffixes, i.e. the path label (common prefix of these suffixes) are repeated.


The internal vertex with the deepest/longest path label is the required answer, which can be found in O(n) with a simple tree traversal.


Without further ado, try LRS(T) on the Suffix Tree of string T = "GATAGACA$" above.

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This time, we need two input strings T1 and T2 that terminate with symbol '$'/'#', respectively. We then create the generalized Suffix Tree of these two strings T1+T2. Then, we can find the Longest Common Substring (LCS) of those two strings T1 and T2 by simply finding the deepest and valid internal vertex of the generalized Suffix Tree of T1+T2.


This is because each internal vertex of the Suffix Tree of T branches out to at least two (or more) suffixes, i.e. the path label (common prefix of these suffixes) are repeated. Then, we add an additional constraint where an internal vertex is considered valid (to be considered as LCS candidate) only if it represents suffixes from both strings, i.e. not just repeated, but a common substring found in both T1 and T2.


The valid internal vertex with the deepest/longest path label is the required answer, which can be found in O(n) with a simple tree traversal.


Without further ado, try LCS(T1,T2) on the generalized Suffix Tree of string T1 = "GATAGACA$" and T2 = "CATABB#" (notice that the UI will change to generalized Suffix Tree version).

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There are a few other things that we can do with Suffix Tree like "Finding Longest Repeated Substring without overlap", "Finding Longest Common Substring of ≥ 2 strings", etc, but we will keep that for later.


We will continue the discussion of this String-specific data structure with the more versatile to Suffix Array data structure.

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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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Build Suffix Tree (instant)

Longest Repeated Substring

========================

Longest Common Substring

>

GATAGACA$

BANANA$

MISSISSIPPI$

AAAAAAA$

Go

Build Generalized ST and Compute LCS

About Team Terms of use

About

VisuAlgo was conceptualised in 2011 by Dr Steven Halim as a tool to help his students better understand data structures and algorithms, by allowing them to learn the basics on their own and at their own pace.

VisuAlgo contains many advanced algorithms that are discussed in Dr Steven Halim's book ('Competitive Programming', co-authored with his brother Dr Felix Halim) and beyond. Today, some of these advanced algorithms visualization/animation can only be found in VisuAlgo.

Though specifically designed for National University of Singapore (NUS) students taking various data structure and algorithm classes (e.g. CS1010, CS1020, CS2010, CS2020, CS3230, and CS3230), as advocators of online learning, we hope that curious minds around the world will find these visualisations useful too.

VisuAlgo is not designed to work well on small touch screens (e.g. smartphones) from the outset due to the need to cater for many complex algorithm visualizations that require lots of pixels and click-and-drag gestures for interaction. The minimum screen resolution for a respectable user experience is 1024x768 and only the landing page is relatively mobile-friendly.

VisuAlgo is an ongoing project and more complex visualisations are still being developed.

The most exciting development is the automated question generator and verifier (the online quiz system) that allows students to test their knowledge of basic data structures and algorithms. The questions are randomly generated via some rules and students' answers are instantly and automatically graded upon submission to our grading server. This online quiz system, when it is adopted by more CS instructors worldwide, should technically eliminate manual basic data structure and algorithm questions from typical Computer Science examinations in many Universities. By setting a small (but non-zero) weightage on passing the online quiz, a CS instructor can (significantly) increase his/her students mastery on these basic questions as the students have virtually infinite number of training questions that can be verified instantly before they take the online quiz. The training mode currently contains questions for 12 visualization modules. We will soon add the remaining 8 visualization modules so that every visualization module in VisuAlgo have online quiz component.

Another active branch of development is the internationalization sub-project of VisuAlgo. We want to prepare a database of CS terminologies for all English text that ever appear in VisuAlgo system. This is a big task and requires crowdsourcing. Once the system is ready, we will invite VisuAlgo visitors to contribute, especially if you are not a native English speaker. Currently, we have also written public notes about VisuAlgo in various languages: zh, id, kr, vn, th.

Team

Project Leader & Advisor (Jul 2011-present)
Dr Steven Halim, Senior Lecturer, School of Computing (SoC), National University of Singapore (NUS)
Dr Felix Halim, Software Engineer, Google (Mountain View)

Undergraduate Student Researchers 1 (Jul 2011-Apr 2012)
Koh Zi Chun, Victor Loh Bo Huai

Final Year Project/UROP students 1 (Jul 2012-Dec 2013)
Phan Thi Quynh Trang, Peter Phandi, Albert Millardo Tjindradinata, Nguyen Hoang Duy

Final Year Project/UROP students 2 (Jun 2013-Apr 2014)
Rose Marie Tan Zhao Yun, Ivan Reinaldo

Undergraduate Student Researchers 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

Final Year Project/UROP students 3 (Jun 2014-Apr 2015)
Erin Teo Yi Ling, Wang Zi

Final Year Project/UROP students 4 (Jun 2016-Dec 2017)
Truong Ngoc Khanh, John Kevin Tjahjadi, Gabriella Michelle, Muhammad Rais Fathin Mudzakir

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

Acknowledgements
This project is made possible by the generous Teaching Enhancement Grant from NUS Centre for Development of Teaching and Learning (CDTL).

Terms of use

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, course webpage, blog review, email, 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 (http://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 a real examination in NUS. Other interested CS instructor should contact Steven if you want to try such 'test mode'.

List of Publications

This work has been presented briefly at the CLI Workshop at the ACM 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).

This work is done mostly by my past students. The most recent final reports are here: Erin, Wang Zi, Rose, Ivan.

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.