Discuss seven functions, Analysis of algorithms- Experimental Studies/Primitive operations/Asymptotic notation- Big Oh/Big-Omega/Big-Theta
(Download is recommended to make the animations work)
Algorithms Lecture 3: Analysis of Algorithms IIMohamed Loey
We will discuss the following: Maximum Pairwise Product, Fibonacci, Greatest Common Divisors, Naive algorithm is too slow. The Efficient algorithm is much better. Finding the correct algorithm requires knowing something interesting about the problem
This presentation educates you about Python - GUI Programming(Tkinter), Tkinter Programming with syntaxe example, Tkinter Widgets with Operator & Description, Standard attributes.
For more topics stay tuned with learnbay.
a. Concept and Definition✓
b. Inserting and Deleting nodes ✓
c. Linked implementation of a stack (PUSH/POP) ✓
d. Linked implementation of a queue (Insert/Remove) ✓
e. Circular List
• Stack as a circular list (PUSH/POP) ✓
• Queue as a circular list (Insert/Remove) ✓
f. Doubly Linked List (Insert/Remove) ✓
For more course related material:
https://github.com/ashim888/dataStructureAndAlgorithm/
Personal blog
www.ashimlamichhane.com.np
PPT on Analysis Of Algorithms.
The ppt includes Algorithms,notations,analysis,analysis of algorithms,theta notation, big oh notation, omega notation, notation graphs
Algorithms Lecture 3: Analysis of Algorithms IIMohamed Loey
We will discuss the following: Maximum Pairwise Product, Fibonacci, Greatest Common Divisors, Naive algorithm is too slow. The Efficient algorithm is much better. Finding the correct algorithm requires knowing something interesting about the problem
This presentation educates you about Python - GUI Programming(Tkinter), Tkinter Programming with syntaxe example, Tkinter Widgets with Operator & Description, Standard attributes.
For more topics stay tuned with learnbay.
a. Concept and Definition✓
b. Inserting and Deleting nodes ✓
c. Linked implementation of a stack (PUSH/POP) ✓
d. Linked implementation of a queue (Insert/Remove) ✓
e. Circular List
• Stack as a circular list (PUSH/POP) ✓
• Queue as a circular list (Insert/Remove) ✓
f. Doubly Linked List (Insert/Remove) ✓
For more course related material:
https://github.com/ashim888/dataStructureAndAlgorithm/
Personal blog
www.ashimlamichhane.com.np
PPT on Analysis Of Algorithms.
The ppt includes Algorithms,notations,analysis,analysis of algorithms,theta notation, big oh notation, omega notation, notation graphs
Slides talk about complete process of usability testing, extensively discusses usability components, phases of usability testing process and significance of designing with empathy
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Illustration of various types of Online marketing with examples.Slides talk about search engine marketing, display ads, affiliate marketing, lead generation marketing, native marketing, email marketing etc.
Slides gives basic understanding of e-strategy,e-commerce,e-business. Discuss unique features of e-commerce technology and different types of e-commerce with examples
Describes Map data structure, its methods and implementation using Hash tables & linked list along with their running time. Hash table components, bucket Array and hash function. Collision handing strategies: Separate chaining, Linear probing, quadratic probing, double hashing.
Ordered Maps and corresponding binary search
Slides cover understanding heap, heap properties, representation of heap, up-heap and down heap bubbling followed by Adaptable priority queues, list and heap implementation of priority queues.
Describes basic understanding of priority queues, their applications, methods, implementation with sorted/unsorted list, sorting applications with insertion sort and selection sort with their running times.
Slides cover definition of tree data structure with examples, related terminologies, accessors methods, query methods, generic methods, traversal algorithms (preorder, postorder, inorder) traversal, Binary tree, Binary tree implementation using linked list and array, Binary search
Slides give the basic introduction of linked list, doubly linked list, circular linked list and operations related to it. It has animations, Download is recommended in order to make best out of animations
(Download is recommended to make the animations work)
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
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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.
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.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
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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
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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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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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.
2. Session 4 is about
Seven Functions
Analysis of algorithms
3. 1. Constant Function
Simplest function:
f(n) = c (some fixed constant)
Value of n doesn’t matter.
Ex: adding two numbers, assigning variable,
comparing two numbers
4. 2. Logarithm Function
f (n) = logb n
for some constant b > 1
This function is defined:
x = logbn if and only if bx = n
Value b is known as the base of the logarithm.
log n = log2 n.
5. Rules for algorithms
Given real numbers a , c > 0, and b , d > 1, we have
If b = 2, we either use log n, or lg n.
6. 3. Linear function
f(n) = c n
Function arises when a single basic
operation is required for each of n
elements.
7. 4. N- log- N function
f(n) = n logn
Grows faster than the linear function.
Slower than the quadratic function.
8. 5. Quadratic function
f(n) = n2
For nested loops, where combined operations of
inner and outer loop gives n*n = n2.
9. 6. Cubic Function & Other Polynomials
f(n) = n3
Comparatively less frequent
10. 7. Exponential Function
f(n) = bn
b is a positive constant, called as the base.
n is the argument and called as the exponent.
Also called as exponent function.
14. Experimental Studies
Running time of implemented algorithm is calculated
by:
Executing it on various test inputs.
Recording the actual time spent in each
execution.
Using the System.curent Time Millis () method.
15. Experimental Studies (cont.)
Steps :
1. Write a program implementing the algorithm.
2. Run the program with inputs of varying size and
composition.
3. Use a system call to get running time measure.
4. Plot the results.
5. Perform a statistical analysis.
17. Limitations of Experimental analysis
Need limited set of test inputs.
Need same hardware and software
environments.
have to fully implement and execute an
algorithm.
18. Primitive operations
Set of primitive operations:
1. Assigning a value to a variable.
2. Calling a method.
3. Performing an arithmetic operation (for example, adding two numbers).
4. Comparing two numbers.
5. Indexing into an array.
6. Following an object reference.
7. Returning from a method.
19. Example
Algorithm arrayMax(A, n)
# operations
currentMax ← A[0] 2
for i ← 1 to n − 1 do 2n
if A[i] > currentMax then 2(n − 1)
currentMax ← A[i] 2(n − 1)
{ increment counter i } 2(n − 1)
return currentMax 1
Total 8n − 2
20. Estimating Running Time
Algorithm arrayMax executes 8n − 2 primitive
operations in the worst case.
Define:
a = Time taken by the fastest primitive operation
b = Time taken by the slowest primitive operation
Let T(n) be worst-case time of arrayMax. Then
a (8n − 2) ≤ T(n) ≤ b(8n − 2)
Hence, the running time T(n) is bounded by two
linear functions.
21. Asymptotic Notation
Uses mathematical notation for functions.
Disregards constant factors.
n refer to a chosen measure of the input “size”.
Focus attention on the primary "big-picture"
aspects in a running time function.
23. Big – Oh Notation
Given functions are f(n) and g(n)
f(n) is O(g(n)) if there are positive constants
c>0 and n0 ≥1 such that
f(n) ≤ cg(n) for n ≥ n0
24. Big – Oh Notation (cont.)
Example: 2n + 10 is O(n)
2n + 10 ≤ cn
(c − 2) n ≥ 10
n ≥ 10/(c − 2)
Pick c = 3 and n0 = 10
25. Big – Oh Notation (cont.)
Example: the function n2 is not O(n)
n2 ≤ cn
n ≤ c
The above inequality cannot be satisfied since c
must be a constant
26.
27. Big – Omega Notation
Given functions are f(n) and g(n)
f(n) is Ω(g(n)) if there are positive constants
c>0 and n0 ≥1 such that
f(n) ≥ cg(n) for n ≥ n0
28. Big – Omega Notation(cont.)
Example : the function 5n2 is Ω(n2)
5n2 ≥ c n2
5n ≥ c n
c = 5 and n0 = 1
29. Big – Theta Notation
Given functions are f(n) and g(n)
f(n) is Θ(g(n)) if f(n) is O(g(n)) and f(n) is Ω(g(n)) ,
that is, there are real constants
c’> 0 and c’’ >0 and n0 ≥1 such that
c’ g(n) ≤ f(n) ≤ c’’ g(n) for n ≥ n0
30. Big – Theta Notation(cont.)
Example : 3nlog n + 4n + 5logn is Θ(n log
n).
Justification:
3nlogn ≤ 3nlogn + 4n + 5logn ≤
(3+4+5)nlog n
for n ≥ 2