The document discusses various types and levels of software testing, including unit testing, integration testing, system testing, and acceptance testing. It describes strategies for black-box testing and white-box testing at the unit level. Black-box testing focuses on input-output behavior while white-box testing aims for thorough coverage of all statements, paths, and branches in the code. Both types of testing are needed as they uncover different types of errors. The document also provides examples of constructing test cases and test oracles for a sample code module. Overall, testing is an important part of the software development process but can never guarantee that a system is bug-free.
1. The document discusses different strategies for integration and system testing, including big bang, bottom-up, top-down, and sandwich testing.
2. It explains the key steps in integration testing such as selecting components, developing drivers/stubs, defining test cases, and executing tests.
3. The goals of system testing are outlined as functional testing, structure testing, performance testing, and acceptance testing.
SE2018_Lec 20_ Test-Driven Development (TDD)Amr E. Mohamed
The document discusses test-driven development (TDD) and unit testing. It explains that TDD follows a cycle of writing an initial failing test case, producing just enough code to pass that test, and refactoring the code. Unit testing involves writing test cases for individual classes or functions, using assertions to validate expected outcomes. The JUnit framework is introduced for writing and running unit tests in Java.
The document discusses various software testing strategies and concepts. It covers the goals of testing as verification (building the software right) and validation (building the right software). It also discusses different types of testing such as black box testing (based on inputs and outputs) and white box testing (based on code). Other topics covered include levels of testing (unit, integration, system), test measures, and a software testing plan.
The document discusses various software testing strategies and techniques:
1. Testing is the process of finding errors in a program before delivering it to end users. It shows errors, tests requirements conformance, and is an indication of quality.
2. Testing begins with unit testing individual components, then progresses to integration testing of components working together, validation testing against requirements, and system testing in the full system context.
3. White-box testing aims to ensure all statements and conditions are executed at least once, while black-box testing treats the software as a "black box" without viewing internal logic or code.
Test-driven development (TDD) is a software development process where test cases are written before code is produced. The process involves writing a failing test case, producing the minimum amount of code to pass the test, and refactoring the new code. TDD encourages writing automated tests that can be repeatedly executed after small code changes to ensure all tests continue to pass.
Chapter 10 Testing and Quality Assurance1Unders.docxketurahhazelhurst
Chapter 10:
Testing and Quality
Assurance
1
Understand quality & basic techniques for software verification and validation.
Analyze basics of software testing and testing techniques.
Discuss the concept of “inspection” process.
Objectives
2
Quality assurance (QA): activities designed
to measure and improve quality in a product— and process.
Quality control (QC): activities designed to validate and verify the quality of the product through detecting faults and “fixing” the defects.
Need good techniques, process, tools,
and team.
Testing Introduction
similar
3
Two traditional definitions:
Conforms to requirements.
Fit to use.
Verification: checking software conforms to
its requirements (did the software evolve
from the requirements properly; does the software “work”?)
Is the system correct?
Validation: checking software meets user requirements (fit to use)
Are we building the correct system?
What Is “Quality”?
4
Testing: executing program in a controlled environment and “verifying/validating” output.
Inspections and reviews.
Formal methods (proving software correct).
Static analysis detects “error-prone conditions.”
Some “Error-Detection” Techniques (finding errors)
5
Error: a mistake made by a programmer or software engineer that caused the fault, which in turn may cause a failure
Fault (defect, bug): condition that may cause a failure in the system
Failure (problem): inability of system to perform a function according to its spec due to some fault
Fault or failure/problem severity (based on consequences)
Fault or failure/problem priority (based on importance of developing a fix, which is in turn based
on severity)
Faults and Failures
6
Activity performed for:
Evaluating product quality
Improving products by identifying defects and having them fixed prior to software release
Dynamic (running-program) verification of program’s behavior on a finite set of test cases selected from execution domain.
Testing can NOT prove product works 100%—even though we use testing to demonstrate that parts of the software works.
Testing
Not always
done!
7
Who tests?
Programmers
Testers/Req. Analyst
Users
What is tested?
Unit code testing
Functional code testing
Integration/system testing
User interface testing
Testing (cont.)
Why test?
Acceptance (customer)
Conformance (std, laws, etc.)
Configuration (user vs. dev.)
Performance, stress, security, etc.
How (test cases designed)?
Intuition
Specification based (black box)
Code based (white box)
Existing cases (regression)
8
Progression of Testing
Equivalence Class Partitioning
Divide the input into several groups, deemed “equivalent” for purposes of finding errors.
Pick one “representative” for each class used for testing.
Equivalence classes determined by req./design specifications and some intuition
Example: pick “larger” of
two integers and . . .
Lessen duplication.
Complete coverage.
10
Suppose we have n distinct functional requirements.
Su ...
Ever tried doing Test First Test Driven Development? Ever failed? TDD is not easy to get right. Here's some practical advice on doing BDD and TDD correctly. This presentation attempts to explain to you why, what, and how you should test, tell you about the FIRST principles of tests, the connections of unit testing and the SOLID principles, writing testable code, test doubles, the AAA of unit testing, and some practical ideas about structuring tests.
The document discusses various aspects of unit testing including definitions, benefits, naming standards, and best practices. It provides definitions for terms like error, defect, failure. It outlines the benefits of unit testing like finding bugs early, enabling code refactoring. It discusses what should be tested like boundaries, error conditions. It also provides examples of good test names and guidelines for structuring and naming unit tests.
1. The document discusses different strategies for integration and system testing, including big bang, bottom-up, top-down, and sandwich testing.
2. It explains the key steps in integration testing such as selecting components, developing drivers/stubs, defining test cases, and executing tests.
3. The goals of system testing are outlined as functional testing, structure testing, performance testing, and acceptance testing.
SE2018_Lec 20_ Test-Driven Development (TDD)Amr E. Mohamed
The document discusses test-driven development (TDD) and unit testing. It explains that TDD follows a cycle of writing an initial failing test case, producing just enough code to pass that test, and refactoring the code. Unit testing involves writing test cases for individual classes or functions, using assertions to validate expected outcomes. The JUnit framework is introduced for writing and running unit tests in Java.
The document discusses various software testing strategies and concepts. It covers the goals of testing as verification (building the software right) and validation (building the right software). It also discusses different types of testing such as black box testing (based on inputs and outputs) and white box testing (based on code). Other topics covered include levels of testing (unit, integration, system), test measures, and a software testing plan.
The document discusses various software testing strategies and techniques:
1. Testing is the process of finding errors in a program before delivering it to end users. It shows errors, tests requirements conformance, and is an indication of quality.
2. Testing begins with unit testing individual components, then progresses to integration testing of components working together, validation testing against requirements, and system testing in the full system context.
3. White-box testing aims to ensure all statements and conditions are executed at least once, while black-box testing treats the software as a "black box" without viewing internal logic or code.
Test-driven development (TDD) is a software development process where test cases are written before code is produced. The process involves writing a failing test case, producing the minimum amount of code to pass the test, and refactoring the new code. TDD encourages writing automated tests that can be repeatedly executed after small code changes to ensure all tests continue to pass.
Chapter 10 Testing and Quality Assurance1Unders.docxketurahhazelhurst
Chapter 10:
Testing and Quality
Assurance
1
Understand quality & basic techniques for software verification and validation.
Analyze basics of software testing and testing techniques.
Discuss the concept of “inspection” process.
Objectives
2
Quality assurance (QA): activities designed
to measure and improve quality in a product— and process.
Quality control (QC): activities designed to validate and verify the quality of the product through detecting faults and “fixing” the defects.
Need good techniques, process, tools,
and team.
Testing Introduction
similar
3
Two traditional definitions:
Conforms to requirements.
Fit to use.
Verification: checking software conforms to
its requirements (did the software evolve
from the requirements properly; does the software “work”?)
Is the system correct?
Validation: checking software meets user requirements (fit to use)
Are we building the correct system?
What Is “Quality”?
4
Testing: executing program in a controlled environment and “verifying/validating” output.
Inspections and reviews.
Formal methods (proving software correct).
Static analysis detects “error-prone conditions.”
Some “Error-Detection” Techniques (finding errors)
5
Error: a mistake made by a programmer or software engineer that caused the fault, which in turn may cause a failure
Fault (defect, bug): condition that may cause a failure in the system
Failure (problem): inability of system to perform a function according to its spec due to some fault
Fault or failure/problem severity (based on consequences)
Fault or failure/problem priority (based on importance of developing a fix, which is in turn based
on severity)
Faults and Failures
6
Activity performed for:
Evaluating product quality
Improving products by identifying defects and having them fixed prior to software release
Dynamic (running-program) verification of program’s behavior on a finite set of test cases selected from execution domain.
Testing can NOT prove product works 100%—even though we use testing to demonstrate that parts of the software works.
Testing
Not always
done!
7
Who tests?
Programmers
Testers/Req. Analyst
Users
What is tested?
Unit code testing
Functional code testing
Integration/system testing
User interface testing
Testing (cont.)
Why test?
Acceptance (customer)
Conformance (std, laws, etc.)
Configuration (user vs. dev.)
Performance, stress, security, etc.
How (test cases designed)?
Intuition
Specification based (black box)
Code based (white box)
Existing cases (regression)
8
Progression of Testing
Equivalence Class Partitioning
Divide the input into several groups, deemed “equivalent” for purposes of finding errors.
Pick one “representative” for each class used for testing.
Equivalence classes determined by req./design specifications and some intuition
Example: pick “larger” of
two integers and . . .
Lessen duplication.
Complete coverage.
10
Suppose we have n distinct functional requirements.
Su ...
Ever tried doing Test First Test Driven Development? Ever failed? TDD is not easy to get right. Here's some practical advice on doing BDD and TDD correctly. This presentation attempts to explain to you why, what, and how you should test, tell you about the FIRST principles of tests, the connections of unit testing and the SOLID principles, writing testable code, test doubles, the AAA of unit testing, and some practical ideas about structuring tests.
The document discusses various aspects of unit testing including definitions, benefits, naming standards, and best practices. It provides definitions for terms like error, defect, failure. It outlines the benefits of unit testing like finding bugs early, enabling code refactoring. It discusses what should be tested like boundaries, error conditions. It also provides examples of good test names and guidelines for structuring and naming unit tests.
The document discusses unit testing and provides guidance on effective unit testing practices. It defines key terms like error, defect, and failure. It outlines the benefits of unit testing like finding defects earlier and maintaining stable code. It discusses naming conventions and frameworks for unit tests. It provides examples of different types of unit tests and guidelines for writing good unit tests that are independent, fast, and test all functionality. The document emphasizes testing boundary conditions and errors as well as documenting test cases.
The document discusses various aspects of unit testing including definitions, benefits, naming standards, and best practices. It provides definitions for terms like error, defect, failure. It outlines the benefits of unit testing like finding bugs early, enabling code refactoring. It discusses what should be tested like boundaries, error conditions. It also provides examples of good test names and guidelines for structuring and naming unit tests.
The document discusses software testing, including definitions of key terms like failure, error, and fault. It covers different types of testing like unit testing, integration testing, and acceptance testing. It also discusses techniques for fault avoidance, detection, and tolerance. Black-box and white-box testing approaches are explained. Finally, it provides an overview of the JUnit testing framework in Java.
This document discusses various types of software testing techniques used in the software development lifecycle (SDLC). It begins by describing different SDLC models like waterfall, prototyping, RAD, spiral and V-models. It then discusses the importance of testing at different stages of SDLC and different types of testing like static vs dynamic, black box vs white box, unit vs integration etc. The rest of the document elaborates on specific black box and white box testing techniques like equivalence partitioning, boundary value analysis, cause-effect graphing, statement coverage and basis path testing.
The document discusses software testing objectives, principles, techniques and processes. It covers black-box and white-box testing, unit and integration testing, and challenges of object-oriented testing. Testing aims to find bugs but can never prove their absence. Exhaustive testing is impossible so testing must be planned and systematic. Frameworks like xUnit can help automate unit 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.
The document discusses integration and system testing. It describes various integration testing strategies like big bang, bottom-up, top-down, and sandwich. It also discusses continuous integration testing. For system testing, it covers functional testing to validate requirements, performance testing for non-functional tests, and acceptance testing conducted by clients. The goal of integration testing is to test interfaces between subsystems and their interactions.
Black box testing is a software testing technique where the internal structure and implementation of the system is not known. It focuses on validating the functionality of the system based on requirements and specifications. Some key techniques of black box testing include equivalence partitioning, boundary value analysis, and error guessing. Equivalence partitioning divides test cases into equivalence classes based on expected behavior. Boundary value analysis tests values at the boundaries of equivalence classes. Error guessing involves creating test cases based on intuition about potential errors. Black box testing is applied at various levels including unit, integration, system, and non-functional testing.
The document discusses effective unit testing. It covers topics like the value of writing tests, test-driven development, behavior-driven development, test doubles, structuring tests with arrange-act-assert/given-when-then, checking behavior not implementation, test smells, JUnit basics, and parameterized testing. The goal of tests is to validate code behavior, catch mistakes, and shape design. Writing tests also helps learn what the code is intended to do.
The document discusses various software testing techniques. It covers the objectives of testing as finding errors and having a high probability of discovering undiscovered errors. It describes different types of testing like white-box testing, which tests internal logic and paths, and black-box testing, which tests external functionality. Specific techniques covered include basis path testing, equivalence partitioning, boundary value analysis, and graph-based testing methods. The importance of testability, traceability, simplicity, and understandability are emphasized.
This workshop is about testing the right way. Get a clear view on how to test your code in an efficient and useful way!
This first testing-related workshop is about all aspects of unit testing. Integration testing and TDD will have their own dedicated workshops.
Model driven testing (MDT) provides several advantages over traditional code-based testing approaches. MDT allows testing to be integrated into the design process, enabling frequent and early testing. Test architectures and test cases can be automatically generated from models, using techniques like animated sequence diagrams to simulate scenarios and effectively record test cases. This helps improve requirements and code coverage at lower cost and in less time compared to traditional testing approaches.
The document discusses different types of integration and system testing for software. It describes integration testing strategies like big bang, bottom-up, top-down, and sandwich testing. Integration testing aims to test interfaces between subsystems. System testing includes functional testing to validate requirements, performance testing to evaluate non-functional properties, and acceptance testing for client approval. Stubs and drivers are used to isolate components during integration and system testing.
The document discusses various software testing techniques including black-box testing which focuses on inputs and outputs without seeing internal code, and white-box testing which considers internal logic and structures. Different levels of testing are covered from unit to acceptance testing. Strategies for effective test case design such as equivalence partitioning and boundary value analysis are also presented.
The document discusses unit testing and provides guidance on how to effectively implement unit testing. It defines unit testing as testing individual units or components of software code to verify they are functioning as intended. The document outlines best practices for unit testing such as writing test cases that cover valid, invalid, and boundary conditions. It also recommends testing frameworks like JUnit that can automate running test cases. Overall, the document advocates for developing a rigorous unit testing strategy and practicing habits like writing tests first and continuously running tests to improve code quality.
The document provides an overview of software testing. It discusses the importance of having a systematic testing plan and achieving high test coverage. The key topics covered include unit testing, integration testing, security testing, designing tests for high coverage using techniques like equivalence partitioning and boundary value analysis, and measuring test coverage at the code level using approaches such as control flow testing and state-based testing. Examples are provided to illustrate acceptance testing and defining states for state-based testing. The overall goal of software testing discussed is to find faults as efficiently as possible by prioritizing some test cases that are more likely to uncover errors.
The document discusses Google Test, an open source unit testing framework for C++ that can also be used for testing C code, providing an overview of its features and how to implement unit tests using common patterns like test fixtures, assertions, and death tests to validate expected failures. It also covers best practices for writing effective unit tests, including keeping tests independent, focused, and fast-running.
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.
This document discusses various software testing methodologies. It begins by defining software testing and its objectives. It then covers topics like verification and validation, unit testing, integration testing strategies, validation testing, system testing types, and software testing strategies. The remainder of the document focuses on different types of testing like white-box testing, black-box testing, and grey-box testing along with techniques like structural testing, code coverage, equivalence partitioning, and boundary value analysis.
Transform Your Communication with Cloud-Based IVR SolutionsTheSMSPoint
Discover the power of Cloud-Based IVR Solutions to streamline communication processes. Embrace scalability and cost-efficiency while enhancing customer experiences with features like automated call routing and voice recognition. Accessible from anywhere, these solutions integrate seamlessly with existing systems, providing real-time analytics for continuous improvement. Revolutionize your communication strategy today with Cloud-Based IVR Solutions. Learn more at: https://thesmspoint.com/channel/cloud-telephony
Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdfVALiNTRY360
Salesforce Healthcare CRM, implemented by VALiNTRY360, revolutionizes patient management by enhancing patient engagement, streamlining administrative processes, and improving care coordination. Its advanced analytics, robust security, and seamless integration with telehealth services ensure that healthcare providers can deliver personalized, efficient, and secure patient care. By automating routine tasks and providing actionable insights, Salesforce Healthcare CRM enables healthcare providers to focus on delivering high-quality care, leading to better patient outcomes and higher satisfaction. VALiNTRY360's expertise ensures a tailored solution that meets the unique needs of any healthcare practice, from small clinics to large hospital systems.
For more info visit us https://valintry360.com/solutions/health-life-sciences
The document discusses unit testing and provides guidance on effective unit testing practices. It defines key terms like error, defect, and failure. It outlines the benefits of unit testing like finding defects earlier and maintaining stable code. It discusses naming conventions and frameworks for unit tests. It provides examples of different types of unit tests and guidelines for writing good unit tests that are independent, fast, and test all functionality. The document emphasizes testing boundary conditions and errors as well as documenting test cases.
The document discusses various aspects of unit testing including definitions, benefits, naming standards, and best practices. It provides definitions for terms like error, defect, failure. It outlines the benefits of unit testing like finding bugs early, enabling code refactoring. It discusses what should be tested like boundaries, error conditions. It also provides examples of good test names and guidelines for structuring and naming unit tests.
The document discusses software testing, including definitions of key terms like failure, error, and fault. It covers different types of testing like unit testing, integration testing, and acceptance testing. It also discusses techniques for fault avoidance, detection, and tolerance. Black-box and white-box testing approaches are explained. Finally, it provides an overview of the JUnit testing framework in Java.
This document discusses various types of software testing techniques used in the software development lifecycle (SDLC). It begins by describing different SDLC models like waterfall, prototyping, RAD, spiral and V-models. It then discusses the importance of testing at different stages of SDLC and different types of testing like static vs dynamic, black box vs white box, unit vs integration etc. The rest of the document elaborates on specific black box and white box testing techniques like equivalence partitioning, boundary value analysis, cause-effect graphing, statement coverage and basis path testing.
The document discusses software testing objectives, principles, techniques and processes. It covers black-box and white-box testing, unit and integration testing, and challenges of object-oriented testing. Testing aims to find bugs but can never prove their absence. Exhaustive testing is impossible so testing must be planned and systematic. Frameworks like xUnit can help automate unit 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.
The document discusses integration and system testing. It describes various integration testing strategies like big bang, bottom-up, top-down, and sandwich. It also discusses continuous integration testing. For system testing, it covers functional testing to validate requirements, performance testing for non-functional tests, and acceptance testing conducted by clients. The goal of integration testing is to test interfaces between subsystems and their interactions.
Black box testing is a software testing technique where the internal structure and implementation of the system is not known. It focuses on validating the functionality of the system based on requirements and specifications. Some key techniques of black box testing include equivalence partitioning, boundary value analysis, and error guessing. Equivalence partitioning divides test cases into equivalence classes based on expected behavior. Boundary value analysis tests values at the boundaries of equivalence classes. Error guessing involves creating test cases based on intuition about potential errors. Black box testing is applied at various levels including unit, integration, system, and non-functional testing.
The document discusses effective unit testing. It covers topics like the value of writing tests, test-driven development, behavior-driven development, test doubles, structuring tests with arrange-act-assert/given-when-then, checking behavior not implementation, test smells, JUnit basics, and parameterized testing. The goal of tests is to validate code behavior, catch mistakes, and shape design. Writing tests also helps learn what the code is intended to do.
The document discusses various software testing techniques. It covers the objectives of testing as finding errors and having a high probability of discovering undiscovered errors. It describes different types of testing like white-box testing, which tests internal logic and paths, and black-box testing, which tests external functionality. Specific techniques covered include basis path testing, equivalence partitioning, boundary value analysis, and graph-based testing methods. The importance of testability, traceability, simplicity, and understandability are emphasized.
This workshop is about testing the right way. Get a clear view on how to test your code in an efficient and useful way!
This first testing-related workshop is about all aspects of unit testing. Integration testing and TDD will have their own dedicated workshops.
Model driven testing (MDT) provides several advantages over traditional code-based testing approaches. MDT allows testing to be integrated into the design process, enabling frequent and early testing. Test architectures and test cases can be automatically generated from models, using techniques like animated sequence diagrams to simulate scenarios and effectively record test cases. This helps improve requirements and code coverage at lower cost and in less time compared to traditional testing approaches.
The document discusses different types of integration and system testing for software. It describes integration testing strategies like big bang, bottom-up, top-down, and sandwich testing. Integration testing aims to test interfaces between subsystems. System testing includes functional testing to validate requirements, performance testing to evaluate non-functional properties, and acceptance testing for client approval. Stubs and drivers are used to isolate components during integration and system testing.
The document discusses various software testing techniques including black-box testing which focuses on inputs and outputs without seeing internal code, and white-box testing which considers internal logic and structures. Different levels of testing are covered from unit to acceptance testing. Strategies for effective test case design such as equivalence partitioning and boundary value analysis are also presented.
The document discusses unit testing and provides guidance on how to effectively implement unit testing. It defines unit testing as testing individual units or components of software code to verify they are functioning as intended. The document outlines best practices for unit testing such as writing test cases that cover valid, invalid, and boundary conditions. It also recommends testing frameworks like JUnit that can automate running test cases. Overall, the document advocates for developing a rigorous unit testing strategy and practicing habits like writing tests first and continuously running tests to improve code quality.
The document provides an overview of software testing. It discusses the importance of having a systematic testing plan and achieving high test coverage. The key topics covered include unit testing, integration testing, security testing, designing tests for high coverage using techniques like equivalence partitioning and boundary value analysis, and measuring test coverage at the code level using approaches such as control flow testing and state-based testing. Examples are provided to illustrate acceptance testing and defining states for state-based testing. The overall goal of software testing discussed is to find faults as efficiently as possible by prioritizing some test cases that are more likely to uncover errors.
The document discusses Google Test, an open source unit testing framework for C++ that can also be used for testing C code, providing an overview of its features and how to implement unit tests using common patterns like test fixtures, assertions, and death tests to validate expected failures. It also covers best practices for writing effective unit tests, including keeping tests independent, focused, and fast-running.
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.
This document discusses various software testing methodologies. It begins by defining software testing and its objectives. It then covers topics like verification and validation, unit testing, integration testing strategies, validation testing, system testing types, and software testing strategies. The remainder of the document focuses on different types of testing like white-box testing, black-box testing, and grey-box testing along with techniques like structural testing, code coverage, equivalence partitioning, and boundary value analysis.
Transform Your Communication with Cloud-Based IVR SolutionsTheSMSPoint
Discover the power of Cloud-Based IVR Solutions to streamline communication processes. Embrace scalability and cost-efficiency while enhancing customer experiences with features like automated call routing and voice recognition. Accessible from anywhere, these solutions integrate seamlessly with existing systems, providing real-time analytics for continuous improvement. Revolutionize your communication strategy today with Cloud-Based IVR Solutions. Learn more at: https://thesmspoint.com/channel/cloud-telephony
Top Benefits of Using Salesforce Healthcare CRM for Patient Management.pdfVALiNTRY360
Salesforce Healthcare CRM, implemented by VALiNTRY360, revolutionizes patient management by enhancing patient engagement, streamlining administrative processes, and improving care coordination. Its advanced analytics, robust security, and seamless integration with telehealth services ensure that healthcare providers can deliver personalized, efficient, and secure patient care. By automating routine tasks and providing actionable insights, Salesforce Healthcare CRM enables healthcare providers to focus on delivering high-quality care, leading to better patient outcomes and higher satisfaction. VALiNTRY360's expertise ensures a tailored solution that meets the unique needs of any healthcare practice, from small clinics to large hospital systems.
For more info visit us https://valintry360.com/solutions/health-life-sciences
Need for Speed: Removing speed bumps from your Symfony projects ⚡️Łukasz Chruściel
No one wants their application to drag like a car stuck in the slow lane! Yet it’s all too common to encounter bumpy, pothole-filled solutions that slow the speed of any application. Symfony apps are not an exception.
In this talk, I will take you for a spin around the performance racetrack. We’ll explore common pitfalls - those hidden potholes on your application that can cause unexpected slowdowns. Learn how to spot these performance bumps early, and more importantly, how to navigate around them to keep your application running at top speed.
We will focus in particular on tuning your engine at the application level, making the right adjustments to ensure that your system responds like a well-oiled, high-performance race car.
UI5con 2024 - Boost Your Development Experience with UI5 Tooling ExtensionsPeter Muessig
The UI5 tooling is the development and build tooling of UI5. It is built in a modular and extensible way so that it can be easily extended by your needs. This session will showcase various tooling extensions which can boost your development experience by far so that you can really work offline, transpile your code in your project to use even newer versions of EcmaScript (than 2022 which is supported right now by the UI5 tooling), consume any npm package of your choice in your project, using different kind of proxies, and even stitching UI5 projects during development together to mimic your target environment.
How Can Hiring A Mobile App Development Company Help Your Business Grow?ToXSL Technologies
ToXSL Technologies is an award-winning Mobile App Development Company in Dubai that helps businesses reshape their digital possibilities with custom app services. As a top app development company in Dubai, we offer highly engaging iOS & Android app solutions. https://rb.gy/necdnt
Measures in SQL (SIGMOD 2024, Santiago, Chile)Julian Hyde
SQL has attained widespread adoption, but Business Intelligence tools still use their own higher level languages based upon a multidimensional paradigm. Composable calculations are what is missing from SQL, and we propose a new kind of column, called a measure, that attaches a calculation to a table. Like regular tables, tables with measures are composable and closed when used in queries.
SQL-with-measures has the power, conciseness and reusability of multidimensional languages but retains SQL semantics. Measure invocations can be expanded in place to simple, clear SQL.
To define the evaluation semantics for measures, we introduce context-sensitive expressions (a way to evaluate multidimensional expressions that is consistent with existing SQL semantics), a concept called evaluation context, and several operations for setting and modifying the evaluation context.
A talk at SIGMOD, June 9–15, 2024, Santiago, Chile
Authors: Julian Hyde (Google) and John Fremlin (Google)
https://doi.org/10.1145/3626246.3653374
Using Query Store in Azure PostgreSQL to Understand Query PerformanceGrant Fritchey
Microsoft has added an excellent new extension in PostgreSQL on their Azure Platform. This session, presented at Posette 2024, covers what Query Store is and the types of information you can get out of it.
8 Best Automated Android App Testing Tool and Framework in 2024.pdfkalichargn70th171
Regarding mobile operating systems, two major players dominate our thoughts: Android and iPhone. With Android leading the market, software development companies are focused on delivering apps compatible with this OS. Ensuring an app's functionality across various Android devices, OS versions, and hardware specifications is critical, making Android app testing essential.
Hand Rolled Applicative User ValidationCode KataPhilip Schwarz
Could you use a simple piece of Scala validation code (granted, a very simplistic one too!) that you can rewrite, now and again, to refresh your basic understanding of Applicative operators <*>, <*, *>?
The goal is not to write perfect code showcasing validation, but rather, to provide a small, rough-and ready exercise to reinforce your muscle-memory.
Despite its grandiose-sounding title, this deck consists of just three slides showing the Scala 3 code to be rewritten whenever the details of the operators begin to fade away.
The code is my rough and ready translation of a Haskell user-validation program found in a book called Finding Success (and Failure) in Haskell - Fall in love with applicative functors.
Flutter is a popular open source, cross-platform framework developed by Google. In this webinar we'll explore Flutter and its architecture, delve into the Flutter Embedder and Flutter’s Dart language, discover how to leverage Flutter for embedded device development, learn about Automotive Grade Linux (AGL) and its consortium and understand the rationale behind AGL's choice of Flutter for next-gen IVI systems. Don’t miss this opportunity to discover whether Flutter is right for your project.
A Study of Variable-Role-based Feature Enrichment in Neural Models of CodeAftab Hussain
Understanding variable roles in code has been found to be helpful by students
in learning programming -- could variable roles help deep neural models in
performing coding tasks? We do an exploratory study.
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2. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 2
Outline
Terminology
Types of errors
Dealing with errors
Quality assurance vs Testing
Component Testing
Unit testing
Integration testing
Testing Strategy
Design Patterns & Testing
System testing
Function testing
Structure Testing
Performance testing
Acceptance testing
Installation testing
3. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 3
Some Observations
It is impossible to completely test any nontrivial module or any
system
Theoretical limitations: Halting problem
Practial limitations: Prohibitive in time and cost
Testing can only show the presence of bugs, not their absence
(Dijkstra)
loop 200 times
total number of execution paths?
??
4. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 4
Testing Activities
Tested
Subsystem
Subsystem
Code
Functional
Integration
Unit
Tested
Subsystem
Requirements
Analysis
Document
System
Design
Document
Tested Subsystem
Test Test
Test
Unit
Test
Unit
Test
User
Manual
Requirements
Analysis
Document
Subsystem
Code
Subsystem
Code
All tests by developer
Functioning
System
Integrated
Subsystems
Cf. levels of testing
5. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 5
Global
Requirements
Testing Activities continued
User’s understanding
Tests by developer
Performance Acceptance
Client’s
Understanding
of Requirements
Test
Functioning
System
Test
Installation
User
Environment
Test
System in
Use
Usable
System
Validated
System
Accepted
System
Tests (?) by user
Tests by client
6. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 6
Levels of Testing in V Model
system
requirements
system
integration
software
requirements
preliminary
design
detailed
design
code &
debug
acceptance
test
software
integration
component
test
unit
test
Time
Level
of
abstraction
N.B.: component test vs. unit test; acceptance test vs. system integration
7. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 7
Test Planning
A Test Plan:
covers all types and phases of
testing
guides the entire testing process
who, why, when, what
developed as requirements,
functional specification, and high-
level design are developed
should be done before
implementation starts
A test plan includes:
test objectives
schedule and logistics
test strategies
test cases
procedure
data
expected result
procedures for handling
problems
[Pressman]
8. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 8
Fault Handling Techniques
Testing
Fault Handling
Fault Avoidance
Fault Tolerance
Fault Detection
Debugging
Unit
Testing
Integration
Testing
System
Testing
Verification
Configuration
Management
Atomic
Transactions
Modular
Redundancy
Correctness
Debugging
Performance
Debugging
Reviews
Design
Methodology
9. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 9
Quality Assurance encompasses Testing
Usability Testing
Quality Assurance
Testing
Prototype
Testing
Scenario
Testing
Product
Testing
Fault Avoidance Fault Tolerance
Fault Detection
Debugging
Unit
Testing
Integration
Testing
System
Testing
Verification
Configuration
Management
Atomic
Transactions
Modular
Redundancy
Correctness
Debugging
Performance
Debugging
Reviews
Walkthrough Inspection
10. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 10
Types of Testing
Unit Testing:
Individual subsystem
Carried out by developers
Goal: Confirm that subsystems is correctly coded and carries out
the intended functionality
Integration Testing:
Groups of subsystems (collection of classes) and eventually the
entire system
Carried out by developers
Goal: Test the interface among the subsystem
11. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 11
System Testing
System Testing:
The entire system
Carried out by developers
Goal: Determine if the system meets the requirements (functional
and global)
Acceptance Testing:
Evaluates the system delivered by developers
Carried out by the client. May involve executing typical
transactions on site on a trial basis
Goal: Demonstrate that the system meets customer requirements
and is ready to use
Implementation (Coding) and testing go hand in hand
Terminology:
system testing here = validation testing
2 kinds of Acceptance testing
12. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 12
Unit Testing
Informal:
Incremental coding
Static Analysis:
Hand execution: Reading the source code
Walk-Through (informal presentation to others)
Code Inspection (formal presentation to others)
Automated Tools checking for
syntactic and semantic errors
departure from coding standards
Dynamic Analysis:
Black-box testing (Test the input/output behavior)
White-box testing (Test the internal logic of the subsystem or object)
Data-structure based testing (Data types determine test cases)
Which is more effective, static or dynamic analysis?
Write a little, test a little
13. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 13
Black-box Testing
Focus: I/O behavior. If for any given input, we can predict the
output, then the module passes the test.
Almost always impossible to generate all possible inputs ("test
cases")
Goal: Reduce number of test cases by equivalence partitioning:
Divide input conditions into equivalence classes
Choose test cases for each equivalence class. (Example: If an object
is supposed to accept a negative number, testing one negative
number is enough)
If x = 3 then …
What would be the equivalence classes?
If x > -5 and x < 5 then …
why?
14. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 14
Black-box Testing (Continued)
Selection of equivalence classes (No rules, only guidelines):
Input is valid across range of values. Select test cases from 3
equivalence classes:
Below the range
Within the range
Above the range
Input is valid if it is from a discrete set. Select test cases from 2
equivalence classes:
Valid discrete value
Invalid discrete value
Another solution to select only a limited amount of test cases:
Get knowledge about the inner workings of the unit being tested =>
white-box testing
Are these complete?
15. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 15
White-box Testing
Focus: Thoroughness (Coverage). Every statement in the component is
executed at least once.
Four types of white-box testing
Statement Testing
Loop Testing
Path Testing
Branch Testing
16. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 16
if ( i =TRUE) printf("YESn");else printf("NOn");
Test cases: 1) i = TRUE; 2) i = FALSE
White-box Testing (Continued)
Statement Testing (Algebraic Testing): Test single statements
Loop Testing:
Cause execution of the loop to be skipped completely. (Exception:
Repeat loops)
Loop to be executed exactly once
Loop to be executed more than once
Path testing:
Make sure all paths in the program are executed
Branch Testing (Conditional Testing): Make sure that each
possible outcome from a condition is tested at least once
17. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 17
Loop Testing
Nested
Loops
Concatenated
Loops Unstructured
Loops
Simple
loop
White-Box Testing
Why is loop testing important?
[Pressman]
18. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 18
/*Read in and sum the scores*/
White-box Testing Example
FindMean(float Mean, FILE ScoreFile)
{ SumOfScores = 0.0; NumberOfScores = 0; Mean = 0;
Read(Scor
eFile, Score);
while (! EOF(ScoreFile) {
if ( Score > 0.0 ) {
SumOfScores = SumOfScores + Score;
NumberOfScores++;
}
Read(ScoreFile, Score);
}
/* Compute the mean and print the result */
if (NumberOfScores > 0 ) {
Mean = SumOfScores/NumberOfScores;
printf("The mean score is %f n", Mean);
} else
printf("No scores found in filen");
}
19. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 19
White-box Testing Example: Determining the Paths
FindMean (FILE ScoreFile)
{ float SumOfScores = 0.0;
int NumberOfScores = 0;
float Mean=0.0; float Score;
Read(ScoreFile, Score);
while (! EOF(ScoreFile) {
if (Score > 0.0 ) {
SumOfScores = SumOfScores + Score;
NumberOfScores++;
}
Read(ScoreFile, Score);
}
/* Compute the mean and print the result */
if (NumberOfScores > 0) {
Mean = SumOfScores / NumberOfScores;
printf(“ The mean score is %fn”, Mean);
} else
printf (“No scores found in filen”);
}
1
2
3
4
5
7
6
8
9
20. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 20
Constructing the Logic Flow Diagram
Start
2
3
4 5
6
7
8 9
Exit
1
F
T F
T F
T
21. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 21
Finding the Test Cases
Start
2
3
4 5
6
7
8 9
Exit
1
b
d e
g
f
i j
h
c
k l
a (Covered by any data)
(Data set must
(Data set must contain at least one value)
be empty)
(Total score > 0.0)
(Total score < 0.0)
(Positive score) (Negative score)
(Reached if either f or
e is reached)
22. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 22
Comparison of White & Black-box Testing 25.1.2002
White-box Testing:
Potentially infinite number of
paths have to be tested
White-box testing often tests
what is done, instead of what
should be done
Cannot detect missing use cases
Black-box Testing:
Potential combinatorical
explosion of test cases (valid &
invalid data)
Often not clear whether the
selected test cases uncover a
particular error
Does not discover extraneous
use cases ("features")
Both types of testing are needed
White-box testing and black box
testing are the extreme ends of a
testing continuum.
Any choice of test case lies in
between and depends on the
following:
Number of possible logical paths
Nature of input data
Amount of computation
Complexity of algorithms and
data structures
Self reading
23. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 23
The 4 Testing Steps
1. Select what has to be
measured
Analysis: Completeness of
requirements
Design: tested for cohesion
Implementation: Code tests
2. Decide how the testing is
done
Code inspection
Proofs (Design by Contract)
Black-box, white box,
Select integration testing
strategy (big bang, bottom
up, top down, sandwich)
3. Develop test cases
A test case is a set of test
data or situations that will be
used to exercise the unit
(code, module, system) being
tested or about the attribute
being measured
4. Create the test oracle
An oracle contains of the
predicted results for a set of
test cases
The test oracle has to be
written down before the
actual testing takes place
Next module
24. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 24
Guidance for Test Case Selection
Use analysis knowledge
about functional
requirements (black-box
testing):
Use cases
Expected input data
Invalid input data
Use design knowledge about
system structure, algorithms,
data structures (white-box
testing):
Control structures
Test branches, loops, ...
Data structures
Test records fields, arrays,
...
Use implementation
knowledge about algorithms:
Examples:
Force division by zero
Use sequence of test cases for
interrupt handler
Self reading
25. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 25
Unit-testing Heuristics
1. Create unit tests as soon as object
design is completed:
Black-box test: Test the use
cases & functional model
White-box test: Test the
dynamic model
Data-structure test: Test the
object model
2. Develop the test cases
Goal: Find the minimal
number of test cases to cover
as many paths as possible
3. Cross-check the test cases to
eliminate duplicates
Don't waste your time!
4. Desk check your source code
Reduces testing time
5. Create a test harness
Test drivers and test stubs are
needed for integration testing
6. Describe the test oracle
Often the result of the first
successfully executed test
7. Execute the test cases
Don’t forget regression testing
Re-execute test cases every time
a change is made.
8. Compare the results of the test with the
test oracle
Automate as much as possible
Self reading
Big cost -> what should be done?
26. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 26
OOT Strategy
class testing is the equivalent of unit testing
operations within the class are tested
the state behavior of the class is examined
integration applied three different strategies/levels of
abstraction
thread-based testing—integrates the set of classes required
to respond to one input or event
use-based testing—integrates the set of classes required to
respond to one use case
cluster testing—integrates the set of classes required to
demonstrate one collaboration
…if there is no nesting of classes
…this is pushing…
[Pressman]
Recall: model-driven software development
27. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 27
OOT—Test Case Design
Berard [BER93] proposes the following approach:
1. Each test case should be uniquely identified and should be explicitly
associated with the class to be tested,
2. A list of testing steps should be developed for each test and should
contain [BER94]:
a. a list of specified states for the object that is to be tested
b. a list of messages and operations that will be exercised as a
consequence of the test how can this be done?
c. a list of exceptions that may occur as the object is tested
d. a list of external conditions (i.e., changes in the environment external
to the software that must exist in order to properly conduct the test)
{people, machine, time of operation, etc.}
[Pressman]
This is a kind of data structure testing
28. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 28
OOT Methods: Behavior Testing
empty
acct
open setupAccnt
set up
acct
deposit
(initial)
working
acct
withdrawal
(final)
dead
acct close
nonworking
acct
deposit
withdraw
balance
credit
accntInfo
Figure 14.3 State diagram for Account class (adapted from [ KIR94])
The tests to be
designed should
achieve all state
coverage [KIR94].
That is, the operation
sequences should
cause the Account
class to make
transition through all
allowable states
This can act as an oracle
[Pressman]
29. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 29
Who Tests the Software?
developer independent tester
Understands the system
but, will test "gently"
and, is driven by "delivery"
Must learn about the system,
but, will attempt to break it
and, is driven by quality
[Pressman]
30. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 30
Counting Bugs
Sometimes reliability requirements take the form:
"The software shall have no more than X bugs/1K LOC"
But how do we measure bugs at delivery time?
Bebugging Process - based on a Monte Carlo technique for statistical analysis of random events.
1. before testing, a known number of bugs (seeded bugs) are secretly inserted.
2. estimate the number of bugs in the system
3. remove (both known and new) bugs.
# of detected seeded bugs/ # of seeded bugs = # of detected bugs/ # of bugs in the system
# of bugs in the system = # of seeded bugs x # of detected bugs /# of detected seeded bugs
Example: secretely seed 10 bugs
an independent test team detects 120 bugs (6 for the seeded)
# of bugs in the system = 10 x 120/6 = 200
# of bugs in the system after removal = 200 - 120 - 4 = 76
But, deadly bugs vs. insignifant ones; not all bugs are equally detectable; ( Suggestion [Musa87]:
"No more than X bugs/1K LOC may be detected during testing"
"No more than X bugs/1K LOC may be remain after delivery,
as calculated by the Monte Carlo seeding technique"
NFRs: Reliability [Chung, RE Lecture Notes]]
31. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 31
Summary
Testing is still a black art, but many rules and heuristics are
available
Testing consists of component-testing (unit testing, integration
testing) and system testing, and …
OOT and architectural testing, still challenging
User-oriented reliability modeling and evaluation not adequate
Testing has its own lifecycle
32. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 32
Additional Slides
33. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 33
Terminology
Reliability: The measure of success with which the observed
behavior of a system confirms to some specification of its
behavior.
Failure: Any deviation of the observed behavior from the
specified behavior.
Error: The system is in a state such that further processing by
the system will lead to a failure.
Fault (Bug): The mechanical or algorithmic cause of an error.
There are many different types of errors and different ways how
we can deal with them.
34. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 34
Examples of Faults and Errors
Faults in the Interface
specification
Mismatch between what the
client needs and what the
server offers
Mismatch between
requirements and
implementation
Algorithmic Faults
Missing initialization
Branching errors (too soon,
too late)
Missing test for nil
Mechanical Faults (very
hard to find)
Documentation does not
match actual conditions or
operating procedures
Errors
Stress or overload errors
Capacity or boundary errors
Timing errors
Throughput or performance
errors
35. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 35
Dealing with Errors
Verification:
Assumes hypothetical environment that does not match real
environment
Proof might be buggy (omits important constraints; simply wrong)
Modular redundancy:
Expensive
Declaring a bug to be a “feature”
Bad practice
Patching
Slows down performance
Testing (this lecture)
Testing is never good enough
36. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 36
Another View on How to Deal with Errors
Error prevention (before the system is released):
Use good programming methodology to reduce complexity
Use version control to prevent inconsistent system
Apply verification to prevent algorithmic bugs
Error detection (while system is running):
Testing: Create failures in a planned way
Debugging: Start with an unplanned failures
Monitoring: Deliver information about state. Find performance bugs
Error recovery (recover from failure once the system is released):
Data base systems (atomic transactions)
Modular redundancy
Recovery blocks
37. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 37
What is this?
A failure?
An error?
A fault?
Need to specify
the desired behavior first!
38. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 38
Erroneous State (“Error”)
39. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 39
Algorithmic Fault
40. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 40
Mechanical Fault
41. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 41
How do we deal with Errors and Faults?
42. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 42
Verification?
43. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 43
Modular Redundancy?
44. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 44
Declaring the Bug
as a Feature?
45. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 45
Patching?
46. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 46
Testing?
47. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 47
Testing takes creativity
Testing often viewed as dirty work.
To develop an effective test, one must have:
Detailed understanding of the system
Knowledge of the testing techniques
Skill to apply these techniques in an effective and efficient manner
Testing is done best by independent testers
We often develop a certain mental attitude that the program should
in a certain way when in fact it does not.
Programmer often stick to the data set that makes the program
work
"Don’t mess up my code!"
A program often does not work when tried by somebody else.
Don't let this be the end-user.
48. Bernd Bruegge & Allen H. Dutoit Object-Oriented Software Engineering: Using UML, Patterns, and Java 48
Test Cases
Test case 1 : ? (To execute loop exactly once)
Test case 2 : ? (To skip loop body)
Test case 3: ?,? (to execute loop more than once)
These 3 test cases cover all control flow paths