The document discusses the C++ Standard Template Library (STL). It provides an overview of STL containers, algorithms, iterators and how to access STL components. The main STL containers include vectors, lists, stacks, queues, priority queues, sets, multisets, maps and multimaps. Common operations on containers like insertion, deletion and traversal are also covered along with examples of how to declare and use iterators to access container elements.
In this core java training session, you will learn Collections – Lists, Sets. Topics covered in this session are:
• List – ArrayList, LinkedList
• Set – HashSet, LinkedHashSet, TreeSet
For more information about this course visit on this link: https://www.mindsmapped.com/courses/software-development/learn-java-fundamentals-hands-on-training-on-core-java-concepts/
A method is a code block that contains a series of statements. A program causes the statements to be executed by calling the method and specifying any required method arguments. In C#, every executed instruction is performed in the context of a method.
In this core java training session, you will learn Collections – Lists, Sets. Topics covered in this session are:
• List – ArrayList, LinkedList
• Set – HashSet, LinkedHashSet, TreeSet
For more information about this course visit on this link: https://www.mindsmapped.com/courses/software-development/learn-java-fundamentals-hands-on-training-on-core-java-concepts/
A method is a code block that contains a series of statements. A program causes the statements to be executed by calling the method and specifying any required method arguments. In C#, every executed instruction is performed in the context of a method.
This presentation introduces some concepts about the Java Collection framework. These slides introduce the following concepts:
- Collections and iterators
- Linked list and array list
- Hash set and tree set
- Maps
- The collection framework
The presentation is took from the Java course I run in the bachelor-level informatics curriculum at the University of Padova.
Collections Framework is a unified architecture for managing collections, Main Parts of Collections Framework
1. Interfaces :- Core interfaces defining common functionality exhibited by collections
2. Implementations :- Concrete classes of the core interfaces providing data structures
3. Operations :- Methods that perform various operations on collections
This set of slides introduces the reader to a subset of the C++ Standard Library called the Standard Template Library (STL). The STL provides a collection of parameterized containers and algorithms, and it is the most successful example of an approach to programming called generic programming. In this presentation, we aim at studying the ideals and concepts of the STL by re-implementing small parts of the library. Specifically, we first show how we can discover requirements on types in order to devise generic algorithms. Then, we focus on how to make algorithms independent of containers through the pivotal abstraction of iterators. To this end, we replicate the standard algorithm for finding the minimum in a sequence (min_element), which we subsequently match with a custom forward iterator over intrusive linked lists of integers. Finally, we see how function objects can be used to customize containers and algorithms alike. This allows us to deepen our understanding of ordering relations, and, in particular, to introduce the concept of strict weak orderings.
This presentation introduces some concepts about the Java Collection framework. These slides introduce the following concepts:
- Collections and iterators
- Linked list and array list
- Hash set and tree set
- Maps
- The collection framework
The presentation is took from the Java course I run in the bachelor-level informatics curriculum at the University of Padova.
Collections Framework is a unified architecture for managing collections, Main Parts of Collections Framework
1. Interfaces :- Core interfaces defining common functionality exhibited by collections
2. Implementations :- Concrete classes of the core interfaces providing data structures
3. Operations :- Methods that perform various operations on collections
This set of slides introduces the reader to a subset of the C++ Standard Library called the Standard Template Library (STL). The STL provides a collection of parameterized containers and algorithms, and it is the most successful example of an approach to programming called generic programming. In this presentation, we aim at studying the ideals and concepts of the STL by re-implementing small parts of the library. Specifically, we first show how we can discover requirements on types in order to devise generic algorithms. Then, we focus on how to make algorithms independent of containers through the pivotal abstraction of iterators. To this end, we replicate the standard algorithm for finding the minimum in a sequence (min_element), which we subsequently match with a custom forward iterator over intrusive linked lists of integers. Finally, we see how function objects can be used to customize containers and algorithms alike. This allows us to deepen our understanding of ordering relations, and, in particular, to introduce the concept of strict weak orderings.
WHAT ARE COLLECTIONS?
Collections store arbitrary objects in a structured manner. Types of collections available within the .NET Framework are:
ARRAYS
ADVANCED COLLECTIONS -
i) Non - Generics
ii) Generics
The first lecture of the ACM Aleppo CPC training. The local contest of ICPC. This lecture will help you get started in programming contests word with the lower bound techniques. The lectures focus on the C++ programming language and the STL library to solve programming problems.
BASICS OF THE COMPUTER SYSTEM,DEFINITION, TYPES OF COMPUTER, PERSONAL COMPUTER, MAINFRAME COMPUTER, MINICOMPUTER ,SUPER COMPUTER,PARTS OF THE COMPUTER SYSTEM, INPUT AND OUTPUT DEVICES, STORAGE DEVICES
Library automation software, Types of software available, Pros and Cons of Commercial and Open source software, List of library automation software.KOHA, WINISIS, NEWGENLIB, SOUL, AUTOLIB AND LIBSYS
Sequential Circuits, Flip-Flop Definition, Flip flop types, SR Flip Flop
JK Flip Flop
T Flip Flop
D Flip Flop
Uses of flip flop
Each Type explanation, truth table and circuit diagram
Java Applet Basics, Important points, Life cycle of an applet, AWT, AWT HIERARCHY, Creating Frame by extending Frame class, Creating Frame by creating instance of Frame class, Java Exceptions, Java try and catch, Syntax, Example for try and catch,
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This presentation contains, Creating string objects.
Reading string objects from keyboard.
Displaying string objects to the screen.
Finding a substring from a string.
Modifying string objects.
Adding string objects.
Accessing characters in a string.
Obtaining the size of string.
This presentation contains the following operations
Creating string objects.
Reading string objects from keyboard.
Displaying string objects to the screen.
Finding a substring from a string.
Modifying string objects.
Adding string objects.
Accessing characters in a string.
Obtaining the size of string.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
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As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
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Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
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Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
2. STL – Standard Template Library
• Collections of useful classes for common data structures
• Ability to store objects of any type (template)
• Study of containers
• Containers form the basis for treatment of data structures
• Container – class that stores a collection of data
• STL consists of 10 container classes:
• Sequence containers
• Adapter containers
• Associative containers
3. What is the STL?
• Standard Template Library
• A collection of classes to make C++ programming more
efficient
• Algorithms, Containers, and Iterators
• Function objects,Allocators, and Adapters
Containers Containers
Function Objects
Iterators
4. STLAlgorithms
• Accept STL Iterators as arguments
• Sort(begin, end);
• 4 categories
• Non-modifying
For each, Find, Count, Equal, Search, etc.
• Mutating
Copy, Generate, Reverse, Remove, Swap, etc.
• Sorting Related
Sort, Stable sort, Binary search, Merge, etc.
• Numeric
Accumulate, Inner product, Partial sum,
Adjacent difference
5. STL Containers
• Sequence Container
• Stores data by position in linear order:
• First element, second element , etc:
• Associate Container
• Stores elements by key, such as name, social security number or
part number
• Access an element by its key which may bear no relationship to the
location of the element in the container
• Adapter Container
• Contains another container as its underlying storage structure
7. Vector Container
• Generalized array that stores a collection of elements of
the same data type
• Vector – similar to an array
• Vectors allow access to its elements by using an index in the range
from 0 to n-1 where n is the size of the vector
• Vector vs array
• Vector has operations that allow the collection to grow and contract
dynamically at the rear of the sequence``
9. Vector Container
• Allows direct access to the elements via an index operator
• Indices for the vector elements are in the range from 0 to
size() -1
• Example:
#include <vector>
vector <int> v(20);
v[5]=15;
10. List Container
• Stores elements by position
• Each item in the list has both a value and a memory
address (pointer) that identifies the next item in the
sequence
• To access a specific data value in the list, one must start
at the first position (front) and follow the pointers from
element to element until data item is located.
• List is not a direct access structure
• Advantage: ability to add and remove items efficiently at
any position in the sequence
11. Stack Container
• Adapter Container
• These containers restrict how elements enter and leave a
sequence
• Stack
• allows access at only one end of the sequence (top)
• Adds objects to container by pushing the object onto the stack
• Removes objects from container by popping the stack
• LIFO ordering (last end, first out)
12. Queue Container
• Queue
• Allows access only at the front and rear of the sequence
• Items enter at the rear and exit from the front
• Example: waiting line at a grocery store
• FIFO ordering (first-in first-out )
• push(add object to a queue)
• pop (remove object from queue)
13. Priority Queue Container
• Priority queue
• Operations are similar to those of a stack or queue
• Elements can enter the priority queue in any order
• Once in the container, a delete operation removes the largest (or
smallest) value
• Example: a filtering system that takes in elements and then
releases them in priority order 8
18 13
3 15
27
14. Set Container
• Set
• Collection of unique values, called keys or set members
• Contains operations that allow a programmer to:
• determine whether an item is a member of the set
• insert and delete items very efficiently
5 1 3
6 27 15
Buick
Ford
Jeep BMW
Set A Set B
15. Multi-Set Container
• A multi-set is similar to a set, but the same value can be in
the set more than once
• Multi-set container allows duplicates
16. Map Container
• Implements a key-value relationship
• Programmer can use a key to access corresponding
values
• Example: key could be a part number such as A24-57
that corresponds to a part: 8.75 price and Martin
manufacturer
A22-56
A23-57
A24-57
A24-57 8.75 Martin
A22-56 12.50 Callowa
y
A23-57 4.95 Mirage
18. How to access Components - Iterator
• Iterator is an object that can access a collection of like
objects one object at a time.
• An iterator can traverse the collection of objects.
• Each container class in STL has a corresponding iterator
that functions appropriately for the container
• For example: an iterator in a vector class allows random
access
• An iterator in a list class would not allow random access
(list requires sequential access)
19. Common Iterator Operations
* Return the item that the iterator currently references
++ Move the iterator to the next item in the list
-- Move the iterator to the previous item in the
list
== Compare two iterators for equality
!= Compare two iterators for inequality
20. STL List Class
Constructors and assignment
• list <T> v;
• list<T> v(aList);
• l=aList;
Access
• l.front() ----returns 1st element in the list
• l.back()----returns the last element in the list
21. STL List
Insert and Remove
• l.push_front(value)
• l.push_back(value)
Iterator Delaration
• list<T>::iteratoritr;
Iterator Options
• itr = l.begin() set iterator to beginning of the list
• Itr = l.end() set iterator to after the end of the list
22. Writing classes that work with the STL
Classes that will be stored in STL containers should
explicitly define the following:
◦ Default constructor
◦ Copy constructor
◦ Destructor
◦ operator =
◦ operator==
◦ operator<
Not all of these are always necessary, but it might be
easier to define them than to figure out which ones
you actually need
Many STL programming errors can be traced to
omitting or improperly defining these methods