Coding Standard and coding Guidelines, Code Review, Software Documentation, Testing Strategies, Testing Techniques and Test Case, Test Suites Design, Testing Conventional
Applications, Testing Object Oriented Applications, Testing Web and Mobile Applications, Testing Tools (Win runner, Load runner).
Black box testing refers to testing software without knowledge of its internal implementation by focusing on inputs and outputs. There are several techniques including boundary value analysis, equivalence partitioning, state transition testing, and graph-based testing. Black box testing is useful for testing functionality, behavior, and non-functional aspects from the end user's perspective.
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 key concepts in software design, including:
- Design involves modeling the system architecture, interfaces, and components before implementation. This allows assessment and improvement of quality.
- Important design concepts span abstraction, architecture, patterns, separation of concerns, modularity, information hiding, and functional independence. Architecture defines overall structure and interactions. Patterns help solve common problems.
- Separation of concerns and related concepts like modularity and information hiding help decompose problems into independently designed and optimized pieces to improve manageability. Functional independence means each module has a single, well-defined purpose with minimal interaction.
The document discusses requirements analysis and specification in software engineering. It defines what requirements are and explains the typical activities involved - requirements gathering, analysis, and specification. The importance of documenting requirements in a Software Requirements Specification (SRS) document is explained. Key sections of an SRS like stakeholders, types of requirements (functional and non-functional), and examples are covered. Special attention is given to requirements for critical systems and importance of non-functional requirements.
Risk management involves identifying potential problems, assessing their likelihood and impacts, and developing strategies to address them. There are two main risk strategies - reactive, which addresses risks after issues arise, and proactive, which plans ahead. Key steps in proactive risk management include identifying risks through checklists, estimating their probability and impacts, developing mitigation plans, monitoring risks and mitigation effectiveness, and adjusting plans as needed. Common risk categories include project risks, technical risks, and business risks.
This ppt covers the following
A strategic approach to testing
Test strategies for conventional software
Test strategies for object-oriented software
Validation testing
System testing
The art of debugging
Integration testing is a process that tests the interfaces between integrated software modules or units. It aims to expose faults in their interaction by deploying modules together and tracking defects from test results. There are various challenges like managing complex integration between new and legacy systems from different companies. Different types of incremental approaches include top-down, bottom-up, and sandwich methods, as well as a big bang approach for small systems. Integration testing provides benefits like early testing, detecting interface errors, and improving test coverage and reliability.
Black box testing refers to testing software without knowledge of its internal implementation by focusing on inputs and outputs. There are several techniques including boundary value analysis, equivalence partitioning, state transition testing, and graph-based testing. Black box testing is useful for testing functionality, behavior, and non-functional aspects from the end user's perspective.
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 key concepts in software design, including:
- Design involves modeling the system architecture, interfaces, and components before implementation. This allows assessment and improvement of quality.
- Important design concepts span abstraction, architecture, patterns, separation of concerns, modularity, information hiding, and functional independence. Architecture defines overall structure and interactions. Patterns help solve common problems.
- Separation of concerns and related concepts like modularity and information hiding help decompose problems into independently designed and optimized pieces to improve manageability. Functional independence means each module has a single, well-defined purpose with minimal interaction.
The document discusses requirements analysis and specification in software engineering. It defines what requirements are and explains the typical activities involved - requirements gathering, analysis, and specification. The importance of documenting requirements in a Software Requirements Specification (SRS) document is explained. Key sections of an SRS like stakeholders, types of requirements (functional and non-functional), and examples are covered. Special attention is given to requirements for critical systems and importance of non-functional requirements.
Risk management involves identifying potential problems, assessing their likelihood and impacts, and developing strategies to address them. There are two main risk strategies - reactive, which addresses risks after issues arise, and proactive, which plans ahead. Key steps in proactive risk management include identifying risks through checklists, estimating their probability and impacts, developing mitigation plans, monitoring risks and mitigation effectiveness, and adjusting plans as needed. Common risk categories include project risks, technical risks, and business risks.
This ppt covers the following
A strategic approach to testing
Test strategies for conventional software
Test strategies for object-oriented software
Validation testing
System testing
The art of debugging
Integration testing is a process that tests the interfaces between integrated software modules or units. It aims to expose faults in their interaction by deploying modules together and tracking defects from test results. There are various challenges like managing complex integration between new and legacy systems from different companies. Different types of incremental approaches include top-down, bottom-up, and sandwich methods, as well as a big bang approach for small systems. Integration testing provides benefits like early testing, detecting interface errors, and improving test coverage and reliability.
This document discusses software coding standards and guidelines. It explains that coding standards provide rules for writing consistent, robust code that is easily understood. Coding transforms a system design into code and tests the code. Standards help ensure maintainability, adding new features, clean coding, and fewer errors. The document provides examples of coding standards like limiting global variables and naming conventions. It also discusses code reviews to find logical errors and oversights, as well as the importance of documentation for requirements, architecture, code, manuals, and marketing.
This document discusses different process models used in software development. It describes the key phases and characteristics of several common process models including waterfall, prototyping, V-model, incremental, iterative, spiral and agile development models. The waterfall model involves sequential phases from requirements to maintenance without iteration. Prototyping allows for user feedback earlier. The V-model adds verification and validation phases. Incremental and iterative models divide the work into smaller chunks to allow for iteration and user feedback throughout development.
This document discusses different approaches to requirements modeling including scenario-based modeling using use cases and activity diagrams, data modeling using entity-relationship diagrams, and class-based modeling using class-responsibility-collaborator diagrams. Requirements modeling depicts requirements using text and diagrams to help validate requirements from different perspectives and uncover errors, inconsistencies, and omissions. The models focus on what the system needs to do at a high level rather than implementation details.
Software testing is an important phase of the software development process that evaluates the functionality and quality of a software application. It involves executing a program or system with the intent of finding errors. Some key points:
- Software testing is needed to identify defects, ensure customer satisfaction, and deliver high quality products with lower maintenance costs.
- It is important for different stakeholders like developers, testers, managers, and end users to work together throughout the testing process.
- There are various types of testing like unit testing, integration testing, system testing, and different methodologies like manual and automated testing. Proper documentation is also important.
- Testing helps improve the overall quality of software but can never prove that there
The document discusses different software engineering process models including:
1. The waterfall model which is a linear sequential model where each phase must be completed before moving to the next.
2. Prototyping models which allow requirements to be refined through building prototypes.
3. RAD (Rapid Application Development) which emphasizes short development cycles through reuse and code generation.
4. Incremental models which deliver functionality in increments with early increments focusing on high priority requirements.
5. The spiral model which has multiple iterations of planning, risk analysis, engineering and evaluation phases.
This document discusses statistical quality assurance techniques for software. It explains that statistical quality assurance involves collecting information about software errors, categorizing them, tracing each error to its underlying cause using the Pareto principle to identify the most common causes, and correcting problems that led to those errors. Common causes of software defects are then listed, such as incomplete specifications, misinterpreted customer communication, and violations of programming standards. The document states that statistical quality assurance techniques have been shown to significantly improve software quality at some organizations through around a 50% reduction in defects per year. It concludes by introducing Six Sigma as a widely used strategy for statistical quality assurance, originally developed by Motorola, which uses data analysis to measure and improve processes by identifying and eliminating
The document provides an overview of software testing techniques and strategies. It discusses unit testing, integration testing, validation testing, system testing, and debugging. The key points covered include:
- Unit testing involves testing individual software modules or components in isolation from the rest of the system. This includes testing module interfaces, data structures, boundary conditions, and error handling paths.
- Integration testing combines software components into clusters or builds to test their interactions before full system integration. Approaches include top-down and bottom-up integration.
- Validation testing verifies that the software meets the intended requirements and customer expectations defined in validation criteria.
- System testing evaluates the fully integrated software system, including recovery, security, stress,
The document discusses various techniques for debugging software bugs, including gathering relevant information, forming and testing hypotheses about the cause, and strategies like tracing execution, simplifying tests, questioning assumptions, and cleaning up unused code. It also provides a checklist for determining the root cause of bugs and ensuring debugging efforts are focused on the right location. The goal of debugging is to understand why bugs occur so they can be removed and prevent future bugs through improved testing, risk management, and learning from past issues.
This document discusses design patterns, beginning with how they were introduced in architecture in the 1950s and became popularized by the "Gang of Four" researchers. It defines what patterns are and provides examples of different types of patterns (creational, structural, behavioral) along with common patterns in each category. The benefits of patterns are that they enable reuse, improve communication, and ease the transition to object-oriented development. Potential drawbacks are that patterns do not directly lead to code reuse and can be overused. Effective use requires applying patterns strategically rather than recasting all code as patterns.
White-box testing is a software testing technique that uses knowledge of the internal workings of a system to design test cases. It involves testing internal structures or workings of a program, such as code coverage. The document discusses different white-box testing techniques like statement coverage, decision coverage, condition coverage, and multiple condition coverage. It aims to execute every statement, decision path, condition, and combination of conditions in the code. White-box testing is more effective at finding defects earlier in the SDLC but also more expensive and difficult to implement than black-box testing.
Integration testing verifies the interfaces between software modules. It has two categories: bottom-up integration starts with unit testing, then subsystem testing, and finally system testing; top-down integration starts with the main routine and tests subroutines in order, using stubs. Automated tools can help with integration testing, such as module drivers, test data generators, environment simulators, and library management systems.
A test case is a set of conditions or variables under which a tester will determine whether a software system is working correctly. Test cases are often written as test scripts and collected into test suites. Characteristics of good test cases include being simple, clear, concise, complete, non-redundant, and having a reasonable probability of catching errors. Test cases should be developed to verify specific requirements or designs and include both positive and negative cases.
This lecture is about the detail definition of software quality and quality assurance. Provide details about software tesing and its types. Clear the basic concepts of software quality and software testing.
This document discusses 15 factors that influence quality and productivity in software development processes: individual ability, team communication, product complexity, appropriate notations, systematic approaches, change control, level of technology, level of reliability, problem understanding, available time, required skills, facilities and resources, adequacy of training, management skills, and appropriate goals. Each factor is described in 1-3 paragraphs on how it can impact quality and productivity.
This document discusses various code quality tools such as FindBugs, PMD, and Checkstyle. It provides information on what each tool is used for, how to install plugins for them in Eclipse, and how to configure them for use with Ant builds. FindBugs looks for potential bugs in Java bytecode. PMD scans source code for coding mistakes, dead code, complicated expressions, and duplicate code. Checkstyle checks that code complies with coding style rules. The document explains how to download and configure each tool so it can be run from Eclipse or as part of an Ant build.
The document discusses component-level design which occurs after architectural design. It aims to create a design model from analysis and architectural models. Component-level design can be represented using graphical, tabular, or text-based notations. The key aspects covered include:
- Defining a software component as a modular building block with interfaces and collaboration
- Designing class-based components following principles like open-closed and dependency inversion
- Guidelines for high cohesion and low coupling in components
- Designing conventional components using notations like sequence, if-then-else, and tabular representations
This document provides an overview of quality management concepts and techniques for software engineering. It discusses quality assurance, software reviews, formal technical reviews, statistical quality assurance, software reliability, and the ISO 9000 quality standards. The document includes slides on these topics with definitions, descriptions, and examples.
The document provides an overview of software architecture. It discusses software architecture versus design, architectural styles like layered and pipe-and-filter styles, software connectors like coordinators and adapters, and using architecture for project management, development and testing. Architectural styles from different domains like buildings are presented as analogies for software architecture styles. The benefits of architectural styles for explaining a system's structure and enabling development of system families are highlighted.
Coupling refers to the interdependence between software modules. There are several types of coupling from loose to tight, with the tightest being content coupling where one module relies on the internal workings of another. Cohesion measures how strongly related the functionality within a module is, ranging from coincidental to functional cohesion which is the strongest. Tight coupling and low cohesion can make software harder to maintain and reuse modules.
The document discusses the software design process. It begins by explaining that software design is an iterative process that translates requirements into a blueprint for constructing the software. It then describes the main steps and outputs of the design process, which include transforming specifications into design models, reviewing designs for quality, and producing a design document. The document also covers key concepts in software design like abstraction, architecture, patterns, modularity, and information hiding.
The document discusses test planning and management. It covers topics like test strategy, test plan, test automation, mutation testing, defects in software engineering, manual vs automation testing challenges, skills of quality testers, agile testing, and the Selenium testing tool. It provides information on creating test plans according to IEEE standards and discusses the components, requirements, and benefits of test automation frameworks and tools.
This document discusses various software testing techniques. It begins by explaining the goals of verification and validation as establishing confidence that software is fit for its intended use. It then covers different testing phases from component to integration testing. The document discusses both static and dynamic verification methods like inspections, walkthroughs, and testing. It details test case development techniques like equivalence partitioning and boundary value analysis. Finally, it covers white-box and structural testing methods that derive test cases from examining a program's internal structure.
This document discusses software coding standards and guidelines. It explains that coding standards provide rules for writing consistent, robust code that is easily understood. Coding transforms a system design into code and tests the code. Standards help ensure maintainability, adding new features, clean coding, and fewer errors. The document provides examples of coding standards like limiting global variables and naming conventions. It also discusses code reviews to find logical errors and oversights, as well as the importance of documentation for requirements, architecture, code, manuals, and marketing.
This document discusses different process models used in software development. It describes the key phases and characteristics of several common process models including waterfall, prototyping, V-model, incremental, iterative, spiral and agile development models. The waterfall model involves sequential phases from requirements to maintenance without iteration. Prototyping allows for user feedback earlier. The V-model adds verification and validation phases. Incremental and iterative models divide the work into smaller chunks to allow for iteration and user feedback throughout development.
This document discusses different approaches to requirements modeling including scenario-based modeling using use cases and activity diagrams, data modeling using entity-relationship diagrams, and class-based modeling using class-responsibility-collaborator diagrams. Requirements modeling depicts requirements using text and diagrams to help validate requirements from different perspectives and uncover errors, inconsistencies, and omissions. The models focus on what the system needs to do at a high level rather than implementation details.
Software testing is an important phase of the software development process that evaluates the functionality and quality of a software application. It involves executing a program or system with the intent of finding errors. Some key points:
- Software testing is needed to identify defects, ensure customer satisfaction, and deliver high quality products with lower maintenance costs.
- It is important for different stakeholders like developers, testers, managers, and end users to work together throughout the testing process.
- There are various types of testing like unit testing, integration testing, system testing, and different methodologies like manual and automated testing. Proper documentation is also important.
- Testing helps improve the overall quality of software but can never prove that there
The document discusses different software engineering process models including:
1. The waterfall model which is a linear sequential model where each phase must be completed before moving to the next.
2. Prototyping models which allow requirements to be refined through building prototypes.
3. RAD (Rapid Application Development) which emphasizes short development cycles through reuse and code generation.
4. Incremental models which deliver functionality in increments with early increments focusing on high priority requirements.
5. The spiral model which has multiple iterations of planning, risk analysis, engineering and evaluation phases.
This document discusses statistical quality assurance techniques for software. It explains that statistical quality assurance involves collecting information about software errors, categorizing them, tracing each error to its underlying cause using the Pareto principle to identify the most common causes, and correcting problems that led to those errors. Common causes of software defects are then listed, such as incomplete specifications, misinterpreted customer communication, and violations of programming standards. The document states that statistical quality assurance techniques have been shown to significantly improve software quality at some organizations through around a 50% reduction in defects per year. It concludes by introducing Six Sigma as a widely used strategy for statistical quality assurance, originally developed by Motorola, which uses data analysis to measure and improve processes by identifying and eliminating
The document provides an overview of software testing techniques and strategies. It discusses unit testing, integration testing, validation testing, system testing, and debugging. The key points covered include:
- Unit testing involves testing individual software modules or components in isolation from the rest of the system. This includes testing module interfaces, data structures, boundary conditions, and error handling paths.
- Integration testing combines software components into clusters or builds to test their interactions before full system integration. Approaches include top-down and bottom-up integration.
- Validation testing verifies that the software meets the intended requirements and customer expectations defined in validation criteria.
- System testing evaluates the fully integrated software system, including recovery, security, stress,
The document discusses various techniques for debugging software bugs, including gathering relevant information, forming and testing hypotheses about the cause, and strategies like tracing execution, simplifying tests, questioning assumptions, and cleaning up unused code. It also provides a checklist for determining the root cause of bugs and ensuring debugging efforts are focused on the right location. The goal of debugging is to understand why bugs occur so they can be removed and prevent future bugs through improved testing, risk management, and learning from past issues.
This document discusses design patterns, beginning with how they were introduced in architecture in the 1950s and became popularized by the "Gang of Four" researchers. It defines what patterns are and provides examples of different types of patterns (creational, structural, behavioral) along with common patterns in each category. The benefits of patterns are that they enable reuse, improve communication, and ease the transition to object-oriented development. Potential drawbacks are that patterns do not directly lead to code reuse and can be overused. Effective use requires applying patterns strategically rather than recasting all code as patterns.
White-box testing is a software testing technique that uses knowledge of the internal workings of a system to design test cases. It involves testing internal structures or workings of a program, such as code coverage. The document discusses different white-box testing techniques like statement coverage, decision coverage, condition coverage, and multiple condition coverage. It aims to execute every statement, decision path, condition, and combination of conditions in the code. White-box testing is more effective at finding defects earlier in the SDLC but also more expensive and difficult to implement than black-box testing.
Integration testing verifies the interfaces between software modules. It has two categories: bottom-up integration starts with unit testing, then subsystem testing, and finally system testing; top-down integration starts with the main routine and tests subroutines in order, using stubs. Automated tools can help with integration testing, such as module drivers, test data generators, environment simulators, and library management systems.
A test case is a set of conditions or variables under which a tester will determine whether a software system is working correctly. Test cases are often written as test scripts and collected into test suites. Characteristics of good test cases include being simple, clear, concise, complete, non-redundant, and having a reasonable probability of catching errors. Test cases should be developed to verify specific requirements or designs and include both positive and negative cases.
This lecture is about the detail definition of software quality and quality assurance. Provide details about software tesing and its types. Clear the basic concepts of software quality and software testing.
This document discusses 15 factors that influence quality and productivity in software development processes: individual ability, team communication, product complexity, appropriate notations, systematic approaches, change control, level of technology, level of reliability, problem understanding, available time, required skills, facilities and resources, adequacy of training, management skills, and appropriate goals. Each factor is described in 1-3 paragraphs on how it can impact quality and productivity.
This document discusses various code quality tools such as FindBugs, PMD, and Checkstyle. It provides information on what each tool is used for, how to install plugins for them in Eclipse, and how to configure them for use with Ant builds. FindBugs looks for potential bugs in Java bytecode. PMD scans source code for coding mistakes, dead code, complicated expressions, and duplicate code. Checkstyle checks that code complies with coding style rules. The document explains how to download and configure each tool so it can be run from Eclipse or as part of an Ant build.
The document discusses component-level design which occurs after architectural design. It aims to create a design model from analysis and architectural models. Component-level design can be represented using graphical, tabular, or text-based notations. The key aspects covered include:
- Defining a software component as a modular building block with interfaces and collaboration
- Designing class-based components following principles like open-closed and dependency inversion
- Guidelines for high cohesion and low coupling in components
- Designing conventional components using notations like sequence, if-then-else, and tabular representations
This document provides an overview of quality management concepts and techniques for software engineering. It discusses quality assurance, software reviews, formal technical reviews, statistical quality assurance, software reliability, and the ISO 9000 quality standards. The document includes slides on these topics with definitions, descriptions, and examples.
The document provides an overview of software architecture. It discusses software architecture versus design, architectural styles like layered and pipe-and-filter styles, software connectors like coordinators and adapters, and using architecture for project management, development and testing. Architectural styles from different domains like buildings are presented as analogies for software architecture styles. The benefits of architectural styles for explaining a system's structure and enabling development of system families are highlighted.
Coupling refers to the interdependence between software modules. There are several types of coupling from loose to tight, with the tightest being content coupling where one module relies on the internal workings of another. Cohesion measures how strongly related the functionality within a module is, ranging from coincidental to functional cohesion which is the strongest. Tight coupling and low cohesion can make software harder to maintain and reuse modules.
The document discusses the software design process. It begins by explaining that software design is an iterative process that translates requirements into a blueprint for constructing the software. It then describes the main steps and outputs of the design process, which include transforming specifications into design models, reviewing designs for quality, and producing a design document. The document also covers key concepts in software design like abstraction, architecture, patterns, modularity, and information hiding.
The document discusses test planning and management. It covers topics like test strategy, test plan, test automation, mutation testing, defects in software engineering, manual vs automation testing challenges, skills of quality testers, agile testing, and the Selenium testing tool. It provides information on creating test plans according to IEEE standards and discusses the components, requirements, and benefits of test automation frameworks and tools.
This document discusses various software testing techniques. It begins by explaining the goals of verification and validation as establishing confidence that software is fit for its intended use. It then covers different testing phases from component to integration testing. The document discusses both static and dynamic verification methods like inspections, walkthroughs, and testing. It details test case development techniques like equivalence partitioning and boundary value analysis. Finally, it covers white-box and structural testing methods that derive test cases from examining a program's internal structure.
White box testing involves testing internal program structure and code. It includes static testing like code reviews and structural testing like unit testing. Static testing checks code against requirements without executing. Structural testing executes code to test paths and conditions. Code coverage metrics like statement coverage measure what code is executed by tests. Code complexity metrics like cyclomatic complexity quantify complexity to determine necessary test cases. White box testing finds defects from incorrect code but may miss realistic errors and developers can overlook own code issues.
The document discusses software testing and analysis. It describes the goals of verification and validation as establishing confidence that software is fit for purpose without being completely defect-free. Both verification and validation are whole-life cycle processes involving static and dynamic techniques to discover defects and assess usability. The document outlines different testing and inspection methods like unit testing, integration testing, walkthroughs, and inspections and their roles in the verification and validation process.
This document provides an overview of various software engineering process models, including:
- Waterfall model which divides the software development life cycle into sequential phases like requirements, design, implementation, testing and maintenance.
- Iterative waterfall model which allows for feedback loops between phases to catch errors earlier.
- Prototyping model which involves building prototypes to refine requirements before development.
- Incremental/evolutionary model which develops the system in modules through successive versions.
- Spiral model which represents the software process as iterative loops to progressively develop and test the product.
- Agile models like Scrum and XP which emphasize adaptive planning, evolutionary development, team collaboration and frequent delivery of working software.
This document provides an overview of different software process models including the waterfall model, V-model, evolutionary development, component-based development, and incremental delivery. It describes the key phases and activities in each model. The V-model is explained in detail with its distinct development and validation phases like requirements, design, coding, unit testing, integration testing, system testing, and acceptance testing. Pros and cons of each model are also highlighted along with guidance on when each is generally most applicable.
The document discusses software coding and testing. It covers coding standards and guidelines, code review techniques like code walkthroughs and inspections, and types of software documentation. It then discusses various software testing strategies and techniques, including unit testing, integration testing, regression testing, smoke testing, and validation testing. The goal of testing is to find errors before delivery to end users. Different testing types focus on different parts of the software development process from individual code components to integrated systems.
Capability Building for Cyber Defense: Software Walk through and Screening Maven Logix
Ā
Dr. Fahim Arif who is the Director R&D at MCS, principal investigator and GHQ authorized consultant for Nexsource Pak (Pvt) Ltd) discussed the capability of building cyber defense in the Data Protection and Cyber Security event that was hosted recently by Maven Logix. In his session he gave the audience valuable information about the life cycle of a cyber-threat discussing what and how to take measures by performing formal code reviews, code inspections. He discussed essential elements of code review, paired programming and alternatives to treat and tackle cyber-threat
This document discusses context-driven test automation and describes four common contexts for automation: individual developer, development team, project, and product line. It analyzes two case studies - the ITE and xBVT test automation frameworks - and how they address common test automation tasks like distribution, setup/teardown, execution, verification and reporting differently depending on their context. The key lesson is that the approach that works best depends on who writes and uses the tests rather than a one-size-fits-all framework. Defining the context upfront helps determine how automation tasks are implemented.
Strategic Approach to Software Testing, Strategic Issues, Test Conventional Software, Test Strategies for Object-Oriented Software, Test Strategies for WebApps, Validation Testing, System Testing, The Art of Debugging, Software Testing Fundamentals, White-Box Testing, Basis Path Testing,
Control Structure Testing
Testing is a process used to identify the correctness, completeness and quality of developed computer software. It involves finding differences between expected and observed behavior by executing the system with different inputs. The goal of testing is to maximize the number of discovered faults and increase reliability. Testing techniques include unit testing of individual components, integration testing of combined components, and system testing of the full application. Fault avoidance techniques like code reviews aim to prevent errors from being introduced.
Architecting for the cloud storage build testLen Bass
Ā
This document discusses best practices for deploying applications to the cloud, including:
- Using a deployment pipeline with continuous integration, integration testing, and staging environments to minimize errors and delays.
- Managing versions and branches to prevent errors from multiple teams working simultaneously.
- Performing integration testing after each commit to catch errors early.
- Maintaining separate databases for different environments like test vs production.
- Using feature toggles to allow uncompleted code to be checked in without breaking builds.
- Performing staging tests using production data and load to thoroughly test before deployment.
Software testing strategies And its typesMITULJAMANG
Ā
Software Testing is a type of investigation to find out if there is any default or error present in the software so that the errors can be reduced or removed to increase the quality of the software and to check whether it fulfills the specifies requirements or not.
According to Glen Myers, software testing has the following objectives:
The process of investigating and checking a program to find whether there is an error or not and does it fulfill the requirements or not is called testing.
When the number of errors found during the testing is high, it indicates that the testing was good and is a sign of good test case.Finding an unknown error thatās wasnāt discovered yet is a sign of a successful and a good test case
The document discusses the Unified Process (UP) methodology for software development. It describes the key aspects of UP including iterative development with timeboxed iterations, four phases (inception, elaboration, construction, transition), architecture-centric and risk-driven approach, and nine core workflows (business modeling, requirements, design, implementation, test, deployment, project management, configuration management, environment). The document provides details on each of these aspects of UP and best practices for its implementation on a software project.
Testing is the process of validating and verifying software to ensure it meets specifications and functions as intended. There are different levels of testing including unit, integration, system, and acceptance testing. An important part of testing is having a test plan that outlines the test strategy, cases, and process to be followed. Testing helps find defects so the product can be improved.
Software test automation involves developing automated test scripts to test software. There are several benefits to test automation including saving time, freeing up test engineers from repetitive tasks, improving reliability of tests, and enabling certain types of testing. Effective test automation requires identifying what to automate based on factors like test type, prone to change areas, and standards. It also requires skills in test case design, frameworks, programming languages, and reporting. Proper design and requirements are needed for the test automation framework and tools. The test automation process should follow the same development lifecycle model as the product.
This document discusses software testing practices and processes. It covers topics like unit testing, integration testing, validation testing, test planning, and test types. The key points are that testing aims to find errors, good testing uses both valid and invalid inputs, and testing should have clear objectives and be assigned to experienced people. Testing is done at the unit, integration and system levels using techniques like black box testing.
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Software maintenance and configuration management, software engineeringRupesh Vaishnav
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Types of Software Maintenance, Re-Engineering, Reverse Engineering, Forward Engineering, The SCM Process, Identification of Objects in the Software Configuration, Version
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The document discusses the key tasks in requirements engineering including inception, elicitation, elaboration, negotiation, specification, validation and management. It describes each task such as inception involves establishing a basic understanding of the problem and potential solutions through questioning stakeholders. Elicitation involves drawing requirements from stakeholders through techniques like meetings. Specification can take the form of documents, models, scenarios or prototypes. The requirements specification is an important output and should have certain characteristics like being unambiguous and traceable.
Software Process Models, The Linear Sequential Model, The Prototyping Model, The RAD Model, Evolutionary Process Models, Agile Process Model, Component-Based Development, Process, Product and Process.
The document discusses software process models. It describes the waterfall model, which is a generic process framework for software engineering that defines five framework activities: communication, planning, modeling, construction, and deployment. It also discusses umbrella activities that are applied throughout the process, such as project tracking and control. The waterfall model prescribes distinct activities, actions, tasks, milestones, and work products for software development. However, process models need to be adapted to meet the needs of specific projects.
Agile development focuses on effective communication, customer collaboration, and incremental delivery of working software. The key principles of agile development according to the Agile Alliance include satisfying customers, welcoming changing requirements, frequent delivery, collaboration between business and development teams, and self-organizing teams. Extreme Programming (XP) is an agile process model that emphasizes planning with user stories, simple design, pair programming, unit testing, and frequent integration and testing.
An In-Depth Exploration of Natural Language Processing: Evolution, Applicatio...DharmaBanothu
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Natural language processing (NLP) has
recently garnered significant interest for the
computational representation and analysis of human
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as machine translation, email spam detection,
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and question answering. This paper first delineates
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followed by a review of the history and progression of
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Better Builder Magazine brings together premium product manufactures and leading builders to create better differentiated homes and buildings that use less energy, save water and reduce our impact on the environment. The magazine is published four times a year.
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Ā
Paper Title
Particle Swarm OptimizationāLong Short-Term Memory based Channel Estimation with Hybrid Beam Forming Power Transfer in WSN-IoT Applications
Authors
Reginald Jude Sixtus J and Tamilarasi Muthu, Puducherry Technological University, India
Abstract
Non-Orthogonal Multiple Access (NOMA) helps to overcome various difficulties in future technology wireless communications. NOMA, when utilized with millimeter wave multiple-input multiple-output (MIMO) systems, channel estimation becomes extremely difficult. For reaping the benefits of the NOMA and mm-Wave combination, effective channel estimation is required. In this paper, we propose an enhanced particle swarm optimization based long short-term memory estimator network (PSOLSTMEstNet), which is a neural network model that can be employed to forecast the bandwidth required in the mm-Wave MIMO network. The prime advantage of the LSTM is that it has the capability of dynamically adapting to the functioning pattern of fluctuating channel state. The LSTM stage with adaptive coding and modulation enhances the BER.PSO algorithm is employed to optimize input weights of LSTM network. The modified algorithm splits the power by channel condition of every single user. Participants will be first sorted into distinct groups depending upon respective channel conditions, using a hybrid beamforming approach. The network characteristics are fine-estimated using PSO-LSTMEstNet after a rough approximation of channels parameters derived from the received data.
Keywords
Signal to Noise Ratio (SNR), Bit Error Rate (BER), mm-Wave, MIMO, NOMA, deep learning, optimization.
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2. Coding Phase
ā¢ Coding is undertaken once design phase is
complete.
ā¢ During coding phase:
ā every module identified in the design document is
coded and unit tested.
ā¢ Unit testing :
ā testing of different modules of a system in isolation.
3. Unit Testing
āWhy test each module in isolation first?
āthen integrate the modules and again test the
set of modules?
āwhy not just test the integrated set of modules
once thoroughly?
4. Unit Testing
ļ® It is a good idea to test modules in
isolation before they are integrated:
ļ® it makes debugging easier.
5. ļ® If an error is detected when several modules are
being tested together,
ļ® it would be difficult to determine which module has the
error.
ļ® Another reason:
ļ® the modules with which this module needs to interface
may not be ready.
Unit Testing
6. Integration Testing
ā¢ After all modules of a system have
been coded and unit tested:
āintegration of modules is done
ā¢ according to an integration plan.
7. Integration Testing
ā¢ The full product takes shape:
ā only after all the modules have been integrated.
ā¢ Modules are integrated together according to an
integration plan:
ā involves integration of the modules through a number
of steps.
8. Integration Testing
ā¢ During each integration step,
āa number of modules are added to the
partially integrated system
ā¢ and the system is tested.
ā¢ Once all modules have been integrated
and tested,
āsystem testing can start.
9. System Testing
ā¢ During system testing:
āthe fully integrated system is tested
against the requirements recorded in
the SRS document.
10. Coding
ā¢ The input to the coding phase is the
design document.
ā¢ During coding phase:
āmodules identified in the design
document are coded according to the
module specifications.
11. Coding
ā¢ At the end of the design phase we have:
ā module structure (e.g. structure chart) of the system
ā module specifications:
ā¢ data structures and algorithms for each module.
ā¢ Objective of coding phase:
ā transform design into code
ā unit test the code.
12. Coding Standards
ā¢ Good software development
organizations require their
programmers to:
āadhere to some standard style of coding
ācalled coding standards.
13. Coding Standards
ā¢ Many software development organizations:
āformulate their own coding standards that suits
them most,
ārequire their engineers to follow these
standards rigorously.
14. Coding Standards
ā¢ Advantage of adhering to a standard style of
coding:
āit gives a uniform appearance to the codes
written by different engineers,
āit enhances code understanding,
āencourages good programming practices.
15. Coding Standards
ā¢ A coding standard
āsets out standard ways of doing several
things:
ā¢ the way variables are named,
ā¢ code is laid out,
ā¢ maximum number of source lines allowed per
function, etc.
16. Coding guidelines
ā¢ Provide general suggestions regarding
coding style to be followed:
āleave actual implementation of the
guidelines:
ā¢ to the discretion of the individual engineers.
17. Code inspection and code walk
throughs
ā¢ After a module has been coded,
ācode inspection and code walk through
are carried out
āensures that coding standards are
followed
āhelps detect as many errors as possible
before testing.
18. Code inspection and code walk
throughs
ā¢ Detect as many errors as possible during
inspection and walkthrough:
ādetected errors require less effort for
correction
ā¢ much higher effort needed if errors were to be
detected during integration or system testing.
19. Representative Coding
Standards
ā¢ Rules for limiting the use of globals:
ā what types of data can be declared global and what
can not.
ā¢ Naming conventions for
ā global variables,
ā local variables, and
ā constant identifiers.
20. Representative Coding Standards
ā¢ Header data:
ā Name of the module,
ā date on which the module was created,
ā author's name,
ā modification history,
ā synopsis of the module,
ā different functions supported, along with their
input/output parameters,
ā global variables accessed/modified by the module.
21. Representative Coding Standards
ā¢ Error return conventions and exception handling
mechanisms.
ā the way error and exception conditions are handled
should be standard within an organization.
ā For example, when different functions encounter
error conditions
ā¢ should either return a 0 or 1 consistently.
22. Representative Coding Guidelines
ā¢ Do not use too clever and difficult to understand
coding style.
ā Code should be easy to understand.
ā¢ Many inexperienced engineers actually take pride:
ā in writing cryptic and incomprehensible code.
23. Representative Coding Guidelines
ā¢ Clever coding can unclear meaning of the code:
ā hampers understanding.
āmakes later maintenance difficult.
ā¢ Avoid obscure side effects.
24. Representative Coding Guidelines
ā¢ The side effects of a function call include:
ā modification of parameters passed by reference,
ā modification of global variables,
ā I/O operations.
ā¢ An obscure side effect:
ā one that is not obvious from a casual examination of
the code.
25. Representative Coding Guidelines
ā¢ Obscure side effects make it difficult to
understand a piece of code.
ā¢ For example,
ā if a global variable is changed obscurely in
a called module,
ā it becomes difficult for anybody trying to
understand the code.
26. Representative Coding Guidelines
ā¢ Do not use an identifier (variable name) for
multiple purposes.
ā Programmers often use the same identifier for
multiple purposes.
ā For example, some programmers use a temporary
loop variable
ā¢ also for storing the final result.
27. Example use of a variable for
multiple purposes
ā¢ for(i=1;i<100;i++)
{ā¦..}
i=2*p*q;
return(i);
28. Use of a variable for multiple
purposes
ā¢ The justification given by programmers for such
use:
ā memory efficiency:
ā e.g. three variables use up three memory locations,
ā whereas the same variable used in three different
ways uses just one memory location.
29. Use of a variable for multiple
purposes
ā¢ There are several things wrong with this
approach:
ā hence should be avoided.
ā¢ Each variable should be given a name indicating
its purpose:
ā This is not possible if an identifier is used for multiple
purposes.
30. Use of a variable for multiple
purposes
ā¢ Leads to confusion and annoyance
āfor anybody trying to understand the
code.
āAlso makes future maintenance difficult.
31. Representative Coding Guidelines
ā¢ Code should be well-documented.
ā¢ Rules of thumb:
ā on the average there must be at least one comment
line
ā¢ for every three source lines.
ā The length of any function should not exceed 10
source lines.
33. Representative Coding Guidelines
ā¢ Do not use goto statements.
ā¢ Use of goto statements:
āmake a program unstructured
āmake it very difficult to understand.
34. Code Walk Through
ā¢ An informal code analysis technique.
ā undertaken after the coding of a module is complete.
ā¢ A few members of the development team select
some test cases:
ā simulate execution of the code by hand using these
test cases.
35. Code Inspection
ā¢ For instance, consider:
ā classical error of writing a procedure that modifies a
formal parameter
ā while the calling routine calls the procedure with a
constant actual parameter.
ā¢ It is more likely that such an error will be
discovered:
ā by looking for this kind of mistakes in the code,
ā rather than by simply hand simulating execution of the
procedure.
36. Code Inspection
ā¢ Good software development companies:
ā collect statistics of errors committed by their engineers
ā identify the types of errors most frequently committed.
ā¢ A list of common errors:
ā can be used during code inspection to look out for
possible errors.
37. Commonly made errors
ā¢ Use of uninitialized variables.
ā¢ Nonterminating loops.
ā¢ Array indices out of bounds.
ā¢ Incompatible assignments.
ā¢ Improper storage allocation and deallocation.
ā¢ Actual and formal parameter mismatch in procedure
calls.
ā¢ Jumps into loops.
38. Code Inspection
ā¢ Use of incorrect logical operators
ā or incorrect precedence among operators.
ā¢ Improper modification of loop variables.
ā¢ Comparison of equality of floating point values,
etc.
ā¢ Also during code inspection,
ā adherence to coding standards is checked.
40. Psychology of Testing
ā¢ Test cases are designed to detect errors but does
not guarantee that all possible error get
detected.
ā¢ There is no standard method for selecting test
cases.
ā¢ Selection of test cases is an art.
ā¢ One of the reason why organization is not
selecting developer as a tester is depend upon
human psychology.
41. Project Testing Flow
ā¢ Unit Testing
ā¢ Integration Testing
ā¢ System Testing
ā¢ User Acceptance Testing
43. Testing Process
ā¢ Testing is carried out at the till later stage of
s/w development.
ā¢ Testing is also necessary even after release of
product.
ā¢ Therefore testing is considered as the
COSTLIEST activity in s/w devp. & should be
done efficiently.
44. Testing Principles
ā¢ All tests should be traceable to customer requirements.
ā¢ Tests should be planned long before testing begins.
ā¢ The Pareto principle applies to software testing.
ā¢ Testing should begin āin the smallā and progress toward
testing āin the large.ā
ā¢ Complete testing is not possible.
ā¢ To be most effective, testing should be conducted by an
independent third party.
45. Software Testability
ā¢ S/w testability is simply how easily system or program or product
can be tested.
ā¢ Testing must exhibit set of characteristics that achieve the goal of
finding errors with a minimum of effort.
Characteristics of s/w Testability:
ā¢ Operability - āThe better it works, the more efficiently it can be
testedā
ā Relatively few bugs will block the execution of tests.
ā Allowing testing progress without fits and starts.
46. ā¢ Observability - "What you see is what you test.ā
ā Distinct output is generated for each input.
ā System states and variables are visible or queriable during
execution.
ā Incorrect output is easily identified.
ā Internal errors are automatically detected & reported.
ā Source code is accessible.
ā¢ Controllability - "The better we can control the software, the
more the testing can be automated and optimized.ā
ā Software and hardware states and variables can be controlled
directly by the test engineer.
ā Tests can be conveniently specified, automated, and
reproduced.
ā¢ Decomposability - By controlling the scope of testing, we can
more quickly isolate problems and perform smarter retesting.
ā Independent modules can be tested independently.
47. ā¢ Simplicity - The less there is to test, the more quickly we can test it."
ā Functional simplicity (e.g., the feature set is the minimum
necessary to meet requirements).
ā Structural simplicity (e.g., architecture is modularized to limit the
propagation of faults).
ā Code simplicity (e.g., a coding standard is adopted for ease of
inspection and maintenance).
ā¢ Stability - "The fewer the changes, the fewer the disruptions to
testing."
ā Changes to the software are infrequent.
ā Changes to the software are controlled.
ā Changes to the software do not invalidate existing tests.
ā¢ Understandability ā "The more information we have, the smarter
we will test."
ā Dependencies between internal, external, and shared
components are well understood.
ā Changes to the design are communicated to testers.
ā Technical documentation is instantly accessible, well organized,
specific and detailed, and accurate.
48. Test Case Design
Specifies
ā¢ how to carry out testing process?
ā¢ Which unit need to be tested?
ā¢ What are the tools that can used for testing?
49. Test Case Specification
Test
Case ID
Test
Case
Name
Test Case
Description
Test
Steps
Status
(pass/fail)
Test
Priority
Defect
Severity
50. Taxonomy of Testing
ā¢ There are two general approaches of testing
1.Black Box Testing
2.White Box Testing
51. Black-box testing
ā¢ Functional testing approach focuses on
application externals.
ā¢ We can call it as Requirements-based or
Specifications-based.
ā¢ Characteristics:
Functionality
Requirements, use, standards Correctness
Does system meet business requirements
54. Black box testing
ā¢ Also called behavioral testing, focuses on the functional requirements
of the software.
ā¢ It enables the software engineer to derive sets of input conditions that
will fully exercise all functional requirements for a program.
ā¢ Black-box testing is not an alternative to white-box techniques but it is
complementary approach.
ā¢ Black-box testing attempts to find errors in the following categories:
ā Incorrect or missing functions,
ā Interface errors,
ā Errors in data structures or external data base access.
ā Behavior or performance errors,
ā Initialization and termination errors.
55. ā¢ Black-box testing purposely ignored control structure, attention is
focused on the information domain. Tests are designed to answer the
following questions:
ā How is functional validity tested?
ā How is system behavior and performance tested?
ā What classes of input will make good test cases?
ā¢ By applying black-box techniques, we derive a set of test cases that
satisfy the following criteria
ā Test cases that reduce the number of additional test cases that
must be designed to achieve reasonable testing (i.e minimize effort
and time)
ā Test cases that tell us something about the presence or absence of
classes of errors
ā¢ Black box testing methods
ā Graph-Based Testing Methods
ā Equivalence partitioning
ā Boundary value analysis (BVA)
ā Orthogonal Array Testing
56. White Box Testing
ā¢ Structural testing approach focuses on
application internals. We can call it as
Program-based
ā¢ Characteristics:
1. Implementation
2. Do modules meet functional and design specifications?
3. Do program structures meet functional and design
specifications?
4. How does the program work
57. White box testing
ā¢ White-box testing of software is predicated on close examination
of procedural detail.
ā¢ Logical paths through the software are tested by providing test
cases that exercise specific sets of conditions and/or loops.
ā¢ The "status of the program" may be examined at various points.
ā¢ White-box testing, sometimes called glass-box testing, is a test
case design method that uses the control structure of the
procedural design to derive test cases.
58. White box testing
Using this method, SE can derive test cases that
1. Guarantee that all independent paths within a module have
been exercised at least once
2. Exercise all logical decisions on their true and false sides,
3. Execute all loops at their boundaries and within their
operational bounds
4. Exercise internal data structures to ensure their validity.
59. White Box Testing
ā¢ Type of Test during White Box Approach:
1. Unit Testing
2. Integration Testing
60.
61. Validation and Verification
ā¢ V & V
ā¢ Validation
ā Are we building the right product?
ā¢ Verification
ā Are we building the product right?
ā Testing
ā Inspection
ā Static analysis
62. Verification and Validation
Testing is one element of a broader topic that is often referred to as verification
and validation (V&V).
ā¢ Verification refers to the set of activities that ensure
that software correctly implements a specific
function.
ā¢ Validation refers to a different set of activities that
ensure that the software that has been built is
traceable to customer requirements.
State another way:
ā Verification: "Are we building the product right?"
ā Validation: "Are we building the right product?ā
The definition of V&V encompasses many of the activities that are similar to
software quality assurance (SQA).
63. Test Cases
ā¢ Key elements of a test plan
ā¢ May include scripts, data, checklists
ā¢ May map to a Requirements Coverage Matrix
ā¢ A traceability tool
69. Regression Testing
ā¢ Each time a new module is added as part of integration testing
ā New data flow paths are established
ā New I/O may occur
ā New control logic is invoked
ā¢ Due to these changes, may cause problems with functions that previously
worked flawlessly.
ā¢ Regression testing is the re-execution of some subset of
tests that have already been conducted to ensure that
changes have not propagated unintended side effects.
ā¢ Whenever software is corrected, some aspect of the software
configuration (the program, its documentation, or the data that support it)
is changed.
70. Smoke Testing
ā¢ Smoke testing is an integration testing approach that is
commonly used when āshrink wrappedā software products are
being developed.
ā¢ It is designed as a pacing mechanism for time-critical projects,
allowing the software team to assess its project on a frequent
basis.
Smoke testing approach activities
ā¢ Software components that have been translated into code are integrated into
a ābuild.ā
ā A build includes all data files, libraries, reusable modules, and engineered
components that are required to implement one or more product
functions.
ā¢ A series of tests is designed to expose errors that will keep the build from
properly performing its function.
ā The intent should be to uncover āshow stopperā errors that have the
highest likelihood of throwing the software project behind schedule.
ā¢ The build is integrated with other builds and the entire product is smoke
71. ā¢ Integration risk is minimized.
ā Smoke tests are conducted daily, incompatibilities and other show-
stopper errors are uncovered early
ā¢ The quality of the end-product is improved.
ā Smoke testing is likely to uncover both functional errors and
architectural and component-level design defects. At the end, better
product quality will result.
ā¢ Error diagnosis and correction are simplified.
ā Software that has just been added to the build(s) is a probable cause of
a newly discovered error.
ā¢ Progress is easier to assess.
ā Frequent tests give both managers and practitioners a realistic
assessment of integration testing progress.
Smoke Testing benefits
72. Validation Testing
ā¢ Validation testing succeeds when software functions in a
manner that can be reasonably expected by the customer.
ā¢ Like all other testing steps, validation tries to uncover errors,
but the focus is at the requirements levelā on things that will
be immediately apparent to the end-user.
ā¢ Reasonable expectations are defined in the Software
Requirements Specificationā a document that describes all
user-visible attributes of the software.
ā¢ Validation testing comprises of
ā Validation Test criteria
ā Configuration review
ā Alpha & Beta Testing
73. Alpha and Beta Testing
ā¢ When custom software is built for one customer, a series of
acceptance tests are conducted to enable the customer to
validate all requirements.
ā¢ Conducted by the end-user rather than software engineers,
an acceptance test can range from an informal "test drive" to
a planned and systematically executed series of tests.
ā¢ Most software product builders use a process called alpha
and beta testing to uncover errors that only the end-user
seems able to find.
74. Alpha testing
ā¢ The alpha test is conducted at the developer's
site by a customer.
ā¢ The software is used in a natural setting with
the developer "looking over the shoulder" of
the user and recording errors and usage
problems.
ā¢ Alpha tests are conducted in a controlled
environment.
75. Beta testing
ā¢ The beta test is conducted at one or more customer
sites by the end-user of the software.
ā¢ beta test is a "live" application of the software in an
environment that cannot be controlled by the
developer.
ā¢ The customer records all problems (real or imagined)
that are encountered during beta testing and reports
these to the developer at regular intervals.
ā¢ As a result of problems reported during beta tests,
software engineers make modifications and then
prepare for release of the software product to the
entire customer base.
76. System Testing
ā¢ System testing is actually a series of different tests
whose primary purpose is to fully exercise the
computer-based system.
ā¢ Although each test has a different purpose, all work to
verify that system elements have been properly
integrated and perform allocated functions.
ā¢ Types of system tests are:
ā Recovery Testing
ā Security Testing
ā Stress Testing
ā Performance Testing
77. Recovery Testing
ā¢ Recovery testing is a system test that forces the software to
fail in a variety of ways and verifies that recovery is properly
performed.
ā¢ If recovery is automatic (performed by the system itself),
reinitialization, checkpointing mechanisms, data recovery,
and restart are evaluated for correctness.
ā¢ If recovery requires human intervention, that is mean-time-
to-repair (MTTR) is evaluated to determine whether it is
within acceptable limits.
78. Security Testing
ā¢ Security testing attempts to verify that protection mechanisms built
into a system will, in fact, protect it from improper break through .
ā¢ During security testing, the tester plays the role(s) of the individual
who desires to break through the system.
ā¢ Given enough time and resources, good security testing will
ultimately penetrate a system.
ā¢ The role of the system designer is to make penetration cost more
than the value of the information that will be obtained.
ā¢ The tester may attempt to acquire passwords through externally,
may attack the system with custom software designed to breakdown
any defenses that have been constructed; may browse through
insecure data; may purposely cause system errors.
79. Stress Testing
ā¢ Stress testing executes a system in a manner that demands resources in
abnormal quantity, frequency, or volume.
For example,
1. special tests may be designed that generate ten interrupts per second
2. Input data rates may be increased by an order of magnitude to determine
how input functions will respond
3. test cases that require maximum memory or other resources are executed
4. test cases that may cause excessive hunting for disk-resident data are
created
ā¢ A variation of stress testing is a technique called sensitivity testing
80. Performance Testing
ā¢ Performance testing occurs throughout all steps in the testing process.
ā¢ Even at the unit level, the performance of an individual module may
be assessed as white-box tests are conducted.
ā¢ Performance tests are often coupled with stress testing and usually
require both hardware and software instrumentation
ā¢ It is often necessary to measure resource utilization (e.g., processor
cycles).
81. THE ART OF DEBUGGING
ā¢ Debugging is the process that results in the
removal of the error.
ā¢ Although debugging can and should be an
orderly process, it is still very much an art.
ā¢ Debugging is not testing but always occurs as
a consequence of testing.