The answer is that, yes, we don’t want the function to change the parameter, but neither do we want to use up time and memory creating and storing an entire copy of it. So, we make the original object available to the called function by using pass-by-reference. We also mark it constant so that the function will not alter it, even by mistake.
The answer is that, yes, we don’t want the function to change the parameter, but neither do we want to use up time and memory creating and storing an entire copy of it. So, we make the original object available to the called function by using pass-by-reference. We also mark it constant so that the function will not alter it, even by mistake.
BSTNode.Java Node class used for implementing the BST. .pdfinfo189835
BSTNode.Java:
/**
* Node class used for implementing the BST.
*
* DO NOT MODIFY THIS FILE!!
*
* @author CS 1332 TAs
* @version 1.0
*/
public class BSTNode> {
private T data;
private BSTNode left;
private BSTNode right;
/**
* Constructs a BSTNode with the given data.
*
* @param data the data stored in the new node
*/
BSTNode(T data) {
this.data = data;
}
/**
* Gets the data.
*
* @return the data
*/
T getData() {
return data;
}
/**
* Gets the left child.
*
* @return the left child
*/
BSTNode getLeft() {
return left;
}
/**
* Gets the right child.
*
* @return the right child
*/
BSTNode getRight() {
return right;
}
/**
* Sets the data.
*
* @param data the new data
*/
void setData(T data) {
this.data = data;
}
/**
* Sets the left child.
*
* @param left the new left child
*/
void setLeft(BSTNode left) {
this.left = left;
}
/**
* Sets the right child.
*
* @param right the new right child
*/
void setRight(BSTNode right) {
this.right = right;
}
}
BST.Java:
import java.util.NoSuchElementException;
/**
* Your implementation of a BST.
*/
public class BST> {
/*
* Do not add new instance variables or modify existing ones.
*/
private BSTNode root;
private int size;
/*
* Do not add a constructor.
*/
/**
* Adds the data to the tree.
*
* This must be done recursively.
*
* The new data should become a leaf in the tree.
*
* Traverse the tree to find the appropriate location. If the data is
* already in the tree, then nothing should be done (the duplicate
* shouldn't get added, and size should not be incremented).
*
* Should be O(log n) for best and average cases and O(n) for worst case.
*
* @param data The data to add to the tree.
* @throws java.lang.IllegalArgumentException If data is null.
*/
public void add(T data) {
// WRITE YOUR CODE HERE (DO NOT MODIFY METHOD HEADER)!
}
/**
* Removes and returns the data from the tree matching the given parameter.
*
* This must be done recursively.
*
* There are 3 cases to consider:
* 1: The node containing the data is a leaf (no children). In this case,
* simply remove it.
* 2: The node containing the data has one child. In this case, simply
* replace it with its child.
* 3: The node containing the data has 2 children. Use the SUCCESSOR to
* replace the data. You should use recursion to find and remove the
* successor (you will likely need an additional helper method to
* handle this case efficiently).
*
* Do NOT return the same data that was passed in. Return the data that
* was stored in the tree.
*
* Hint: Should you use value equality or reference equality?
*
* Must be O(log n) for best and average cases and O(n) for worst case.
*
* @param data The data to remove.
* @return The data that was removed.
* @throws java.lang.IllegalArgumentException If data is null.
* @throws java.util.NoSuchElementException If the data is not in the tree.
*/
public T remove(T data) {
// WRITE YOUR CODE HERE (DO NOT MODIFY METHOD HEADER)!
}
/**
* Returns the root of the tree.
*
* For grading purposes only. You shouldn't need to use this met.
BSTNode.Java Node class used for implementing the BST. .pdfinfo189835
BSTNode.Java:
/**
* Node class used for implementing the BST.
*
* DO NOT MODIFY THIS FILE!!
*
* @author CS 1332 TAs
* @version 1.0
*/
public class BSTNode> {
private T data;
private BSTNode left;
private BSTNode right;
/**
* Constructs a BSTNode with the given data.
*
* @param data the data stored in the new node
*/
BSTNode(T data) {
this.data = data;
}
/**
* Gets the data.
*
* @return the data
*/
T getData() {
return data;
}
/**
* Gets the left child.
*
* @return the left child
*/
BSTNode getLeft() {
return left;
}
/**
* Gets the right child.
*
* @return the right child
*/
BSTNode getRight() {
return right;
}
/**
* Sets the data.
*
* @param data the new data
*/
void setData(T data) {
this.data = data;
}
/**
* Sets the left child.
*
* @param left the new left child
*/
void setLeft(BSTNode left) {
this.left = left;
}
/**
* Sets the right child.
*
* @param right the new right child
*/
void setRight(BSTNode right) {
this.right = right;
}
}
BST.Java:
import java.util.NoSuchElementException;
/**
* Your implementation of a BST.
*/
public class BST> {
/*
* Do not add new instance variables or modify existing ones.
*/
private BSTNode root;
private int size;
/*
* Do not add a constructor.
*/
/**
* Adds the data to the tree.
*
* This must be done recursively.
*
* The new data should become a leaf in the tree.
*
* Traverse the tree to find the appropriate location. If the data is
* already in the tree, then nothing should be done (the duplicate
* shouldn't get added, and size should not be incremented).
*
* Should be O(log n) for best and average cases and O(n) for worst case.
*
* @param data The data to add to the tree.
* @throws java.lang.IllegalArgumentException If data is null.
*/
public void add(T data) {
// WRITE YOUR CODE HERE (DO NOT MODIFY METHOD HEADER)!
}
/**
* Removes and returns the data from the tree matching the given parameter.
*
* This must be done recursively.
*
* There are 3 cases to consider:
* 1: The node containing the data is a leaf (no children). In this case,
* simply remove it.
* 2: The node containing the data has one child. In this case, simply
* replace it with its child.
* 3: The node containing the data has 2 children. Use the SUCCESSOR to
* replace the data. You should use recursion to find and remove the
* successor (you will likely need an additional helper method to
* handle this case efficiently).
*
* Do NOT return the same data that was passed in. Return the data that
* was stored in the tree.
*
* Hint: Should you use value equality or reference equality?
*
* Must be O(log n) for best and average cases and O(n) for worst case.
*
* @param data The data to remove.
* @return The data that was removed.
* @throws java.lang.IllegalArgumentException If data is null.
* @throws java.util.NoSuchElementException If the data is not in the tree.
*/
public T remove(T data) {
// WRITE YOUR CODE HERE (DO NOT MODIFY METHOD HEADER)!
}
/**
* Returns the root of the tree.
*
* For grading purposes only. You shouldn't need to use this met.
AVL (Adelson-Velskii and Landis) tree. An AVL tree is identical to a BST except height of the left and right subtrees can differ by at most 1.height of an empty tree is defined to be (–1).
Union is clearly a constant time operation. Running time of find(i) is proportional to the height of the tree containing node i.If unions are done by weight (size), the depth of any element is never greater than log2n.
Web-IT Support and Consulting - bulk dBase (DBF) exports via Microsoft Excel ...Dirk Cludts
If you're working with dBase files and want them to migrate to MS SQL Server or export them into CSV files? If so, this handy white paper will be important for you.
Coding Component (50)Weve provided you with an implementation .docxmary772
Coding Component (50%)
We've provided you with an implementation of an unbalanced binary search tree. The tree implements an ordered dynamic set over a generic comparable type T. Supported operations include insertion, deletion, min, max, and testing whether a value is in the set (via the exists method). Because it's a set, duplicates are not allowed, and the insert operation will not insert a value if it is already present.
We have implemented the BST operations in a recursive style. For example, inserting a value into a tree recurses down the tree seeking the correct place to add a new leaf. Each recursive call returns the root of the subtree on which it was called, after making any modifications needed to the subtree to perform the insertion. Deletion is implemented similarly.
Your job is to add the functionality needed to keep the tree balanced using the AVL property. In particular, you will need to
· augment the tree to maintain the height of each of its subtrees, as discussed in Studio;
· compute the balance at the root of a subtree (which is the height of the root's left subtree minus that of its right subtree);
· implement the AVL rebalancing operation, along with the supporting rotation operations; and
· call the height maintenance and rebalancing operations at the appropriate times during insertion and deletion.
Code Outline
There are two main source code files you need to consider, both in the avl package:
· TreeNode.java implements a class TreeNode that represents a node of a binary search tree. It holds a value (the key of the node) along with child and parent pointers. It has a height data member that is currently not used for anything. You should not modify this file, but you need to understand its contents.
· AVLTree.java implements an ordered set as a binary search tree made out of TreeNode objects.
The AVLTree class provides an interface that includes element insertion and deletion, as well as an exists() method that tests whether a value is present in the set. It also offers min() and max() methods. These methods all work as given for (unbalanced) BSTs, using the algorithms we discussed in lecture.
To implement the AVL balancing method, you will need to fill in some missing code to maintain the height of each subtree and perform rebalancing. Look for the 'FIXME' tags in AVLTree.java to see which methods you must modify.
Height Maintenance
You'll need to set the height data member each time a new leaf is allocated in the tree. You can then maintain the height as part of insertion or deletion using the incremental updating strategy you worked out in Studio 10, Part C.
The update procedure updateHeight() takes in a node and updates its height using the heights of its two subtrees. It should run in constant time.
You'll need to call updateHeight() wherever it is needed – in insertion, deletion, and perhaps elsewhere.
Rebalancing
You must implement four methods as part of AVL rebalancing:
· getBalance() computes the balance fact.
Algorithm to convert postfix expression into an expression tree. We already have an expression to convert an infix expression to postfix. Read a symbol from the postfix expression. If symbol is an operand, put it in a one node tree and push it on a stack
1) Introduction to Trees.
2) Basic terminologies
3) Binary tree
4) Binary tree types
5) Binary tree representation
6) Binary search tree
7) Creation of a binary tree
8) Operations on binary search tree Trees
Building Scalable Producer-Consumer Pools based on Elimination-Diraction TreesGuy Korland
We present the ED-Tree, a distributed pool structure based on a combination of the elimination-tree and diffracting-tree paradigms, allowing high degrees of parallelism with reduced contention
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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.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
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We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
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Gopinath Rebala
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Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
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Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
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
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