The document discusses stacks and their implementation. It defines a stack as a LIFO data structure where elements can only be inserted or removed from the top. The basic stack operations are PUSH, which inserts an element onto the top of the stack, and POP, which removes the top element. Stacks can be used to check if parentheses in an arithmetic expression are correctly nested by scanning the expression and using a stack to match opening and closing parentheses.
Lecture06 methods for-making_data_structures_v2Hariz Mustafa
The document discusses methods for implementing dynamic data structures using arrays and linked lists. It describes how insertion and removal of elements from an array requires shifting all subsequent elements, which is inefficient. Linked lists allow efficient insertion and removal by using pointer connections between nodes. The document provides an example of traversing a linked list to search for a node matching given criteria.
Queues are first-in, first-out data structures where elements are added to the rear of the queue and removed from the front, and can be implemented using arrays where the front and rear indices track the start and end of the queue, with circular queue implementations overcoming space limitations by treating the array as a circular buffer. Common queue operations include enqueue to add an element, dequeue to remove an element, and checks for empty and full queues.
The document discusses thread lifecycle and methods in Java. It explains that a thread goes through different states like new, ready, running, blocked, and dead. It provides a state transition diagram and describes each state. It also discusses various thread methods like start(), stop(), suspend(), resume(), wait(), notify(), isAlive(), and join(). Example programs are provided to demonstrate using these methods and the thread lifecycle.
The talk was delivered by Ying Zhang at the the First International Array Databases Workshop , co-located with the EDBT/ICDT 2011 Joint Conference on March 25, 2011 in Uppsala, Sweden.
Publication: http://bit.ly/zyQPBq
Abstract:
Scientific applications are still poorly served by contemporary relational database systems. At best, the system provides a bridge towards an external library using user-defined functions, explicit import/export facilities or linked-in Java/C# interpreters. Time has come to rectify this with SciQL1, a SQL query language for scientific applications with arrays as first class citizens. It provides a seamless symbiosis of array-, set-, and sequence- interpretation using a clear separation of the mathematical object from its underlying implementation. A key innovation is to extend valuebased grouping in SQL:2003 with structural grouping, i.e., fixedsized and unbounded groups based on explicit relationships between their dimension attributes. It leads to a generalization of window-based query processing with wide applicability in science domains. This paper is focused on the language features, extensively illustrated with examples of its intended use.
This document provides an overview of key concepts in the study of discrete random variables including:
- Definitions of discrete and continuous random variables as well as probability mass functions and density functions.
- Examples of common discrete distributions like the Bernoulli and Binomial distributions.
- How to calculate the mean and variance of discrete random variables.
- Notation used to define random variables and their distributions.
12X1 T01 03 integrating derivative on functionNigel Simmons
The document discusses various techniques for integrating derivatives. It provides examples of integrating common derivatives and explains the steps. Example integrals presented include 1/(7-3x), 8x+5, x5, 1/5x, (4x+1)/(2x+1), ∫x2/(x2+1)dx, and differentiating and integrating x3logx.
From Lisp to Clojure/Incanter and RAn Introductionelliando dias
This document provides a comparison between the statistical computing languages R and Clojure/Incanter. It discusses the histories and philosophies behind Lisp, Fortran, R and Clojure. Key differences noted are that Clojure runs on the Java Virtual Machine, allowing it to leverage Java libraries, while R is primarily written in C and Fortran. Incanter is presented as a Clojure-based platform for statistical computing and graphics that is more immature than R but allows easier access to Java capabilities. Basic syntax comparisons are provided.
This document provides an overview of using Clojure for data science. It discusses why Clojure is suitable for data science due to its functional programming capabilities, performance on the JVM, and rich library ecosystem. It introduces core.matrix, a Clojure library that provides multi-dimensional array programming functionality through Clojure protocols. The document covers core.matrix concepts like array creation and manipulation, element-wise operations, broadcasting, and optional support for mutability. It also discusses core.matrix implementation details like the performance benefits of using Clojure protocols.
Lecture06 methods for-making_data_structures_v2Hariz Mustafa
The document discusses methods for implementing dynamic data structures using arrays and linked lists. It describes how insertion and removal of elements from an array requires shifting all subsequent elements, which is inefficient. Linked lists allow efficient insertion and removal by using pointer connections between nodes. The document provides an example of traversing a linked list to search for a node matching given criteria.
Queues are first-in, first-out data structures where elements are added to the rear of the queue and removed from the front, and can be implemented using arrays where the front and rear indices track the start and end of the queue, with circular queue implementations overcoming space limitations by treating the array as a circular buffer. Common queue operations include enqueue to add an element, dequeue to remove an element, and checks for empty and full queues.
The document discusses thread lifecycle and methods in Java. It explains that a thread goes through different states like new, ready, running, blocked, and dead. It provides a state transition diagram and describes each state. It also discusses various thread methods like start(), stop(), suspend(), resume(), wait(), notify(), isAlive(), and join(). Example programs are provided to demonstrate using these methods and the thread lifecycle.
The talk was delivered by Ying Zhang at the the First International Array Databases Workshop , co-located with the EDBT/ICDT 2011 Joint Conference on March 25, 2011 in Uppsala, Sweden.
Publication: http://bit.ly/zyQPBq
Abstract:
Scientific applications are still poorly served by contemporary relational database systems. At best, the system provides a bridge towards an external library using user-defined functions, explicit import/export facilities or linked-in Java/C# interpreters. Time has come to rectify this with SciQL1, a SQL query language for scientific applications with arrays as first class citizens. It provides a seamless symbiosis of array-, set-, and sequence- interpretation using a clear separation of the mathematical object from its underlying implementation. A key innovation is to extend valuebased grouping in SQL:2003 with structural grouping, i.e., fixedsized and unbounded groups based on explicit relationships between their dimension attributes. It leads to a generalization of window-based query processing with wide applicability in science domains. This paper is focused on the language features, extensively illustrated with examples of its intended use.
This document provides an overview of key concepts in the study of discrete random variables including:
- Definitions of discrete and continuous random variables as well as probability mass functions and density functions.
- Examples of common discrete distributions like the Bernoulli and Binomial distributions.
- How to calculate the mean and variance of discrete random variables.
- Notation used to define random variables and their distributions.
12X1 T01 03 integrating derivative on functionNigel Simmons
The document discusses various techniques for integrating derivatives. It provides examples of integrating common derivatives and explains the steps. Example integrals presented include 1/(7-3x), 8x+5, x5, 1/5x, (4x+1)/(2x+1), ∫x2/(x2+1)dx, and differentiating and integrating x3logx.
From Lisp to Clojure/Incanter and RAn Introductionelliando dias
This document provides a comparison between the statistical computing languages R and Clojure/Incanter. It discusses the histories and philosophies behind Lisp, Fortran, R and Clojure. Key differences noted are that Clojure runs on the Java Virtual Machine, allowing it to leverage Java libraries, while R is primarily written in C and Fortran. Incanter is presented as a Clojure-based platform for statistical computing and graphics that is more immature than R but allows easier access to Java capabilities. Basic syntax comparisons are provided.
This document provides an overview of using Clojure for data science. It discusses why Clojure is suitable for data science due to its functional programming capabilities, performance on the JVM, and rich library ecosystem. It introduces core.matrix, a Clojure library that provides multi-dimensional array programming functionality through Clojure protocols. The document covers core.matrix concepts like array creation and manipulation, element-wise operations, broadcasting, and optional support for mutability. It also discusses core.matrix implementation details like the performance benefits of using Clojure protocols.
This document summarizes a presentation about machine learning. It begins with a definition of machine learning as giving computers the ability to learn without being explicitly programmed. It then provides examples of tasks that machine learning can perform, such as spam filtering and stock market prediction. The document notes that machine learning works to some degree but not perfectly. It introduces a company called Nuroko that is building a machine learning toolkit with certain desirable properties such as being general purpose, powerful, scalable, real-time, and pragmatic. The document explains why the company chose Clojure as its programming language and provides an overview of some key machine learning concepts and abstractions like vectors, coders, tasks, modules, and algorithms. It concludes
The document provides information about an upcoming statistics workshop, an in-class test covering probability and distributions, expectations for the test, guidance on preparing note sheets, and content on the normal distribution including its probability density function, transformations of normal random variables, and the standard normal distribution.
Writable Foreign Data Wrapper (JPUG Unconference 16-Feb-2013)Kohei KaiGai
The document summarizes the writable foreign data wrapper (FDW) feature in PostgreSQL. It explains that FDWs allow writing to external data sources like they are regular tables. It describes how FDWs work by hooking into the query planning and execution phases. It also discusses challenges for writable FDWs, like identifying rows to update, and proposes solutions like using a "rowid" pseudo-column. Finally, it outlines new APIs needed to support writable FDWs and provides an example of updating a foreign table.
The document describes using threshold-based agent models to optimize plant placement in a landscape. It proposes an agent-based algorithm where individual "plants" search the landscape for optimal locations based on their light and water requirements. A genetic algorithm approach is also mentioned. The goal is to maximize overall plant growth by finding placements where each plant meets a 70% threshold of its ideal growth conditions. Future work could include formal analysis and comparisons to determine how well the approach works at finding the optimal plant collection for a given landscape.
This document discusses techniques for visualizing high-dimensional data, including t-Distributed Stochastic Neighbor Embedding (t-SNE). t-SNE is used to visualize molecular data with thousands of features and won a Kaggle competition by mapping the data based on activity and time. The document also discusses limitations of single maps and introduces multiple maps t-SNE to better model relationships between different concepts.
The Ring programming language version 1.4.1 book - Part 3 of 31Mahmoud Samir Fayed
Ring 1.3 includes several new features and improvements, such as better RingQt and Ring Notepad, new functions, and a form designer. It also allows embedding Ring code without sharing state.
Graphs in the Database: Rdbms In The Social Networks AgeLorenzo Alberton
Despite the NoSQL movement trying to flag traditional databases as a dying breed, the RDBMS keeps evolving and adding new powerful weapons to its arsenal. In this talk we'll explore Common Table Expressions (SQL-99) and how SQL handles recursion, breaking the bi-dimensional barriers and paving the way to more complex data structures like trees and graphs, and how we can replicate features from social networks and recommendation systems. We'll also have a look at window functions (SQL:2003) and the advanced reporting features they make finally possible.
This document provides an introduction and overview to the Python programming language. It includes sections on why learn programming and Python, how to learn Python, Python versions 2 vs 3, data types in Python like integers, floats, strings, lists, dictionaries, functions, loops, and classes. The document contains links to online resources for learning Python and examples of basic Python code.
Programme of the Australian Beverages Council conference, ausdrinks2012. Presenters and delegates from manufacturing, government, research, industry, science, regulatory, service and allied industries will come together for two days to discuss topics leading developing and informing the industry in Australia.
The document lists different levels of education including nursery, primary, secondary, senior secondary, and vocational. It then lists specific subjects taught at each level from lower kindergarten and upper kindergarten up through senior secondary subjects like biology, chemistry, mathematics, and physics. The final lines introduce the presenter of the document as Kalpana Gautam.
Study Island is an online learning program that requires login information available from technology or media specialists. To access it, users type http://studyisland.com into their web browser. The tutorial then guides students through the screencasting features available on Study Island to record and share video explanations of their work.
Podcasting involves creating digital audio files and making them available for download through RSS feeds. A free podcasting site allows users to create accounts, set up basic settings like privacy levels and channel information. Users can then upload and publish audio files by adding titles, descriptions and tags. The goal is to make the audio files discoverable online for others to subscribe to and listen.
- Gateway is an annual interschool literary and cultural meet that has been held in Coimbatore, India since 2000.
- In the past 13 years, over 575,000 students from across India have participated in Gateway events.
- Gateway holds the world record for the largest students meet, with over 72,000 participants in 2012. Overall, Gateway has set 52 world records since 2000.
- Gateway 2013 is proposed to be held on October 19, 2013 at Codissia Trade Fair Complex in Coimbatore. It is expected to have over 74,000 participants competing in 21 events. Gateway 2013 aims to set 20 new world records.
Gateway is an annual interschool literary and cultural event held in Coimbatore, India that has set 52 world records since 2000 for hosting the largest student meet, with over 72,000 students participating from across India in 2012; the 2014 Gateway event aims to involve 74,000 participants across various literary and cultural competitions to set 20 new world records. Sponsorship opportunities are available for the Gateway event, ranging from Rs. 5-27 lakhs for various branding and promotional benefits.
The document discusses several students' experiences exploring different mobile technologies and learning pathways over the course of a class. It provides reflections from multiple students on how exploring technologies like iPods, mp3 players, and apps helped address their individual learning styles and enhance their learning in other classes. The students found mobile devices useful for visual, reflective, sequential, and active learning styles. Exploring different levels of learning quests provided various perspectives that increased their understanding of technologies.
The Australian Beverages Council is the peak industry body representing non-alcoholic beverage producers and manufacturers in Australia. It provides regulatory updates, technical advice, industry statistics, and networking opportunities to its members. Membership categories include bottlers/distributors and supplier members, with fees based on annual turnover. The Council aims to provide a united industry voice and leadership on issues while delivering relevant member benefits. It operates through a board of directors and various committees to represent the industry.
This document discusses the relationship between air pollution and asthma. It begins by defining asthma as a chronic respiratory disorder characterized by sensitive and inflamed airways that overreact to certain air pollutants. It then examines the effects of specific air pollutants like nitric oxide, ozone, and particulate matter on asthma pathology. Nitric oxide can have dual effects depending on its quantity, type of enzyme involved, and location of release. Ozone production is increased by nitrogen oxides and volatile organic compounds reacting with sunlight. Particulate matter from sources like burning fuels exacerbates asthma by promoting allergic inflammation and increasing reactive oxygen species, which cause further tissue damage and symptom amplification.
The document is a sponsorship and exhibition prospectus for ausdrinks 2012, a conference for the non-alcoholic beverage industry to be held August 13-14, 2012 in Melbourne, Australia. It outlines various sponsorship packages including gold, silver, and bronze levels that provide branding opportunities and access to attendees. A new "table top" exhibition style is introduced that allows sponsors to display with a trestle table and half meter of space. The prospectus provides event details, anticipated 150 attendees, and an application form for sponsors and exhibitors to sign up for the event.
Chemical equations are used to represent chemical reactions. They show the reactants on the left side of the arrow and the products on the right. Element symbols represent the elements involved and subscripts show the number of atoms. Coefficients show the number of molecules or atoms participating in the reaction. For a chemical equation to be balanced, it must have the same number of each type of atom on both sides according to the law of conservation of mass. Balancing chemical equations involves adjusting coefficients as needed until this is achieved.
1) Atoms are made up of protons, neutrons, and electrons. Protons and neutrons are in the nucleus, while electrons orbit the nucleus in shells.
2) Isotopes are atoms of the same element that have different numbers of neutrons, giving them different mass numbers but the same chemical properties.
3) Electrons fill the lowest available shell around the nucleus. The arrangement of electrons is shown in an element's electronic structure.
This document summarizes a presentation about machine learning. It begins with a definition of machine learning as giving computers the ability to learn without being explicitly programmed. It then provides examples of tasks that machine learning can perform, such as spam filtering and stock market prediction. The document notes that machine learning works to some degree but not perfectly. It introduces a company called Nuroko that is building a machine learning toolkit with certain desirable properties such as being general purpose, powerful, scalable, real-time, and pragmatic. The document explains why the company chose Clojure as its programming language and provides an overview of some key machine learning concepts and abstractions like vectors, coders, tasks, modules, and algorithms. It concludes
The document provides information about an upcoming statistics workshop, an in-class test covering probability and distributions, expectations for the test, guidance on preparing note sheets, and content on the normal distribution including its probability density function, transformations of normal random variables, and the standard normal distribution.
Writable Foreign Data Wrapper (JPUG Unconference 16-Feb-2013)Kohei KaiGai
The document summarizes the writable foreign data wrapper (FDW) feature in PostgreSQL. It explains that FDWs allow writing to external data sources like they are regular tables. It describes how FDWs work by hooking into the query planning and execution phases. It also discusses challenges for writable FDWs, like identifying rows to update, and proposes solutions like using a "rowid" pseudo-column. Finally, it outlines new APIs needed to support writable FDWs and provides an example of updating a foreign table.
The document describes using threshold-based agent models to optimize plant placement in a landscape. It proposes an agent-based algorithm where individual "plants" search the landscape for optimal locations based on their light and water requirements. A genetic algorithm approach is also mentioned. The goal is to maximize overall plant growth by finding placements where each plant meets a 70% threshold of its ideal growth conditions. Future work could include formal analysis and comparisons to determine how well the approach works at finding the optimal plant collection for a given landscape.
This document discusses techniques for visualizing high-dimensional data, including t-Distributed Stochastic Neighbor Embedding (t-SNE). t-SNE is used to visualize molecular data with thousands of features and won a Kaggle competition by mapping the data based on activity and time. The document also discusses limitations of single maps and introduces multiple maps t-SNE to better model relationships between different concepts.
The Ring programming language version 1.4.1 book - Part 3 of 31Mahmoud Samir Fayed
Ring 1.3 includes several new features and improvements, such as better RingQt and Ring Notepad, new functions, and a form designer. It also allows embedding Ring code without sharing state.
Graphs in the Database: Rdbms In The Social Networks AgeLorenzo Alberton
Despite the NoSQL movement trying to flag traditional databases as a dying breed, the RDBMS keeps evolving and adding new powerful weapons to its arsenal. In this talk we'll explore Common Table Expressions (SQL-99) and how SQL handles recursion, breaking the bi-dimensional barriers and paving the way to more complex data structures like trees and graphs, and how we can replicate features from social networks and recommendation systems. We'll also have a look at window functions (SQL:2003) and the advanced reporting features they make finally possible.
This document provides an introduction and overview to the Python programming language. It includes sections on why learn programming and Python, how to learn Python, Python versions 2 vs 3, data types in Python like integers, floats, strings, lists, dictionaries, functions, loops, and classes. The document contains links to online resources for learning Python and examples of basic Python code.
Programme of the Australian Beverages Council conference, ausdrinks2012. Presenters and delegates from manufacturing, government, research, industry, science, regulatory, service and allied industries will come together for two days to discuss topics leading developing and informing the industry in Australia.
The document lists different levels of education including nursery, primary, secondary, senior secondary, and vocational. It then lists specific subjects taught at each level from lower kindergarten and upper kindergarten up through senior secondary subjects like biology, chemistry, mathematics, and physics. The final lines introduce the presenter of the document as Kalpana Gautam.
Study Island is an online learning program that requires login information available from technology or media specialists. To access it, users type http://studyisland.com into their web browser. The tutorial then guides students through the screencasting features available on Study Island to record and share video explanations of their work.
Podcasting involves creating digital audio files and making them available for download through RSS feeds. A free podcasting site allows users to create accounts, set up basic settings like privacy levels and channel information. Users can then upload and publish audio files by adding titles, descriptions and tags. The goal is to make the audio files discoverable online for others to subscribe to and listen.
- Gateway is an annual interschool literary and cultural meet that has been held in Coimbatore, India since 2000.
- In the past 13 years, over 575,000 students from across India have participated in Gateway events.
- Gateway holds the world record for the largest students meet, with over 72,000 participants in 2012. Overall, Gateway has set 52 world records since 2000.
- Gateway 2013 is proposed to be held on October 19, 2013 at Codissia Trade Fair Complex in Coimbatore. It is expected to have over 74,000 participants competing in 21 events. Gateway 2013 aims to set 20 new world records.
Gateway is an annual interschool literary and cultural event held in Coimbatore, India that has set 52 world records since 2000 for hosting the largest student meet, with over 72,000 students participating from across India in 2012; the 2014 Gateway event aims to involve 74,000 participants across various literary and cultural competitions to set 20 new world records. Sponsorship opportunities are available for the Gateway event, ranging from Rs. 5-27 lakhs for various branding and promotional benefits.
The document discusses several students' experiences exploring different mobile technologies and learning pathways over the course of a class. It provides reflections from multiple students on how exploring technologies like iPods, mp3 players, and apps helped address their individual learning styles and enhance their learning in other classes. The students found mobile devices useful for visual, reflective, sequential, and active learning styles. Exploring different levels of learning quests provided various perspectives that increased their understanding of technologies.
The Australian Beverages Council is the peak industry body representing non-alcoholic beverage producers and manufacturers in Australia. It provides regulatory updates, technical advice, industry statistics, and networking opportunities to its members. Membership categories include bottlers/distributors and supplier members, with fees based on annual turnover. The Council aims to provide a united industry voice and leadership on issues while delivering relevant member benefits. It operates through a board of directors and various committees to represent the industry.
This document discusses the relationship between air pollution and asthma. It begins by defining asthma as a chronic respiratory disorder characterized by sensitive and inflamed airways that overreact to certain air pollutants. It then examines the effects of specific air pollutants like nitric oxide, ozone, and particulate matter on asthma pathology. Nitric oxide can have dual effects depending on its quantity, type of enzyme involved, and location of release. Ozone production is increased by nitrogen oxides and volatile organic compounds reacting with sunlight. Particulate matter from sources like burning fuels exacerbates asthma by promoting allergic inflammation and increasing reactive oxygen species, which cause further tissue damage and symptom amplification.
The document is a sponsorship and exhibition prospectus for ausdrinks 2012, a conference for the non-alcoholic beverage industry to be held August 13-14, 2012 in Melbourne, Australia. It outlines various sponsorship packages including gold, silver, and bronze levels that provide branding opportunities and access to attendees. A new "table top" exhibition style is introduced that allows sponsors to display with a trestle table and half meter of space. The prospectus provides event details, anticipated 150 attendees, and an application form for sponsors and exhibitors to sign up for the event.
Chemical equations are used to represent chemical reactions. They show the reactants on the left side of the arrow and the products on the right. Element symbols represent the elements involved and subscripts show the number of atoms. Coefficients show the number of molecules or atoms participating in the reaction. For a chemical equation to be balanced, it must have the same number of each type of atom on both sides according to the law of conservation of mass. Balancing chemical equations involves adjusting coefficients as needed until this is achieved.
1) Atoms are made up of protons, neutrons, and electrons. Protons and neutrons are in the nucleus, while electrons orbit the nucleus in shells.
2) Isotopes are atoms of the same element that have different numbers of neutrons, giving them different mass numbers but the same chemical properties.
3) Electrons fill the lowest available shell around the nucleus. The arrangement of electrons is shown in an element's electronic structure.
Euromonitor definitions health &wellnessmskimstaples
This document defines Euromonitor International's research definitions for various soft drink categories including carbonates, concentrates, fruit/vegetable juices, bottled water, sports drinks, energy drinks, ready-to-drink tea and coffee, and Asian specialty drinks. Definitions are provided for each category that describe what beverages are included in terms of ingredients and packaging. The purpose is to outline how Euromonitor conducts research and aggregates data around global soft drink trends and consumer preferences.
This document provides a step-by-step guide for deriving a hair product from an existing hair in the IMVU catalog and publishing the derived product. The steps include choosing a base hair, opening its derivation tree, deriving the product in the creator, changing the texture, saving the new product, and submitting it to the catalog for peer review and publication. The overall process allows users to customize and publish new hair textures based on existing products in IMVU.
This document outlines an interior design student's coursework and qualifications. It lists courses such as Introduction to Interior Design, Design Graphics, Art and Architecture History, Textiles, Space Planning, Rendering, CAD programs, Building Systems, Furnishings History, and Interior Design Business Practices. It also notes the student's 3.55 GPA, Dean's List recognition, resident assistant experience, and community service involvement. Contact information of phone number, email, and address is provided at the bottom.
The document discusses the giant panda. It describes the panda's distinctive black and white fur and bamboo-based diet. Pandas live in temperate and bamboo forests in the mountains of central China. They reproduce infrequently, with females giving birth to twin cubs though usually only one survives. Pandas play an important role in their ecosystem but are threatened by habitat loss and fragmentation from human activities. Conservation efforts aim to protect panda habitats and encourage sustainable development.
This document discusses stacks and queues as data structures. It begins by introducing stacks and their LIFO (last-in, first-out) operation. Common applications of stacks are then described, such as function calls, calculators, mazes, and undo functions. Static and dynamic stack implementations using arrays and linked lists are covered. The document then introduces queues and their FIFO (first-in, first-out) operation. Example applications of queues like print jobs and round robin scheduling are provided. Finally, the operations and implementations of queues are discussed at a high level.
The document discusses stacks and queues. It describes stacks as last-in first-out (LIFO) data structures that support push, pop, peek and isEmpty operations. It provides examples of implementing stacks using arrays and linked lists. It also briefly introduces queues as first-in first-out (FIFO) data structures.
This document discusses stacks and their implementation in Python. It begins with an introduction to stacks and their LIFO (last-in, first-out) principle. Key operations on a stack like PUSH and POP are explained. The document then presents an implementation of a stack in Python using a list and defines functions for common stack operations. It also discusses applications of stacks, conversion between infix and postfix notation using a stack, and evaluating postfix expressions.
A queue is a data structure that follows the first-in, first-out (FIFO) principle. Elements are added to the rear of the queue and removed from the front. A queue can be implemented using an array, with indexes to track the front and rear elements. When an element is added (enqueued), the rear index is incremented; when an element is removed (dequeued), the front index is incremented and the element at that index is returned. The queue has a limited capacity based on the size of the array.
This document contains a lab manual for data structures programming. It outlines various exercises including representing sparse matrices using arrays and linked lists, implementing stack and queue data structures using arrays and linked lists, and performing operations on singly, doubly and circular linked lists. It also covers binary tree traversals, binary search tree implementation and operations, and algorithms including heap sort, quick sort, depth first search, breadth first search and Dijkstra's algorithm.
Stacks, Queues, and Deques describes different data structures and their properties. Stacks follow LIFO order with insertion and removal at the same end. Queues follow FIFO order with insertion at one end and removal at the other. Deques allow insertion and removal at both ends. These structures can be implemented using arrays or linked lists.
This document provides an overview of stacks and queues as data structures. It discusses stacks and their LIFO (last-in, first-out) nature, as well as queues and their FIFO (first-in, first-out) nature. It covers the basic operations of each like push, pop, peek for stacks and enqueue, dequeue for queues. It provides examples of how to implement stacks and queues in code as well as examples of their uses.
Stacks, queues, and deques are common linear data structures. A stack follows LIFO order, with items added and removed from the same end. A queue follows FIFO order, with items added to one end and removed from the other. A deque allows additions and removals from both ends. These structures can be implemented using either arrays or linked lists. Array implementations require care to avoid overflow and underflow, while linked list versions have efficient addition and removal at both ends.
This document discusses stacks and queues as data structures. It begins by defining a stack as a linear collection where elements are added and removed from the top in a last-in, first-out (LIFO) manner. Common stack operations like push, pop, and peek are described. It then discusses applications of stacks like undo sequences and method calls. The document also defines queues as collections where elements are added to the rear and removed from the front in a first-in, first-out (FIFO) manner. Common queue operations and applications like waiting lists and printer access are also covered. Finally, it discusses implementations of stacks and queues using arrays and how to handle overflow and underflow cases.
The document discusses circular linked lists and stacks. It begins by explaining circular linked lists, how they differ from regular singly and doubly linked lists, and how to implement operations like insertion and deletion in a circular linked list. It then covers stacks, including common stack operations like push and pop. Stacks can be implemented using either arrays or linked lists. The document provides examples of how to represent a stack using each data structure and perform operations on it. It also discusses applications of stacks, like evaluating arithmetic expressions in postfix notation using a stack.
This presentation summarizes stacks as a data structure. It defines stacks as linear data structures that follow a last-in, first-out principle where only the top element can be accessed. Common stack operations like push, pop, peek are described. Examples of stack implementation using arrays and linked lists are provided. Key applications of stacks like function calls, expression evaluation, and memory management are highlighted. Advantages like efficiency and disadvantages like limited access are discussed.
This document discusses queues as an abstract data type and their common implementations and operations. Queues follow first-in, first-out (FIFO) ordering, with new items added to the rear and removed from the front. Queues can be implemented using either arrays or linked lists. Array implementations involve tracking the front, rear, and size of the queue, with special logic needed when the rear reaches the end. Linked list implementations use head and tail pointers to reference the front and rear of the queue. Common queue operations like enqueue and dequeue are also described.
The document discusses different data structures like arrays, linked lists, stacks, and queues, explaining what they are, common operations on them like searching and sorting, as well as examples of algorithms for implementing common operations like insertion and deletion on each data structure. Key data structures are explained along with their properties and typical applications.
The document discusses the Python implementation of a stack data structure. A stack follows the LIFO (Last-In First-Out) principle, where the most recently added item is the first to be removed. The stack is represented as a list, with methods like push(), pop(), peek(), and size() to add/remove items and check properties of the stack. The code demonstrates basic stack operations and how it can be used to manage items where the most recent is processed first.
This document discusses the introduction to data structures and algorithms. It covers course objectives including learning basic data structures like stacks and abstract data types. It defines abstract data types and lists the stack abstract data type. It provides examples of stack operations and applications. It demonstrates using a Stack class in Java and limitations/idioms when using stacks. It poses an exercise to use a stack to check if parentheses and curly brackets are balanced in a string. Finally, it discusses Eclipse concepts like the workspace, projects, and perspectives.
C++ STL (quickest way to learn, even for absolute beginners).pptxGauravPandey43518
C++ STL is a collection of containers and algorithms that provide common programming tasks. It includes data structures like vector, set, map as well as sorting and searching algorithms. Using STL containers makes code shorter, faster and more error-free compared to manually writing these routines. STL is important for learning advanced C++ concepts like graphs and algorithms.
This document discusses queues as a data structure. It defines queues as lists that only allow insertions at one end and deletions at the other end, following a First-In First-Out (FIFO) ordering. Common queue operations like add, remove, and peek are introduced. Examples of queues in computer science and real world are provided, like print job queues and lines. Implementations of queues using arrays and linked lists are briefly described.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Webinar: Designing a schema for a Data WarehouseFederico Razzoli
Are you new to data warehouses (DWH)? Do you need to check whether your data warehouse follows the best practices for a good design? In both cases, this webinar is for you.
A data warehouse is a central relational database that contains all measurements about a business or an organisation. This data comes from a variety of heterogeneous data sources, which includes databases of any type that back the applications used by the company, data files exported by some applications, or APIs provided by internal or external services.
But designing a data warehouse correctly is a hard task, which requires gathering information about the business processes that need to be analysed in the first place. These processes must be translated into so-called star schemas, which means, denormalised databases where each table represents a dimension or facts.
We will discuss these topics:
- How to gather information about a business;
- Understanding dictionaries and how to identify business entities;
- Dimensions and facts;
- Setting a table granularity;
- Types of facts;
- Types of dimensions;
- Snowflakes and how to avoid them;
- Expanding existing dimensions and facts.
Ocean lotus Threat actors project by John Sitima 2024 (1).pptxSitimaJohn
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Project Management Semester Long Project - Acuityjpupo2018
Acuity is an innovative learning app designed to transform the way you engage with knowledge. Powered by AI technology, Acuity takes complex topics and distills them into concise, interactive summaries that are easy to read & understand. Whether you're exploring the depths of quantum mechanics or seeking insight into historical events, Acuity provides the key information you need without the burden of lengthy texts.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Digital Marketing Trends in 2024 | Guide for Staying AheadWask
https://www.wask.co/ebooks/digital-marketing-trends-in-2024
Feeling lost in the digital marketing whirlwind of 2024? Technology is changing, consumer habits are evolving, and staying ahead of the curve feels like a never-ending pursuit. This e-book is your compass. Dive into actionable insights to handle the complexities of modern marketing. From hyper-personalization to the power of user-generated content, learn how to build long-term relationships with your audience and unlock the secrets to success in the ever-shifting digital landscape.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/building-and-scaling-ai-applications-with-the-nx-ai-manager-a-presentation-from-network-optix/
Robin van Emden, Senior Director of Data Science at Network Optix, presents the “Building and Scaling AI Applications with the Nx AI Manager,” tutorial at the May 2024 Embedded Vision Summit.
In this presentation, van Emden covers the basics of scaling edge AI solutions using the Nx tool kit. He emphasizes the process of developing AI models and deploying them globally. He also showcases the conversion of AI models and the creation of effective edge AI pipelines, with a focus on pre-processing, model conversion, selecting the appropriate inference engine for the target hardware and post-processing.
van Emden shows how Nx can simplify the developer’s life and facilitate a rapid transition from concept to production-ready applications.He provides valuable insights into developing scalable and efficient edge AI solutions, with a strong focus on practical implementation.
“Building and Scaling AI Applications with the Nx AI Manager,” a Presentation...
Stack
1. Data Structures and Algorithms
Objectives
In this session, you will learn to:
Identify the features of a stack
Implement stacks
Apply stacks to solve programming problems
Ver. 1.0 Session 10
2. Data Structures and Algorithms
Stacks
• Let us play the game of Rummy.
7 7
7 7
6 6
6 6
6 6
6 6
7 7
7 7
6 6
6 6
6 6
6 6
Ver. 1.0 Session 10
3. Data Structures and Algorithms
Defining a Stack
A stack is Stack ?
What is a a collection of data items that can be accessed at
only one end, called top.
Items can be inserted and deleted in a stack only at the top.
The last item inserted in a stack is the first one to be
deleted.
Therefore, a stack is called a Last-In-First-Out (LIFO) data
structure.
Ver. 1.0 Session 10
4. Data Structures and Algorithms
Identifying the Operations on Stacks
• PUSH: It two process of inserting are performed
There areis thebasic operations that a new element on the
top of a
stacks: stack.
PUSH
POP
Push an
Element 1
Empty Stack
1
Ver. 1.0 Session 10
5. Data Structures and Algorithms
Identifying the Operations on Stacks (Contd.)
• PUSH: It is the process of inserting a new element on the
top of a stack.
Push an
Push an
Element 2
Element 3
3
2
1
Ver. 1.0 Session 10
6. Data Structures and Algorithms
Identifying the Operations on Stacks (Contd.)
• POP: It is the process of deleting an element from the top of
a stack.
POP an
Element
3
3 2
2
1
Ver. 1.0 Session 10
7. Data Structures and Algorithms
Just a minute
Elements in stacks are inserted and deleted on a
___________ basis.
Answer:
LIFO
Ver. 1.0 Session 10
8. Data Structures and Algorithms
Just a minute
List down some real life examples that work on the LIFO
principle.
Answer:
Pile of books: Suppose a set of books are placed one over
the other in a pile. When you remove books from the pile, the
topmost book will be removed first. Similarly, when you have
to add a book to the pile, the book will be placed at the top of
the pile.
Pile of plates: The first plate begins the pile. The second plate
is placed on the top of the first plate and the third plate is
placed on the top of the second plate, and so on. In general, if
you want to add a plate to the pile, you can keep it on the top
of the pile. Similarly, if you want to remove a plate, you can
remove the plate from the top of the pile.
Bangles in a hand: When a person wears bangles, the last
bangle worn is the first one to be removed.
Ver. 1.0 Session 10
9. Data Structures and Algorithms
Implementing Stacks
You need to develop a method to check if the parentheses
in an arithmetic expression are correctly nested.
How will you solve this problem?
You can solve this problem easily by using a stack.
Ver. 1.0 Session 10
10. Data Structures and Algorithms
Implementing Stacks (Contd.)
{(a + b) × (c + d) + (c × d)]}
Consider an example.
Suppose the expression is:
{(a + b) × (c + d) + (c × d)]}
Scan the expression from
left to right.
The first entry to be
scanned is ‘{’, which is a left
parenthesis.
Push it into the stack.
{
Ver. 1.0 Session 10
11. Data Structures and Algorithms
Implementing Stacks (Contd.)
{(a + b) × (c + d) + (c × d)]}
The next entry to be
scanned is ‘(’, which is a left
parenthesis.
Push it into the stack.
The next entry is ‘a’, which
is an operand. Therefore, it
is discarded.
The next entry is ‘+’, which
is an operator. Therefore, it
is discarded. (
{
The next entry is ‘b’, which
is an operand. Therefore, it
is discarded.
Ver. 1.0 Session 10
12. Data Structures and Algorithms
Implementing Stacks (Contd.)
{(a + b) × (c + d) + (c × d)]}
The next entry to be
scanned is ‘)’, which is a
right parenthesis
POP the topmost entry from
the stack.
Match the two brackets.
( )
Brackets Matched
(
{
Ver. 1.0 Session 10
13. Data Structures and Algorithms
Implementing Stacks (Contd.)
The next entry to be scanned
{(a + b) × (c + d) + (c × d)]}
is ‘×’, which is an operator.
Therefore, it is discarded.
The next entry to be scanned
is ‘(’, which is a left
parenthesis
Push it into the stack
The next entry to be scanned
is ‘c’, which is an operand.
Therefore it is discarded
(
The next entry to be scanned
{
is ‘+’, which is an operator.
Therefore it is discarded
The next entry to be scanned
is ‘d’, which is an operand.
Therefore it is discarded
Ver. 1.0 Session 10
14. Data Structures and Algorithms
Implementing Stacks (Contd.)
{(a + b) × (c + d) + (c × d)]}
The next entry to be
scanned is ‘)’, which is a
right parenthesis.
POP the topmost element
from the stack.
Match the two brackets.
( )
Brackets Matched
(
{
Ver. 1.0 Session 10
15. Data Structures and Algorithms
Implementing Stacks (Contd.)
The next entry to be scanned
{(a + b) × (c + d) + (c × d)]}
is ‘+’, which is an operator.
Therefore, it is discarded.
The next entry to be scanned
is ‘(’, which is a left
parenthesis.
Push it into the stack.
The next entry to be scanned
is ‘c’, which is an operand.
Therefore, it is discarded.
(
The next entry to be scanned
{
is ‘×’, which is an operator.
Therefore, it is discarded.
The next entry to be scanned
is ‘d’, which is an operand.
Therefore, it is discarded.
Ver. 1.0 Session 10
16. Data Structures and Algorithms
Implementing Stacks (Contd.)
{(a + b) × (c + d) + (c × d)]}
The next entry to be
scanned is ‘)’, which is a
right parenthesis.
POP the topmost element
from the stack.
Match the two brackets.
( )
Brackets Matched
(
{
Ver. 1.0 Session 10
17. Data Structures and Algorithms
Implementing Stacks (Contd.)
{(a + b) × (c + d) + (c × d)]}
The next entry to be
scanned is ‘]’, which is a
right parenthesis.
POP the topmost element
from the stack.
Match the two brackets.
{ ]
Brackets Do Not Match
The Expression is INVALID
{
Ver. 1.0 Session 10
18. Data Structures and Algorithms
Implementing a Stack Using an Array
A stack is similarstack list in which insertion and deletion is
To implement a to a using an array:
allowed only atarray: end.
– Declare an one
Therefore,Stack[5];a // Maximum size needs to be specified in
int similar to list, stack can be implemented using
both arrays and linked lists. // advance
– Declare a variable, top to hold the index of the topmost
element in the stacks:
int top;
– Initially, when the stack is empty, set:
top = –1
Ver. 1.0 Session 10
19. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
Let us now write an algorithm for 1. Increment top by 1.
the PUSH operation. 3. Store the value to be
pushed at index top in
Initially:
the array. Top now
top = – 1 contains the index of the
topmost element.
PUSH an element 3
0 1 2 3 4
Stack
Ver. 1.0 Session 10
20. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
top = – 1 contains the index of the
topmost element.
PUSH an element 3
0 1 2 3 4
Stack 10
Ver. 1.0 Session 10
21. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
top = 0 contains the index of the
topmost element.
PUSH an element 3
0 1 2 3 4
Stack 10
top = 0
Ver. 1.0 Session 10
22. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 3
0 1 2 3 4
Stack 3 10 Item pushed
top = 0
Ver. 1.0 Session 10
23. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
1. Increment top by 1.
3. Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 8
0 1 2 3 4
Stack 3 10
top = 0
Ver. 1.0 Session 10
24. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 8
0 1 2 3 4
Stack 3 10
top = 0 = 1
top
Ver. 1.0 Session 10
25. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 8
0 1 2 3 4
Stack 3 10 8 Item pushed
top = 1
Ver. 1.0 Session 10
26. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
1. Increment top by 1.
3. Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 5
0 1 2 3 4
Stack 3 10 8
top = 1
Ver. 1.0 Session 10
27. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 5
0 1 2 3 4
Stack 3 10 8
top = top = 2
1
Ver. 1.0 Session 10
28. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 5
0 1 2 3 4
Stack 3 10 8 5 Item pushed
top = 2
Ver. 1.0 Session 10
29. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
1. Increment top by 1.
3. Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 1
0 1 2 3 4
Stack 3 10 8 5
top = 2
Ver. 1.0 Session 10
30. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 1
0 1 2 3 4
Stack 3 10 8 5
top = 2 = 3
top
Ver. 1.0 Session 10
31. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 1
0 1 2 3 4
Stack 3 10 8 5 1 Item pushed
top = 3
Ver. 1.0 Session 10
32. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
1. Increment top by 1.
3. Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 9
0 1 2 3 4
Stack 3 10 8 5 1
top = 3
Ver. 1.0 Session 10
33. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 9
0 1 2 3 4
Stack 3 10 8 5 1
top = 3 = 4
top
Ver. 1.0 Session 10
34. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 9
0 1 2 3 4
Stack 3 10 8 5 1 9 Item pushed
top = 4
Ver. 1.0 Session 10
35. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
1. Increment top by 1.
3. Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 2
0 1 2 3 4
Stack 3 10 8 5 1 9
top = 4
Ver. 1.0 Session 10
36. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 2
0 1 2 3 4
Stack 3 10 8 5 1 9
top = 4top = 5
Ver. 1.0 Session 10
37. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
• Increment top by 1.
• Store the value to be
pushed at index top in
the array. Top now
contains the index of the
topmost element.
PUSH an element 2
0 1 2 3 4
Stack 3 10 8 5 1 9 Stack overflow
top = 5
Ver. 1.0 Session 10
38. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
The stack has been implemented
To avoid the stack overflow, you 1. Increment top–by 1.
If top = MAX 1:
a. Display “Stack
need to checksizethe stack full
in an array of for 5. 3. Store the value to be
Full”
condition before pushing an element
Therefore, you cannot store more pushed at index top in
b. Exit
the array. Top now
into theelements in the stack.
than 5 stack. 3. contains the index1of the
Increment top by
Let us modify the algorithm to check topmost element.
5. Store the value to be
for this condition. pushed at index top in
the array
0 1 2 3 4
Stack 3 10 8 5 1 9
Ver. 1.0 Session 10
39. Data Structures and Algorithms
Implementing a Stack Using an Array (Contd.)
Write an algorithm to implement the POP operation on a
stack.
Algorithm for POP operation:
1. If top = – 1:
a. Display “Stack Empty”
b. Exit
4. Retrieve the value stored at index top
5. Decrement top by 1
Ver. 1.0 Session 10
40. Data Structures and Algorithms
Just a minute
In a stack, data can be stored and removed only from one
end of the stack called the ______ of the stack.
Answer:
top
Ver. 1.0 Session 10
41. Data Structures and Algorithms
Implementing a Stack Using a Linked List
Write an algorithm to implement theas follows:
The algorithm for PUSH operation isPUSH and POP
POP operation is as follows:
operations using a Linkedtmp point to the topmost node.
Make a memory for the List.
1. Allocatevariable/pointer new node.
2. Assign valuevalue contained in the topmost node.
Retrieve the to the data field of the new node.
3. Make the next field of nextnew node point to top.
top point to the the node in sequence.
4. Make topmemory allocatednode. node marked by tmp.
Release point to the new to the
Ver. 1.0 Session 10
42. Data Structures and Algorithms
Activity: Implementing a Stack Using an Array
Problem Statement:
Write a program to implement a stack by using an array that
can store five elements.
Ver. 1.0 Session 10
43. Data Structures and Algorithms
Activity: Implementing a Stack Using a Linked List
Problem Statement:
Write a program to implement a stack by using a linked list.
Ver. 1.0 Session 10
44. Data Structures and Algorithms
Just a minute
What will be the condition for stack full in a stack
implemented as a linked list?
Answer:
When a stack is implemented as a linked list, there is no upper
bound limit on the size of the stack. Therefore, there will be no
stack full condition in this case.
Ver. 1.0 Session 10
45. Data Structures and Algorithms
Just a minute
If a stack is represented in memory by using a linked list,
then insertion and deletion of data will be done ________.
1. At the end of the list
2. At the beginning of the list
3. Anywhere in the list
4. At the beginning and at the end of the list respectively
Answer:
2. At the beginning of the list
Ver. 1.0 Session 10
46. Data Structures and Algorithms
Applications of Stacks
Some of the applications of stacks are:
Implementing function calls
Maintaining the UNDO list for an application
Checking the nesting of parentheses in an expression
Evaluating expressions
Ver. 1.0 Session 10
47. Data Structures and Algorithms
Implementing Function Calls
Implementing function calls:
Consider an example. There are three functions, F1, F2, and
F3. Function F1 invokes F2 and function F2 invokes F3, as
shown.
Ver. 1.0 Session 10
48. Data Structures and Algorithms
Implementing Function Calls (Contd.)
void F1()
Assuming these instructions at the
{
given locations in the memory.
1100 int x;
1101 x = 5;
1102 F2();
1103 print(x);
}
void F2(int x)
{
1120 x = x + 5;
1121 F3(x);
1122 print(x);
}
void F3(int x)
{
1140 x = x × 2;
1141 print x;
}
Ver. 1.0 Session 10
49. Data Structures and Algorithms
Implementing Function Calls (Contd.)
void F1()
{ The execution starts from
1100 int x; function F1
1101 x = 5;
1102 F2();
1103 print(x);
}
void F2(int x)
{
1120 x = x + 5;
1121 F3(x);
1122 print(x);
}
void F3(int x)
{
1140 x = x × 2;
1141 print x;
}
Ver. 1.0 Session 10
50. Data Structures and Algorithms
Implementing Function Calls (Contd.)
void F1()
{
1100 int x;
1101 x = 5;
1102 F2();
1103 print(x);
}
void F2(int x)
{
1120 x = x + 5;
1121 F3(x);
1122 print(x);
}
void F3(int x)
{
1140 x = x × 2;
1141 print x;
}
Ver. 1.0 Session 10
51. Data Structures and Algorithms
Implementing Function Calls (Contd.)
void F1() x=5
{
1100 int x;
1101 x = 5;
1102 F2();
1103 print(x);
}
void F2(int x)
{
1120 x = x + 5;
1121 F3(x);
1122 print(x);
}
void F3(int x)
{
1140 x = x × 2;
1141 print x;
}
Ver. 1.0 Session 10
52. Data Structures and Algorithms
Implementing Function Calls (Contd.)
void F1() x=5
{
1100 int x;
1101 x = 5;
1102 F2();
1103 print(x);
}
void F2(int x)
{
1120 x = x + 5;
1121 F3(x); 1103, x = 5
1122 print(x);
} Address and the local variable of F1
void F3(int x)
{
1140 x = x × 2;
1141 print x;
}
Ver. 1.0 Session 10
53. Data Structures and Algorithms
Implementing Function Calls (Contd.)
void F1() x = 10
5
{
1100 int x;
1101 x = 5;
1102 F2();
1103 print(x);
}
void F2(int x)
{
1120 x = x + 5;
1121 F3(x); 1103, x = 5
1122 print(x);
}
void F3(int x)
{
1140 x = x × 2;
1141 print x;
}
Ver. 1.0 Session 10
54. Data Structures and Algorithms
Implementing Function Calls (Contd.)
void F1() x = 10
{
1100 int x;
1101 x = 5;
1102 F2();
1103 print(x);
}
void F2(int x)
{
1120 1122, x = 10
x = x + 5;
1121 F3(x); 1103, x = 5
1122 print(x);
} Address and the local variable of F2
void F3(int x)
{
1140 x = x × 2;
1141 print x;
}
Ver. 1.0 Session 10
55. Data Structures and Algorithms
Implementing Function Calls (Contd.)
void F1() x = 20
10
{
1100 int x;
1101 x = 5;
1102 F2();
1103 print(x);
}
void F2(int x)
{
1120 1122, x = 10
x = x + 5;
1121 F3(x); 1103, x = 5
1122 print(x);
} Address and the local variable of F2
void F3(int x)
{
1140 x = x × 2;
1141 print x;
}
Ver. 1.0 Session 10
56. Data Structures and Algorithms
Implementing Function Calls (Contd.)
void F1() x = 20
10
{
1100 int x;
1101 x = 5;
1102 F2();
1103 print(x);
}
void F2(int x) 1122, x = 10
{
1120 1122, x = 10
x = x + 5;
1121 F3(x); 1103, x = 5
1122 print(x);
}
void F3(int x)
{
1140 x = x × 2;
1141 print x; 20
}
Ver. 1.0 Session 10
57. Data Structures and Algorithms
Implementing Function Calls (Contd.)
void F1() x=5
10
{
1100 int x;
1101 x = 5;
1102 F2();
1103 print(x);
}
void F2(int x) 1103, x = 5
{
1120 x = x + 5;
1121 F3(x); 1103, x = 5
1122 print(x);
}
void F3(int x)
{
1140 x = x × 2;
1141 print x; 20 10
}
Ver. 1.0 Session 10
58. Data Structures and Algorithms
Implementing Function Calls (Contd.)
void F1() x=5
{
1100 int x;
1101 x = 5;
1102 F2();
1103 print(x);
}
void F2(int x)
{
1120 x = x + 5;
1121 F3(x);
1122 print(x);
}
void F3(int x)
{
1140 x = x × 2;
1141 print x; 20 10 5
}
Ver. 1.0 Session 10
59. Data Structures and Algorithms
Maintaining the UNDO list for an Application
Maintaining the UNDO list for an application:
Consider that you made some changes in a Word document.
Now, you want to revert back those changes. You can revert
those changes with the help of an UNDO feature.
The UNDO feature reverts the changes in a LIFO manner.
This means that the change that was made last is the first one
to be reverted.
You can implement the UNDO list by using a stack.
Ver. 1.0 Session 10
60. Data Structures and Algorithms
Checking the Nesting of Parentheses in an Expression
Checking the nesting of parentheses in an expression:
You can do this by checking the following two conditions:
– The number of left parenthesis should be equal to the number of
right parenthesis.
– Each right parenthesis is preceded by a matching left
parenthesis.
Ver. 1.0 Session 10
61. Data Structures and Algorithms
Evaluating Expressions
Evaluating an expression by using stacks:
Stacks can be used to solve complex arithmetic expressions.
The evaluation of an expression is done in two steps:
Conversion of the infix expression into a postfix expression.
Evaluation of the postfix expression.
Ver. 1.0 Session 10
62. Data Structures and Algorithms
Activity: Implementing a Stack using a Linked List
Problem Statement:
Write a program that accepts an infix expression, and then
converts it into a postfix expression. You can assume that the
entered expression is a valid infix expression.
Ver. 1.0 Session 10
63. Data Structures and Algorithms
Summary
In this session, you learned that:
A stack is a collection of data items that can be accessed at
only one end, called top. The last item inserted in a stack is the
first one to be deleted.
A stack is called a LIFO data structure.
There are two operations that can be performed on stacks.
They are:
– PUSH
– POP
– Stacks can be implemented by using both arrays and linked
lists.
Ver. 1.0 Session 10
64. Data Structures and Algorithms
Summary (Contd.)
Stacks are used in many applications. Some of the application
domains of stacks are as follows:
Implementing function calls
Maintaining the UNDO list for an application
Checking the nesting of parentheses in an expression
Evaluating expressions
Ver. 1.0 Session 10
Editor's Notes
To start the session, you need to get a set of playing cards in the class. Follow the instructions as given below to begin the game of Rummy. 1. The game begins by dealing a fixed number of cards to all players. The remaining cards are placed face down to form a “stock” pile. 2. There is also a face-up pile called the “discard” pile. 3. Initially, the discard pile contains only one card which is obtained by picking the topmost card from the stock pile. 4. Each player can draw either the topmost card of the stock pile or the topmost card on the discard pile to make a valid sequence in his/her hand. 5. After this, the player must discard one card on top of the discard pile. 6. The next player, can then draw either the topmost card of the draw pile or the topmost card of the discard pile. 7. Therefore, if a player has to draw a card from the discard pile, he/she can draw only the topmost card of the discard pile. 8. Similarly, when a player has to discard a card, he/she must discard it on the top of the discard pile. 9. The discard pile can therefore be considered a Last-In-First-Out list. 10. The last card placed on top of the discard pile is the first one to be drawn. 11. To represent and manipulate this kind of a discard pile in a computer program, you would like to use a list that: a. Contains the details of all the cards in the discard pile. b. Implements insertion and deletion of card details in such a way that the last inserted card is the first one to be removed. This kind of a list can be implemented by using a stack. Ask students to define a stack? Ask them to refer to the game and come up with some characteristics of a stack. Then come to next slide and give them the definition of stacks.
You can give some more explanation of stacks by with the help of the following example. 1. A stack is like an empty box containing books, which is just wide enough to hold the books in one pile. 2. The books can be placed as well as removed only from the top of the box. 3. The book most recently put in the box is the first one to be taken out. 4. The book at the bottom is the first one to be put inside the box and the last one to be taken out.
In this slide you need to show the calculation to determine the sum of an arithmetic progression for bubble sort algorithm. Refer to student guide.
In this slide you need to show the calculation to determine the sum of an arithmetic progression for bubble sort algorithm. Refer to student guide.
This is one of the applications where stack is used. You need to run through the slides and then ask students to write an algorithm to check the correctness of the nested parenthesis. The algorithm will be: Scan the expression. Push the opening bracket into the stack. If a closing bracket is encountered, check if the closing bracket is same as the opening bracket. If this condition holds true, POP the corresponding opening bracket from the stack. If the condition is false, the expression is not a valid expression.
Tell students that stacks can be implemented using both arrays and Linked List. The slides to explain the implementation of stacks using an array are given.
Make this session an interactive one by asking students to write an algorithm to implement POP operation using an array. Let students first try to write the algorithm. Then you can explain the algorithm given in the student guide. In addition, also explain the exception conditions that is encountered while popping an element from the stack, using an array.
In this slide you need to show the calculation to determine the sum of an arithmetic progression for bubble sort algorithm. Refer to student guide.
Student have learnt the implementation of Linked List in chapter 2, therefore ask students to write an algorithm for the PUSH and POP operations using linked lists.
To demonstrate this activity, you do not need to write the complete code. You can use the data files provided at the following location. TIRM Datafiles for Faculty Chapter 06 Activities StackUsingArrays_CSharp.txt and TIRM Datafiles for Faculty Chapter 06 Activities StackUsingArrays_CPP.txt .
To demonstrate this activity, you do not need to write the complete code. You can use the data files provided at the following location. TIRM Datafiles for Faculty Chapter 06 Activities StackUsingLinkedList_CSharp.txt and TIRM Datafiles for Faculty Chapter 06 Activities StackUsingLinkedList_CPP.txt .
In this slide you need to show the calculation to determine the sum of an arithmetic progression for bubble sort algorithm. Refer to student guide.
In this slide you need to show the calculation to determine the sum of an arithmetic progression for bubble sort algorithm. Refer to student guide.
In this section, you need to discuss the applications of Stacks. In addition, to the given applications, you can discuss some real life applications also. For example, ask students to notice the operations in their Mobile phones. When you go to the Menu log Recent calls Missed calls. On the missed call page, you will be able to view all the missed call number. To back to the main page, you need to press the back option and it will take you page, you last visited.
In this section, you need to discuss the applications of Stacks. In addition, to the given applications, you can discuss some real life applications also. For example, ask students to notice the operations in their Mobile phones. When you go to the Menu log Recent calls Missed calls. On the missed call page, you will be able to view all the missed call number. To back to the main page, you need to press the back option and it will take you page, you last visited.
Explain this concept to students by further telling them that the changes are internally stored in the stack data structure inside the computer. The last change made is the first one to be reverted.
In this slide, ask students to relate to the example they have learnt in the beginning of the session.
In this slide, ask students to relate to the example they have learnt in the beginning of the session.
To demonstrate this activity, you do not need to write the complete code. You can use the data files provided at the following location. TIRM Datafiles for Faculty Chapter 06 Activities InfixToPostfix_CSharp.txt and TIRM Datafiles for Faculty Chapter 06 Activities InfixToPostfix_CPP.txt .