Software testing is a vital process without which no software release can occur, it makes the software usable. Software testing offers opportunities constantly to be exposed with new development methods, new platform technologies, new product innovations.
Equivalence class testing is a software testing technique that divides input values into valid and invalid categories called equivalence classes. Representative values are selected from each class as test data. This technique reduces the number of test cases needed while maintaining thorough coverage. An example divides numbers into classes of valid 2-3 digit numbers and invalid single digit numbers to test a program's valid and invalid number handling. There are different types of equivalence class testing that vary in robustness. The technique helps reduce testing time and cases but requires expertise to define classes and may not test all boundary conditions.
Control flow testing is a white box testing technique that uses the program's control flow graph to design test cases that execute different paths through the code. It involves creating a control flow graph from the source code, defining a coverage target like branches or paths, generating test cases to cover the target, and executing the test cases to analyze results. It is useful for finding bugs in program logic but does not test for missing or extra requirements.
White box testing involves testing the internal structure and code of a software program, allowing testers to see inside the "box". It is used to test for internal security holes, code paths, expected outputs, and functionality of conditional statements. It involves understanding the source code and creating test cases to execute each process individually through manual testing and testing tools. Common techniques include statement, branch, condition coverage, and path testing. White box testing can thoroughly test all code paths but is complex, expensive, time-consuming, and requires professional resources with programming expertise.
Unit testing refers to testing individual units or components of an application to ensure they are working as intended. It is typically performed by developers during coding to validate each part of the program. The goal of unit testing is to isolate units and validate their correctness independently before integration testing. Common techniques for unit testing include equivalence partitioning, boundary value analysis, and positive/negative testing.
Black box testing tests the functionality of software without knowledge of its internal structure or design. It is performed by testers and clients to test the software from an end user's perspective. There are various techniques used in black box testing including equivalence partitioning, boundary value analysis, and error guessing.
Black Box Testing Techniques by Sampath MForziatech
This document provides an overview of black box testing techniques. It begins with an agenda that outlines topics like quality assurance, testing types (functional vs non-functional), and black box testing. The document then defines black box testing as testing an application's functionality without knowing its internal structure or code. Common black box techniques are described like equivalence partitioning, boundary value analysis, decision tables, and error guessing. Examples of using these techniques for testing valid and invalid salary, date, and month fields in a talent management application are also provided.
A presenetation on basics of software testing, explaining the software development life cycle and steps invovled in it and detials about each step from the testing point of view.
Se (techniques for black box testing ppt)Mani Kanth
This document discusses techniques for black box testing software. It defines black box testing as testing software functionality without knowledge of its internal implementation or code structure. The techniques described are equivalence partitioning, boundary value analysis, state transition testing, graph-based testing, error guessing, and comparison testing. Equivalence partitioning divides inputs into classes based on similar outcomes to reduce test cases. Boundary value analysis focuses on edge cases rather than the full input range. State transition testing checks behavior changes between states with the same inputs. Graph-based testing visualizes the relationships between inputs and outputs. Error guessing leverages the tester's experience to find common mistakes. Comparison testing looks for differences between versions of the same software.
The document discusses various techniques for white box testing including static testing and structural testing. Static testing involves techniques like desk checking, code walkthroughs, and code inspections that do not require executing the code. Structural testing techniques execute the code and include unit testing, code coverage testing, and complexity testing. Code coverage criteria like statement coverage and branch coverage are discussed as ways to measure how thoroughly the code has been tested. Control flow graphs are presented as a way to represent program logic and control flow.
Unit 3 Control Flow Testing contains Concept of CFT, Generate Test Input Data, Activities of Generating Test Input Data, Control Flow Graph, Path Selection Criteria, Techniques for Path Selection statement wise, branch wise, predicate wise etc. and Generating Test Input.
Dynamic black-box testing involves testing software without knowledge of its internal code by entering various inputs and checking the outputs. Key aspects include reducing test cases using equivalence partitioning to group similar inputs and outputs, identifying boundary conditions, using different data values and software states to find bugs, and using exploratory testing without specifications by systematically exploring features. The document contrasts testing-to-pass with simpler cases versus testing-to-fail with more complex cases aimed at breaking the software. Equivalence partitioning is described as a way to methodically reduce the huge number of potential test cases into a smaller yet still effective set by grouping inputs and outputs that will reveal the same bugs.
Black Box Testing, also known as Behavioral Testing it is a method of software testing in which the internal structure/ design/ implementation of the item being tested is not known to the tester. These tests can be functional or non-functional, though usually functional. This method of test can be applied virtually to every level of software testing: unit, integration, system and acceptance. It typically comprises most if not all higher level testing, but can also embody unit testing
White box testing is a software testing technique that tests internal coding and infrastructure. It involves writing test cases that exercise the paths in the code to help identify missing logic or errors. The document discusses various white box testing techniques like statement coverage, decision coverage, loop coverage, condition coverage, and path coverage. It also discusses performing white box testing at the unit, integration, and system levels. The session will cover white box testing at the unit level using control flow analysis techniques like building control flow graphs and analyzing possible paths.
The document discusses different black box testing techniques, including equivalence partitioning, boundary value analysis, and state transition testing. Equivalence partitioning divides input domains into equivalence classes where members are expected to produce the same outputs. Boundary value analysis tests values at the boundaries of equivalence classes. State transition testing models a system as a finite state machine and aims to trigger all transitions by inputting events from each state. Together, these black box techniques structure black box testing around a system's specification without knowledge of its internal implementation.
The document discusses white box and black box testing techniques. White box testing involves designing test cases based on the internal structure of the code, such as each path through conditional statements. Black box testing focuses on validating functional requirements regardless of internal structure. Both techniques are important, with white box testing occurring earlier and black box testing later in the testing process. Exhaustive testing is impossible due to resource constraints, so test cases aim to have a high probability of finding errors.
The document discusses various black-box testing techniques. It introduces testing, verification, and validation. It then describes black-box and white-box testing. Various types of testing like unit, integration, functional, system, acceptance, regression, and beta testing are explained. Strategies for writing test cases like equivalence partitioning and boundary value analysis are provided. The document emphasizes the importance of planning testing early in the development process.
This document discusses different techniques for software testing, including static and dynamic techniques. It covers specification-based or black-box techniques like equivalence partitioning, boundary value analysis, decision tables, and state transition testing. Equivalence partitioning involves dividing inputs into equivalent partitions, while boundary value analysis focuses on testing values at the boundaries of partitions. Decision tables systematically test combinations of inputs. State transition testing models the different states a system can be in and the transitions between states.
The document discusses test case design and provides guidance on creating effective test cases. It recommends that test cases have a reasonable chance of catching errors, are not redundant, and are neither too simple nor too complex. Additionally, it emphasizes the importance of making program failures obvious. Various techniques are described for selecting the best test cases, including equivalence partitioning and boundary value analysis. Equivalence classes group test cases that are expected to have the same outcome, and boundary values at the edges of valid inputs are most likely to find failures.
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Decision CAMP 2014 - Howard Rogers - Programming with decision tables v01Decision CAMP
The talk will cover the use of decision tables in a variety of programming languages and software products and follow the development from simple Condition/Action tables to those with Initial Action and Multi-condition sections. This will include a brief history of the use of decision tables in IT from the 1970’s to present day. Table structures and rule formats used will be shown. The speaker will cover the topics of rule redundancy, rule reduction and optimisation as well as bit masking techniques for runtime evaluation, and demonstrate the importance of relevance testing. Examples of code will be used to show shortcut compact coding techniques and comparison with simple truth logic. There will be an explanation of the benefits and downsides of tools which use interpretive execution of decision table logic and those which use tokenised or fully compiled execution. Examples of program code and complex logic coding will be given and comparison made with “conventional” programming languages, which will demonstrate that Decision Tables can be used not just as visual representations of complex logical processing but also as a practical and efficient programming tool. A summary of current programming and application development tools which use decision tables will be given, and the speaker will discuss future developments and techniques that will allow decision table structured and expressed logic to be incorporated in other programming languages.
Mule functional, blackbox, unit testingveena naresh
Mule is an open source integration platform that allows users to connect applications together and exchange data. Functional testing of Mule applications is important to ensure integration flows and APIs work as expected. Tests should validate that data flows through the application correctly and the expected results are produced.
This document discusses black box testing techniques. It defines black box testing as testing that ignores internal mechanisms and focuses on inputs and outputs. Six common black box testing techniques are described: equivalence partitioning, boundary value analysis, cause-effect graphing, decision table-based testing, orthogonal array testing, and syntax-driven testing. The document provides examples of how to use these techniques to design test cases to uncover faults.
Development)
- Define test strategy and approach
- Estimate test effort and schedule
- Identify risks and contingencies
- Define test environment
- Select tools and techniques
- Estimate test completion criteria
- Produce test plan document
Test planning involves:
- Defining the overall test strategy and approach
- Estimating the test effort and schedule
- Identifying risks and contingencies
- Defining the test environment requirements
- Selecting tools and techniques
- Estimating test completion criteria
- Producing the test plan document
The key outputs of test planning are:
- Test strategy and approach
- Test effort and schedule estimates
- Risks and contingencies plan
- Test environment
This document discusses code complexity and how to measure it objectively using cyclomatic complexity. Cyclomatic complexity is a metric developed by Thomas McCabe that measures the number of linearly independent paths through a program's source code. It is calculated as the number of edges (flow control statements) minus the number of nodes (executable statements) plus 1. The document provides examples of functions with different complexities and discusses how complexity scores can help prioritize testing and refactoring efforts.
This document provides an introduction to using the Google Test framework for unit testing C++ code. It begins with an example of a simple test for a function called calc_isect. It then demonstrates how to add assertions to tests, use test fixtures to reduce duplicated setup code, and generate parameterized tests. The document also covers best practices for test organization, installing and using Google Test, and some key features like XML output and selecting subsets of tests. Overall, the document serves as a tutorial for getting started with the Google Test framework for writing and running unit tests in C++ projects.
1) The document describes various testing documents created at different levels of the project testing process. Test policy and strategy are created by quality control and management, while test plans, cases, scripts, and reports are created by QA engineers.
2) Test documents can be at the company level (policy, strategy) or project level (methodology, plans, cases, scripts, reports). The key documents include test policy, strategy, methodology, plan, cases, scripts, and reports.
3) Test execution involves various levels from initial sanity testing to comprehensive and regression testing to validate requirements and detect defects in builds received from development.
Black box testing involves testing a system without knowledge of its internal workings by examining its behaviors and outputs based on given inputs. The document discusses various black box testing techniques including equivalence partitioning, boundary value analysis, cause-effect graphing, and syntax-driven testing. It also describes how black box testing is useful for finding incorrect or missing functions, interface errors, and other types of defects.
An ATM program begins by setting the initial balance to $1000. It then displays a menu asking the user to select an option to print their balance or withdraw funds. Based on their selection, it will either print the current balance or withdraw the amount and print the updated balance.
Test cases are used to systematically test software and verify requirements. A test case contains a set of steps, expected results, and actual results. It has a name, description, prerequisites, and test data. Each test case contains multiple test steps that verify a discrete action. Best practices for writing test cases include avoiding jargon, writing steps independently, and focusing on positive scenarios. Test cases are organized into templates with required fields and naming conventions to facilitate management in testing tools.
System testing involves testing a fully integrated software application to verify it meets requirements. It is done after unit and integration testing. System testing checks interactions between components, verifies functional and non-functional requirements, and validates the architecture. Test cases cover use cases and validate all types of requirements. The system is tested as a whole in a controlled environment to check for defects before delivery.
The document discusses the database development process, including conceptual data modeling using entity-relationship diagrams, logical and physical database design, and implementation using SQL. It also covers information systems architecture and planning, involving developing an enterprise data model and process decomposition. The prototyping and system development life cycle approaches to database development are presented, as well as the roles of various people involved. Finally, it describes the three-schema database architecture separating conceptual, external and internal schemas, and the three-tiered database location architecture separating presentation, process and data tiers.
The document discusses different types of software testing:
- Development testing includes unit, component, and system testing to discover bugs during development. Unit testing involves testing individual program units in isolation.
- Release testing is done by a separate team to test a complete version before public release.
- User testing involves potential users testing the system in their own environment.
The goals of testing are to demonstrate that software meets requirements and to discover incorrect or undesirable behavior to find defects. Different testing types include validation testing to check correct functionality and defect testing to uncover bugs. Both inspections and testing are important and complementary methods in software verification.
Test planning involves prescribing the scope, approach, resources, and schedule for testing activities. It helps identify items and features to be tested as well as risk items. Test planning should occur early in the project lifecycle to note any risk factors that could jeopardize testing and include a testing schedule. The purpose is to help those outside the test group understand how and why product validation will take place.
The document outlines a software testing lifecycle practice plan that includes test planning, case design, execution, defect tracking, and reporting over 10 hours total. It provides details on each stage including objectives, key points, and sample templates. Homework involves drafting a test plan, cases, and report for testing a work log system.
This document discusses unit and integration testing. It begins by explaining the benefits of testing, such as reducing bugs and allowing safe refactoring. It then describes different types of tests like unit, integration, and database tests. The document focuses on unit testing, explaining how to write and organize unit tests using PHPUnit. It provides examples of test assertions and annotations. It also covers mocking and stubbing dependencies. Finally, it discusses challenges like testing code that relies on external components and provides strategies for database testing.
This document outlines the test approach, scope, objectives, assumptions, and methodology for testing applications. It describes unit, integration, system, regression, and user acceptance testing. The primary objective is to ensure all requirements are met and the system functions as intended. The secondary objective is to identify and address all issues before release. Test deliverables include documents like the test approach, plan, and specifications as well as test cases, bug reports, and status reports.
This document discusses black box testing techniques. Black box testing involves testing software without knowledge of its internal structure or design. Key black box techniques include equivalence partitioning, which divides input into classes; boundary value analysis, which tests boundary cases; error guessing, which uses experience to generate test cases; and cause-effect graphing, which analyzes how inputs cause outputs to derive test cases. Black box testing has advantages like independence from implementation details and testing from a user perspective.
Unit testing involves testing individual units or components of code to ensure they work as intended. It focuses on testing small, isolated units of code to check functionality and edge cases. Benefits include faster debugging, development and regression testing. Guidelines for effective unit testing include keeping tests small, automated, independent and focused on the code's public API. Tests should cover a variety of inputs including boundaries and error conditions.
This document discusses various static and dynamic testing techniques. It explains that static testing is done manually without executing code, such as reviews and inspections. Dynamic testing requires executing the code using techniques like unit testing. Black box techniques like equivalence partitioning, boundary value analysis, decision tables, and state transition testing are covered, along with an example for each. White box techniques focus on internal code structure and test coverage metrics. The document provides details on different testing techniques for testers to design effective test cases.
The document describes various software testing methods and techniques. It discusses black box and white box testing methods. Black box testing evaluates software based on requirements without knowledge of internal structure, while white box testing uses knowledge of internal structure. Key black box techniques include equivalence partitioning, boundary value analysis, cause-effect graphing and comparison testing. White box techniques covered are basis path testing, loop testing and control structure testing. The document also discusses other techniques like gray box testing, fuzz testing and model-based testing.
The document contains a quiz with multiple choice questions about software testing techniques like unit testing, black box testing, and code reviews. It asks about topics such as the number of test cases needed to cover all paths in a code sample, the steps in equivalence partitioning for black box testing, and definitions of terms like decision coverage and scaffolding. The questions are in Vietnamese and English.
The document discusses code coverage from the perspective of DO178B certification. It explains that testing of code coverage is essential for safety-critical software certification. It describes the five levels of software criticality in DO178B from Level A to E, with A being the highest. The level of testing required varies according to the software's criticality level, from no structural testing needed for Level D to modified condition/decision coverage required for Level A.
In this quality assurance training, you will learn Test Case Design and Technique. Topics covered in this session are:
• Test Case Design and Techniques
• Black-box: Three major approaches
• Steps for drawing cause-Effect Diagram:
• Behavior Testing
• Random Testing
• White Box Techniques
• Path Testing
• Statement Coverage
• Data Flow Testing
For more information, visit this link: https://www.mindsmapped.com/courses/quality-assurance/software-testing-training-beginners-and-intermediate-level/
Find out more about quality assurance training and specifically about Test Case Design and Techniques. Topics covered in this session are:
Test Case Design and Techniques
Black-box: Three major approaches
Steps for drawing cause-Effect Diagram:
Behavior Testing
Random Testing
White Box Techniques
Path Testing
Statement Coverage
Data Flow Testing
For more information, visit: https://www.mindsmapped.com/courses/quality-assurance/quality-assurance-training-learn-manual-and-automation-testing/
In this session you will learn:
Test Case Design and Techniques
Black-box: Three major approaches
Steps for drawing cause-Effect Diagram:
Behavior Testing
Random Testing
White Box Techniques
Path Testing
Statement Coverage
Data Flow Testing
For more information, click here:
https://www.mindsmapped.com/courses/quality-assurance/software-testing-tutorial/
In this quality assurance training session, you will learn Test case design. Topics covered in this course are:
• Test Case Design and Techniques
• Black-box: Three major approaches
• Steps for drawing cause-Effect Diagram:
• Behavior Testing
• Random Testing
• White Box Techniques
• Path Testing
• Statement Coverage
• Data Flow Testing
To know more, visit this link: https://www.mindsmapped.com/courses/quality-assurance/software-testing-quality-assurance-qa-training-with-hands-on-exercises/
In this session you will learn:
Test Case Design and Techniques
Black-box: Three major approaches
Steps for drawing cause-Effect Diagram:
Behavior Testing
Random Testing
White Box Techniques
Path Testing
Statement Coverage
Data Flow Testing
For more information: https://www.mindsmapped.com/courses/quality-assurance/qa-software-testing-training-for-beginners/
The document discusses various topics related to software testing and maintenance. It defines key terms like testing, debugging, bugs, errors etc. It explains different types of testing like unit testing, integration testing, black box testing and white box testing. It also discusses software development life cycle, test plan, test case, test suite, testability. Testing methodologies like black box testing and white box testing are explained. Finally, it discusses different levels of testing like unit testing, integration testing and system testing.
Testing involves executing a program to find errors and is done at various stages - unit testing focuses on individual program modules, integration testing combines units and tests their interactions, and regression testing re-executes previous tests to ensure changes haven't caused errors. Key aspects of testing include white box testing which examines internal logic and black box testing which treats the program as a "black box" and focuses on inputs/outputs.
As testers, we know that we can define many more test cases than we will ever have time to design, execute, and report. The key problem in testing is choosing a small, “smart” subset from the almost infinite number of tests available that will find a large percentage of the defects. Join Lee Copeland to discover how to design test cases using formal black-box techniques, including equivalence class testing, boundary value testing, decision tables, and state-transition diagrams. Explore examples of each of these techniques in action. Don’t just pick test cases at random. Rather, learn to selectively choose a set of test cases that maximizes your effectiveness and efficiency to find more defects in less time. Then, learn how to use the test results to evaluate the quality of both your products and your testing. Discover the test design techniques that will make your testing more productive.
The document discusses various test case design techniques, including boundary value analysis and decision table testing. Boundary value analysis focuses on testing values at the boundaries of requirements because defects often occur there. It involves testing one point on the boundary, one just below, and one just above. Decision table testing represents complex business rules in a table with conditions and expected actions. Test cases are then created based on each rule in the table.
The document discusses various software testing and evaluation techniques used to ensure software solutions meet design specifications and are free from errors. It covers topics like unit testing, integration testing, system testing, black box and white box testing, test data generation, benchmarking, and quality assurance.
The document discusses various techniques for software testing including whitebox testing, blackbox testing, unit testing, integration testing, validation testing, and system testing. It provides details on techniques like equivalence partitioning, boundary value analysis, orthogonal array testing, and graph matrices. The objective of testing is to systematically uncover errors in a minimum amount of time and effort. Testing should begin with unit testing and progress towards integration and system-level testing.
Cyclomatic complexity is a software metric used to measure the complexity of a program based on the number of linearly independent paths. It is calculated as the number of edges - nodes + 2 in the program's control flow graph. Higher cyclomatic complexity indicates a more complex program that is likely more error-prone. Testing seeks to determine the required quality standard and strategy before planning specific unit, integration, and system tests. Factors considered in test planning include prioritizing what to test based on damage severity and risk levels, determining test sources, who will perform the tests, where to conduct them, and when to terminate testing. The results are documented in a software test plan.
The document discusses different types of software testing including white box testing, black box testing, integration testing, system and acceptance testing, and regression testing. It describes various techniques for each type such as statement coverage for white box testing and requirements-based testing for black box testing. The goal of testing is to find errors, check requirements, and evaluate properties like reliability, performance, and security.
Unit testing focuses on testing individual units or components of an application, such as functions, classes, or modules, to determine if they are fit for use. Integration testing checks how software components function when combined together and interact with each other. White box testing involves testing based on the internal structure and design of the code, such as checking all paths through the code have been executed. Black box testing ignores the internal implementation and tests the functionality of the system from an outside user perspective.
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Linux Mint is the first operating system that people from Windows or Mac are drawn towards when they have to switch to Linux in their work environment. Linux Mint has been around since the year 2006 and has grown and matured into a very user-friendly OS. Do watch the PPT till the very end to see all the demonstrations.
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How to Deploy Java Web App in AWS| EdurekaEdureka!
YouTube Link:https://youtu.be/Ozc5Yu_IcaI
** Edureka AWS Architect Certification Training - https://www.edureka.co/aws-certification-training**
This Edureka PPT shows how to deploy a java web application in AWS using AWS Elastic Beanstalk. It also describes the advantages of using AWS for this purpose.
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*** Edureka Digital Marketing Course: https://www.edureka.co/post-graduate/digital-marketing-certification***
This Edureka PPT on "Top 10 Reasons to Learn Digital Marketing" will help you understand why you should take up Digital Marketing
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** RPA Training: https://www.edureka.co/robotic-process-automation-training**
This PPT on RPA in 2020 will provide a glimpse of the accomplishments and benefits provided by RPA. Also, it will list out the new changes and technologies that will collaborate with RPA in 2020.
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**DevOps Certification Courses - https://www.edureka.co/devops-certification-training **
This PPT shows how to configure Jenkins to receive email notifications. It also includes a demo that shows how to do it in 6 simple steps in the Windows machine.
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EA Algorithm in Machine Learning | EdurekaEdureka!
YouTube Link: https://youtu.be/DIADjJXrgps
** Machine Learning Certification Training: https://www.edureka.co/machine-learning-certification-training **
This Edureka PPT on 'EM Algorithm In Machine Learning' covers the EM algorithm along with the problem of latent variables in maximum likelihood and Gaussian mixture model.
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Cognitive computing aims to mimic human reasoning and behavior to solve complex problems. It works by simulating human thought processes through adaptive, interactive, iterative and contextual means. Cognitive computing supplements human decision making in sectors like customer service and healthcare, while artificial intelligence focuses more on autonomous decision making with applications in finance, security and more. A use case of cognitive AI is using it to assess skills, find relevant jobs, negotiate pay, suggest career paths and provide salary comparisons and job openings to help humans.
YouTube Link: https://youtu.be/0djPrlaxx_U
Edureka AWS Architect Certification Training - https://www.edureka.co/aws-certification-training
This Edureka PPT on AWS Cloud Practitioner will provide a complete guide to your AWS Cloud Practitioner Certification exam. It will explain the exam details, objectives, why you should get certified and also how AWS certification will help your career.
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Blue Prism Top Interview Questions | EdurekaEdureka!
YouTube Link: https://youtu.be/ykbRdUNIbyQ
** RPA Training: https://www.edureka.co/robotic-process-automation-certification-courses**
This PPT on Blue Prism Interview Questions will cover the Top 50 Blue Prism related questions asked in your interviews.
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AWS Architect Certification Training: https://www.edureka.co/aws-certification-training
This PPT will help you in understanding how AWS deals smartly with Big Data. It also shows how AWS can solve Big Data challenges with ease.
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A star algorithm | A* Algorithm in Artificial Intelligence | EdurekaEdureka!
YouTube Link: https://youtu.be/amlkE0g-YFU
** Artificial Intelligence and Deep Learning: https://www.edureka.co/ai-deep-learni... **
This Edureka PPT on 'A Star Algorithm' teaches you all about the A star Algorithm, the uses, advantages and disadvantages and much more. It also shows you how the algorithm can be implemented practically and has a comparison between the Dijkstra and itself.
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Kubernetes Installation on Ubuntu | EdurekaEdureka!
YouTube Link: https://youtu.be/UWg3ORRRF60
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This Edureka PPT will help you set up a Kubernetes cluster having 1 master and 1 node. The detailed step by step instructions is demonstrated in this PPT.
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DevOps Training: https://www.edureka.co/devops-certification-training
This Edureka DevOps Tutorial for Beginners talks about What is DevOps and how it works. You will learn about several DevOps tools (Git, Jenkins, Docker, Puppet, Ansible, Nagios) involved at different DevOps stages such as version control, continuous integration, continuous delivery, continuous deployment, continuous monitoring.
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The Challenge of Interpretability in Generative AI Models.pdfSara Kroft
Navigating the intricacies of generative AI models reveals a pressing challenge: interpretability. Our blog delves into the complexities of understanding how these advanced models make decisions, shedding light on the mechanisms behind their outputs. Explore the latest research, practical implications, and ethical considerations, as we unravel the opaque processes that drive generative AI. Join us in this insightful journey to demystify the black box of artificial intelligence.
Dive into the complexities of generative AI with our blog on interpretability. Find out why making AI models understandable is key to trust and ethical use and discover current efforts to tackle this big challenge.
Increase Quality with User Access Policies - July 2024Peter Caitens
⭐️ Increase Quality with User Access Policies ⭐️, presented by Peter Caitens and Adam Best of Salesforce. View the slides from this session to hear all about “User Access Policies” and how they can help you onboard users faster with greater quality.
Self-Healing Test Automation Framework - HealeniumKnoldus Inc.
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Welcome to Cyberbiosecurity. Because regular cybersecurity wasn't complicated...Snarky Security
How wonderful it is that in our modern age, every bit of our biological data can be digitized, stored, and potentially pilfered by cyber thieves! Isn't it just splendid to think that while scientists are busy pushing the boundaries of biotechnology, hackers could be plotting the next big bio-data heist? This delightful scenario is brought to you by the ever-expanding digital landscape of biology and biotechnology, where the integration of computer science, engineering, and data science transforms our understanding and manipulation of biological systems.
While the fusion of technology and biology offers immense benefits, it also necessitates a careful consideration of the ethical, security, and associated social implications. But let's be honest, in the grand scheme of things, what's a little risk compared to potential scientific achievements? After all, progress in biotechnology waits for no one, and we're just along for the ride in this thrilling, slightly terrifying, adventure.
So, as we continue to navigate this complex landscape, let's not forget the importance of robust data protection measures and collaborative international efforts to safeguard sensitive biological information. After all, what could possibly go wrong?
-------------------------
This document provides a comprehensive analysis of the security implications biological data use. The analysis explores various aspects of biological data security, including the vulnerabilities associated with data access, the potential for misuse by state and non-state actors, and the implications for national and transnational security. Key aspects considered include the impact of technological advancements on data security, the role of international policies in data governance, and the strategies for mitigating risks associated with unauthorized data access.
This view offers valuable insights for security professionals, policymakers, and industry leaders across various sectors, highlighting the importance of robust data protection measures and collaborative international efforts to safeguard sensitive biological information. The analysis serves as a crucial resource for understanding the complex dynamics at the intersection of biotechnology and security, providing actionable recommendations to enhance biosecurity in an digital and interconnected world.
The evolving landscape of biology and biotechnology, significantly influenced by advancements in computer science, engineering, and data science, is reshaping our understanding and manipulation of biological systems. The integration of these disciplines has led to the development of fields such as computational biology and synthetic biology, which utilize computational power and engineering principles to solve complex biological problems and innovate new biotechnological applications. This interdisciplinary approach has not only accelerated research and development but also introduced new capabilities such as gene editing and biomanufact
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Keynote : AI & Future Of Offensive SecurityPriyanka Aash
In the presentation, the focus is on the transformative impact of artificial intelligence (AI) in cybersecurity, particularly in the context of malware generation and adversarial attacks. AI promises to revolutionize the field by enabling scalable solutions to historically challenging problems such as continuous threat simulation, autonomous attack path generation, and the creation of sophisticated attack payloads. The discussions underscore how AI-powered tools like AI-based penetration testing can outpace traditional methods, enhancing security posture by efficiently identifying and mitigating vulnerabilities across complex attack surfaces. The use of AI in red teaming further amplifies these capabilities, allowing organizations to validate security controls effectively against diverse adversarial scenarios. These advancements not only streamline testing processes but also bolster defense strategies, ensuring readiness against evolving cyber threats.
"Building Future-Ready Apps with .NET 8 and Azure Serverless Ecosystem", Stan...Fwdays
.NET 8 brought a lot of improvements for developers and maturity to the Azure serverless container ecosystem. So, this talk will cover these changes and explain how you can apply them to your projects. Another reason for this talk is the re-invention of Serverless from a DevOps perspective as a Platform Engineering trend with Backstage and the recent Radius project from Microsoft. So now is the perfect time to look at developer productivity tooling and serverless apps from Microsoft's perspective.
Top 12 AI Technology Trends For 2024.pdfMarrie Morris
Technology has become an irreplaceable component of our daily lives. The role of AI in technology revolutionizes our lives for the betterment of the future. In this article, we will learn about the top 12 AI technology trends for 2024.
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Enterprises have traditionally prioritized data quantity, assuming more is better for AI performance. However, a new reality is setting in: high-quality data, not just volume, is the key. This shift exposes a critical gap – many organizations struggle to understand their existing data and lack effective curation strategies and tools. This talk dives into these data challenges and explores the methods of automating data curation.
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Keynote : Presentation on SASE TechnologyPriyanka Aash
Secure Access Service Edge (SASE) solutions are revolutionizing enterprise networks by integrating SD-WAN with comprehensive security services. Traditionally, enterprises managed multiple point solutions for network and security needs, leading to complexity and resource-intensive operations. SASE, as defined by Gartner, consolidates these functions into a unified cloud-based service, offering SD-WAN capabilities alongside advanced security features like secure web gateways, CASB, and remote browser isolation. This convergence not only simplifies management but also enhances security posture and application performance across global networks and cloud environments. Discover how adopting SASE can streamline operations and fortify your enterprise's digital transformation strategy.
Cracking AI Black Box - Strategies for Customer-centric Enterprise ExcellenceQuentin Reul
The democratization of Generative AI is ushering in a new era of innovation for enterprises. Discover how you can harness this powerful technology to deliver unparalleled customer value and securing a formidable competitive advantage in today's competitive market. In this session, you will learn how to:
- Identify high-impact customer needs with precision
- Harness the power of large language models to address specific customer needs effectively
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2. Slide 2 www.edureka.co/software-testing
Objectives
At the end of this session, you will be able to:
Understand Software Testing
Understand different types of Software Testing
Understand Black Box Testing & White Box Testing
Understand difference between Black Box and White Box Testing
Implement Black Box Testing
» Equivalence Class Testing
» Boundary Value Analysis
» Decision Table Testing
3. Slide 3 www.edureka.co/software-testingSlide 3
What is Software Testing
Software Testing is the process of validating and verifying that a software application or product works as expected
4. Slide 4 www.edureka.co/software-testingSlide 4
Classification of Software Testing
Software Testing
Black Box Testing
White Box Testing
Unit Testing
Regression Testing
Integration Testing
5. Slide 5 www.edureka.co/software-testingSlide 5
Black Box Testing
Black box testing is a software testing technique in which functionality of the software is tested without looking
at the internal code structure
Black Box Testing can entirely be done on the basis of software requirements and specifications
In Black Box testing, tester tests the software/application by applying different inputs and comparing the
output with the expected result
Black Box
Input Output
Black Box Testing is also known as Behavioral Testing
Flow and Working
6. Slide 6 www.edureka.co/software-testingSlide 6
White Box Testing
White Box Testing is software testing technique based on analysis of internal logic (design, code, etc.). It’s
important to note that expected results still come from requirements
White Box Testing is usually done by developers and difficult as developers can't easily spot flaws in their own
code
Code coverage and Path testing are well known White Box Testing techniques
White Box Testing is also known as Structural Testing
White Box
Input Output
Design and code
7. Slide 7 www.edureka.co/software-testingSlide 7
Difference b/w Black Box and White Box Testing
Black Box
• Not Required
• Software Testers
• Not Required
• Requirement Specifications
White Box
• Required
• Software Developers
• Required
• Detail Design
Knowledge of internal
structure of test application
Responsibility
Programming Knowledge
Basis for Test Cases
8. Slide 8 www.edureka.co/software-testingSlide 8
Techniques of Black Box Testing
There are various techniques used to perform Black Box Testing. Some of them are listed below
Partition 1 Partition 2 Partition 3
10 10 11
Invalid Valid Invalid
1 10
Partition 1 Partition 2 Partition 3
Equivalence class partitioning
Boundary Value Analysis(BVA)
Decision Table Testing
Condition R1 R2 R3 R4
Input 1 F F T T
Input 2 F T F T
Action ERR ERR ERR GO
Invalid Valid Invalid
9. Slide 9 www.edureka.co/software-testingSlide 9
Equivalence Class Partitioning (ECP)
Usually its not possible to perform exhaustive testing when there is large test data either due to time or
budget constraints
Equivalence Class Partitioning is a very efficient technique used to cut down the number of test data to
test the application
Example
1 12<1 >12
Invalid Valid Invalid
Rather than testing the application for all number between 1 and 12, numbers <1 and >12, we can
partition test data into 3 sets, first for valid partition (1 -12), second for invalid partition (<1) and third
invalid partition (>12)
Test
Application
May, Sept
10. Slide 10 www.edureka.co/software-testingSlide 10
Applying Equivalence Class Partitioning
According to our example the test data can be partitioned into following classes
…, -3, -2, -1, 0 1, 2, 3…….., 12 13, 14, 15……..
Invalid Partition 1 Valid Partition Invalid Partition 2
Now to test the application tester can use any one number from each partition
So we can test the application with only three numbers (any one number from each partition)
Each number of a particular class partition will generate the same result. This is why this technique is called
Equivalence Class Partitioning
11. Slide 11 www.edureka.co/software-testingSlide 11
What about Boundaries?
Equivalence Class Partitioning does not guarantee to test the application on boundary values. It
gives the same weightage to both numbers within partition and numbers on the boundary
…, -3, -2, -1, 0 1, 2, 3…….., 12 13, 14, 15……..
Invalid Partition 1 Valid Partition Invalid Partition 2
What happens if the
test fails on the
boundary values?
To ensure that a tester tests the application on boundary
values also we can use Boundary Value Analysis technique
12. Slide 12 www.edureka.co/software-testingSlide 12
Boundary Value Analysis (BVA)
Decision boundaries are places where the behavior of the system changes
Boundary Value Analysis is an important technique as it is widely recognized that values on the boundaries
cause more errors in system
Therefore a tester should always check the boundaries as if the system fails, it is likely to fail on these decision
boundaries
[0,1] [12,13]<1 >12
It is very important that tester test the application on boundary values. Equivalence Partitioning and
Boundary Value Analysis are used together at all levels of testing e.g. unit testing, integration testing
Invalid Valid Invalid
13. Slide 13 www.edureka.co/software-testingSlide 13
Applying Boundary Value Analysis (BVA)
Consider the previous example where we partition the test data into three classes
In Boundary Value Analysis a tester must also check on boundary values in addition to other test data
Lets apply Boundary value Analysis to the previous example
…, -3, -2, -1, 0 1, 2, 3…….., 12 13, 14, 15……..
Invalid Partition 1 Valid Partition Invalid Partition 2
To apply BVA, we will take the minimum and maximum (boundary) values from the valid partition (1 and 12 in
this case) together with the first or last value respectively in each of the invalid partitions adjacent to the valid
partition (0 and 13 in this case)
14. Slide 14 www.edureka.co/software-testingSlide 14
ECP and BVA Together
According to the example we would have three equivalence partitioning tests (one from each of the three partitions)
and four boundary value tests
To perform both Equivalence portioning and BVA tests a tester can use one of the below combination of test data
» [-3, 6, 20] (for equivalence partitioning tests ) and [0,1,12,13] (for boundary value tests)
» [-4, 4, 14] (for equivalence partitioning tests ) and [0,1,12,13] (for boundary value tests)
» [-1, 5, 15] (for equivalence partitioning tests ) and [0,1,12,13] (for boundary value tests)
15. Slide 15 www.edureka.co/software-testingSlide 15
Decision Table Testing
Decision Table Testing is a good way to deal with a combination
of inputs, which produce different results and are used to model
complicated logic
It helps reduce test effort in verifying each and every
combination of test data, at the same time ensuring complete
coverage
The biggest advantage of using decision tables is that they make
it possible to detect combinations of conditions that would
otherwise not have been found and therefore not tested or
developed
16. Slide 16 www.edureka.co/software-testingSlide 16
Decision Table Testing
Let’s take an example scenario for an ATM where a decision table would be of use
A customer requests a cash withdrawal
One of the business rules for the ATM is that the ATM machine pays out the amount if the customer has
sufficient funds in their account or if the customer has the credit granted. In a decision table, conditions are
usually expressed as true (T) or false (F)
Conditions R1 R2 R3
Withdrawal Amount <=
Balance
T F F
Credit granted - T F
Withdrawal granted T T F
Decision Table
Each column in the table corresponds to a
rule in the business logic that describes
the unique combination of circumstances
that will result in the actions
17. Slide 17 www.edureka.co/software-testingSlide 17
Decision Table Testing
Lets consider another example of how we can model a scenario of book borrowing from college library
Conditions R1 R2 R3 R4 R5 R6 R7 R8
User Registered ? F F F F T T T T
No Pending Fees ? F F T T F F T T
Under Borrow Limit? F T F T F T F T
Borrow Book No No No No No No No Yes
User will only be allowed to borrow a book when user is registered, user does not have any outstanding fees
and he have not exceeded the book borrowing limit
If the user is not registered, then
the other two inputs are irrelevant
18. Slide 18 www.edureka.co/software-testingSlide 18
Simplifying Decision Tables
Note that in our decision table we have 8 possible combinations but we can simplify the decision table by examining
the decision table and merging the similar combinations
Conditions R1 R2 R3 R4 R5
User Registered ? F T T T T
No Pending Fees ? - F F T T
Under Borrow Limit? - F T F T
Borrow Book No No No No Yes
If the user is having pending fees, then also he
cannot borrow books even if he has borrow limits
We have merged the first four columns
as the user is not registered
19. Slide 19 www.edureka.co/software-testingSlide 19
Simplifying Decision Tables (Contd.)
Again we can simplify the decision table as is does not matter whether user has borrow limit or not. If user has
pending fees, then the user can not borrow book
Conditions R1 R2 R3 R4
User Registered ? F T T T
No Pending Fees ? - F T T
Under Borrow Limit? - - F T
Borrow Book No No No Yes
We have merged the next two columns
as the user was having pending fees
22. Slide 22 www.edureka.co/software-testing
Course Topics
Module 6
» Test Execution
Module 7
» Defect Management
Module 8
» Reporting & Team Collaboration
Module 9
» Metrics & Measurement
Module 10
» Testing Tools & FAQs
Module 1
» Introduction to Software Testing Life Cycle
Module 2
» Test Planning
Module 3
» Test Design
Module 4
» Test Techniques
Module 5
» Levels & Types Of Testing
23. Slide 23 www.edureka.co/software-testing
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