This document discusses code coverage, which quantifies how much application code is exercised by testing activities. It outlines the benefits of code coverage, such as providing an objective measure of test coverage and identifying untested areas to improve testing. The document also covers code coverage terminology like instrumentation, merge, and coverage types. Finally, it discusses evaluating code coverage tools and deploying the tools as part of the development workflow.
Code coverage is a measure of how much of the source code of a program is tested by a test suite. It helps ensure quality by enabling early detection of flaws. Common types of code coverage include statement, function, path, condition, and branch coverage. Tools like Cobertura, Clover, and Emma can help measure and analyze code coverage. Aim for 70-80% test coverage but 100% is not always cost effective or possible. Code coverage should be implemented from the start of development.
The document provides an overview of code coverage as a white-box testing technique. It discusses various coverage metrics like statement coverage, decision coverage, conditional coverage, and path coverage. It also covers code coverage implementation in real tools and general recommendations around code coverage goals and testing practices. The presentation includes demos of different coverage metrics and aims to help readers learn about coverage theory, metrics, and tools to familiarize them with code coverage.
The document discusses code coverage, including coverage theory, metrics, and implementation in tools. It defines various coverage metrics like statement coverage, decision coverage, and path coverage. It recommends starting with simple metrics like statement coverage and moving to more advanced ones like branch coverage. It also provides recommendations for code coverage goals and implementation in tools.
Unit Testing Concepts and Best PracticesDerek Smith
Unit testing involves writing code to test individual units or components of an application to ensure they perform as expected. The document discusses best practices for unit testing including writing atomic, consistent, self-descriptive tests with clear assertions. Tests should be separated by business module and type and not include conditional logic, loops, or exception handling. Production code should be isolated from test code. The goal of unit testing is to validate that code meets specifications and prevents regressions over time.
This document discusses code coverage tools and JaCoCo in particular. It summarizes that JaCoCo is an open-source Java code coverage library that collects execution data for Java applications and libraries. JaCoCo can collect data both offline from Java byte code or online by instrumenting Java applications dynamically. The document compares JaCoCo to other code coverage tools and outlines JaCoCo's integrations, metrics, and features to help developers test code coverage.
The document discusses test automation process and framework. It provides details on what test automation means, benefits of automation, guidelines for identifying test cases to automate, challenges in automation, and components of an automation framework like data tables, libraries, object repositories, scripts, and results.
This document discusses test automation approaches and best practices. It defines test automation as using software to perform test activities like execution and checking results. The document outlines how test automation fits into the software development lifecycle and notes that reducing manual testing and redundant tasks is key to success. It also discusses factors to consider for test automation, types of tests that can be automated, and technologies used for test automation like object-based and image-based recognition.
Code coverage is a measure of how much of the source code of a program is tested by a test suite. It helps ensure quality by enabling early detection of flaws. Common types of code coverage include statement, function, path, condition, and branch coverage. Tools like Cobertura, Clover, and Emma can help measure and analyze code coverage. Aim for 70-80% test coverage but 100% is not always cost effective or possible. Code coverage should be implemented from the start of development.
The document provides an overview of code coverage as a white-box testing technique. It discusses various coverage metrics like statement coverage, decision coverage, conditional coverage, and path coverage. It also covers code coverage implementation in real tools and general recommendations around code coverage goals and testing practices. The presentation includes demos of different coverage metrics and aims to help readers learn about coverage theory, metrics, and tools to familiarize them with code coverage.
The document discusses code coverage, including coverage theory, metrics, and implementation in tools. It defines various coverage metrics like statement coverage, decision coverage, and path coverage. It recommends starting with simple metrics like statement coverage and moving to more advanced ones like branch coverage. It also provides recommendations for code coverage goals and implementation in tools.
Unit Testing Concepts and Best PracticesDerek Smith
Unit testing involves writing code to test individual units or components of an application to ensure they perform as expected. The document discusses best practices for unit testing including writing atomic, consistent, self-descriptive tests with clear assertions. Tests should be separated by business module and type and not include conditional logic, loops, or exception handling. Production code should be isolated from test code. The goal of unit testing is to validate that code meets specifications and prevents regressions over time.
This document discusses code coverage tools and JaCoCo in particular. It summarizes that JaCoCo is an open-source Java code coverage library that collects execution data for Java applications and libraries. JaCoCo can collect data both offline from Java byte code or online by instrumenting Java applications dynamically. The document compares JaCoCo to other code coverage tools and outlines JaCoCo's integrations, metrics, and features to help developers test code coverage.
The document discusses test automation process and framework. It provides details on what test automation means, benefits of automation, guidelines for identifying test cases to automate, challenges in automation, and components of an automation framework like data tables, libraries, object repositories, scripts, and results.
This document discusses test automation approaches and best practices. It defines test automation as using software to perform test activities like execution and checking results. The document outlines how test automation fits into the software development lifecycle and notes that reducing manual testing and redundant tasks is key to success. It also discusses factors to consider for test automation, types of tests that can be automated, and technologies used for test automation like object-based and image-based recognition.
This document discusses unit and integration testing. It begins by explaining the benefits of testing, such as reducing bugs and allowing safe refactoring. It then describes different types of tests like unit, integration, and database tests. The document focuses on unit testing, explaining how to write and organize unit tests using PHPUnit. It provides examples of test assertions and annotations. It also covers mocking and stubbing dependencies. Finally, it discusses challenges like testing code that relies on external components and provides strategies for database testing.
This document provides an overview of unit testing. It defines a unit as a software component containing routines and variables. Unit testing involves testing individual units in isolation to find defects. The benefits of unit testing include refactoring code easily and making integration testing simpler. Various test types are covered, including functional, non-functional, and structure-based testing. Static and white box testing techniques like statement coverage and branch coverage are also discussed. The document concludes with guidelines for effective unit testing.
This document provides an overview of test-driven development (TDD). TDD involves writing tests before writing code to ensure new functionality works as intended. Key principles of TDD include writing failing tests first, then code to pass the tests, and refactoring code while maintaining all tests. TDD results in higher quality, flexible, readable and maintainable code. It also helps improve both internal code quality and external functionality through a well-designed development process focused on automated testing.
Unit testing is a method to test individual units of source code to determine if they are fit for use. A unit is the smallest testable part of an application. Unit tests are created by programmers during development. Test-driven development uses tests to drive the design by writing a failing test first, then code to pass the test, and refactoring the code. Unit tests should be isolated, repeatable, fast, self-documenting, and use techniques like dependency injection and mocking dependencies. Benefits of unit testing include instant feedback, promoting modularity, acting as a safety net for changes, and providing documentation.
Test Automation Best Practices (with SOA test approach)Leonard Fingerman
Today we hear a lot of buzz about the latest & greatest test automation tools like Selenium, Rational Functional Tester or HP LoadRunner but to make your test automation effort successful it might take more than just having the right tool. This presentation will try to uncover major pitfalls typically involved with test automation efforts. It will provide guidance on successful strategy as well as differences among third-generation frameworks like keyword-driven, data-driven and hybrid. It will also cover various aspects of SOA test automation
This document provides an overview of unit testing and isolation frameworks. It defines key concepts like units, unit tests, stubs, mocks and isolation frameworks. It explains that the goal of unit tests is to test individual units of code in isolation by replacing dependencies with stubs or mocks. It also discusses different isolation frameworks like Rhino Mocks and Moq that make it easier to dynamically create stubs and mocks without writing implementation code. The document covers different styles of isolation like record-and-replay and arrange-act-assert. It emphasizes best practices like having one mock per test and using stubs for other dependencies being tested.
Anatomy of a Continuous Integration and Delivery (CICD) PipelineRobert McDermott
This presentation covers the anatomy of a production CICD pipeline that is used to develop and deploy the cancer research application Oncoscape (https://oncoscape.sttrcancer.org)
Unit testing involves testing individual units or components of code to ensure they work as intended. It focuses on testing functional correctness, error handling, and input/output values. The main benefits are faster debugging, easier integration testing, and living documentation. Guidelines for effective unit testing include writing automated, independent, focused tests that cover boundaries and are easy to run and maintain.
powerpoint template for testing trainingJohn Roddy
This document provides an overview of software testing concepts. It defines software testing, discusses the testing process, and covers related terminology. The key points are:
- Software testing is the process of executing a program to evaluate its quality and identify errors. It involves designing and running tests to verify requirements are met.
- The testing process includes planning, specification, execution, recording results, and checking for completion. Regression testing is also important to check for unintended changes.
- Defining expected results is crucial, as it allows testers to properly evaluate actual outputs. Good communication and independence from development are also important aspects of testing.
The document discusses software testing, outlining key achievements in the field, dreams for the future of testing, and ongoing challenges. Some of the achievements mentioned include establishing testing as an essential software engineering activity, developing test process models, and advancing testing techniques for object-oriented and component-based systems. The dreams include developing a universal test theory, enabling fully automated testing, and maximizing the efficacy and cost-effectiveness of testing. Current challenges pertain to testing modern complex systems and evolving software.
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.
Today we need everything reliable and accelerated, so to attain prompt results we are using varied automation testing tools. An automation tool is a piece of software that is run by little human interaction. Different testing tools are used for automation/manual testing, unit testing, performance, web, mobile, etc., more to that we have some open source testing tools as well.
This is my complete introductory course for Software Test Automation.If you need full training that includes different automation tools (Selenium, J-Meter, Burp, SOAP UI etc), feel free to contact me by email (amraldo@hotmail.com) or by mobile (+201223600207).
We know that Code Reviews are a Good Thing. We probably have our own personal lists of things we look for in the code we review, while also fearing what others might say about our code. How to we ensure that code reviews are actually benefiting the team, and the application? How do we decide who does the reviews? What does "done" look like?
In this talk, Trisha will identify some best practices to follow. She'll talk about what's really important in a code review, and set out some guidelines to follow in order to maximise the value of the code review and minimise the pain.
This document discusses automation testing. It begins by defining automation testing and listing its benefits, which include saving time and money, improving accuracy, and increasing test coverage. It then covers levels of automation testing, frameworks, approaches like record and playback, modular scripting, and keyword-driven testing. The document also discusses the automation testing lifecycle, how to choose a testing tool, types of tools, when to automate and who should automate, supporting practices, and skills needed for automation testing.
This document provides an overview and agenda for a presentation on automation testing using IBM Rational Functional Tester. It discusses what automation testing is, why it is useful, and when it should be implemented. It also addresses common myths about automation testing and provides tips for successful automation. Finally, it covers features of IBM Rational Functional Tester, including how to set up a test environment and record scripts to automate testing.
This document provides an introduction to automation testing. It discusses the need for automation testing to improve speed, reliability and test coverage. The document outlines when tests should be automated such as for regression testing or data-driven testing. It also discusses automation tool options and the types of tests that can be automated, including functional and non-functional tests. Finally, it addresses the advantages of automation including time savings and repeatability, as well as challenges such as maintenance efforts and tool limitations.
Sonar is a software quality management platform that enables developers to access and track code analysis data ranging from styling errors and potential bugs to code defects, duplications, lack of test coverage, and excess complexity. It supports over 20 programming languages. Some key features include over 600 coding rules, standard software metrics, the ability to drill down to source code details, a time machine feature to analyze technical debt and code smells over time, security measures, an extensible plugin system, and integrations with tools like Jenkins. Sonar also covers 7 axes of code quality and has an architecture that allows for analysis of code in a continuous integration workflow.
Term Paper - Quality Assurance in Software DevelopmentSharad Srivastava
This document provides an overview of software quality assurance. It discusses the evolution of SQA from an initial focus on "code and ship" in the 1960s-1980s to today's emphasis on SQA processes. Key concepts covered include quality, quality control, quality assurance, and the cost of quality. Elements of SQA like activities and models are described. Leading organizations' SQA practices are examined through case studies. The document aims to explain the importance of SQA for software development organizations.
Quality Assurance and its Importance in Software Industry by Aman ShuklaAbhishekKumar773294
Quality assurance is important for software companies to eliminate bugs and reduce costs. Some of the most expensive software errors in history include a $169 million error for the Mariner 1 spacecraft in 1962 due to a hyphen, and Mt. Gox losing $850,000 in bitcoins in 2014 due to a hacking incident. Companies implement quality assurance practices like maintaining a dedicated security testing team, integrating testing into development using test-driven development, and ensuring all tests are part of continuous integration/delivery pipelines. Testing frameworks like behavior-driven development, test-driven development, and acceptance test-driven development provide better testing approaches and efficiency. Quality assurance is necessary to deliver bug-free applications and satisfy customers.
This document discusses unit and integration testing. It begins by explaining the benefits of testing, such as reducing bugs and allowing safe refactoring. It then describes different types of tests like unit, integration, and database tests. The document focuses on unit testing, explaining how to write and organize unit tests using PHPUnit. It provides examples of test assertions and annotations. It also covers mocking and stubbing dependencies. Finally, it discusses challenges like testing code that relies on external components and provides strategies for database testing.
This document provides an overview of unit testing. It defines a unit as a software component containing routines and variables. Unit testing involves testing individual units in isolation to find defects. The benefits of unit testing include refactoring code easily and making integration testing simpler. Various test types are covered, including functional, non-functional, and structure-based testing. Static and white box testing techniques like statement coverage and branch coverage are also discussed. The document concludes with guidelines for effective unit testing.
This document provides an overview of test-driven development (TDD). TDD involves writing tests before writing code to ensure new functionality works as intended. Key principles of TDD include writing failing tests first, then code to pass the tests, and refactoring code while maintaining all tests. TDD results in higher quality, flexible, readable and maintainable code. It also helps improve both internal code quality and external functionality through a well-designed development process focused on automated testing.
Unit testing is a method to test individual units of source code to determine if they are fit for use. A unit is the smallest testable part of an application. Unit tests are created by programmers during development. Test-driven development uses tests to drive the design by writing a failing test first, then code to pass the test, and refactoring the code. Unit tests should be isolated, repeatable, fast, self-documenting, and use techniques like dependency injection and mocking dependencies. Benefits of unit testing include instant feedback, promoting modularity, acting as a safety net for changes, and providing documentation.
Test Automation Best Practices (with SOA test approach)Leonard Fingerman
Today we hear a lot of buzz about the latest & greatest test automation tools like Selenium, Rational Functional Tester or HP LoadRunner but to make your test automation effort successful it might take more than just having the right tool. This presentation will try to uncover major pitfalls typically involved with test automation efforts. It will provide guidance on successful strategy as well as differences among third-generation frameworks like keyword-driven, data-driven and hybrid. It will also cover various aspects of SOA test automation
This document provides an overview of unit testing and isolation frameworks. It defines key concepts like units, unit tests, stubs, mocks and isolation frameworks. It explains that the goal of unit tests is to test individual units of code in isolation by replacing dependencies with stubs or mocks. It also discusses different isolation frameworks like Rhino Mocks and Moq that make it easier to dynamically create stubs and mocks without writing implementation code. The document covers different styles of isolation like record-and-replay and arrange-act-assert. It emphasizes best practices like having one mock per test and using stubs for other dependencies being tested.
Anatomy of a Continuous Integration and Delivery (CICD) PipelineRobert McDermott
This presentation covers the anatomy of a production CICD pipeline that is used to develop and deploy the cancer research application Oncoscape (https://oncoscape.sttrcancer.org)
Unit testing involves testing individual units or components of code to ensure they work as intended. It focuses on testing functional correctness, error handling, and input/output values. The main benefits are faster debugging, easier integration testing, and living documentation. Guidelines for effective unit testing include writing automated, independent, focused tests that cover boundaries and are easy to run and maintain.
powerpoint template for testing trainingJohn Roddy
This document provides an overview of software testing concepts. It defines software testing, discusses the testing process, and covers related terminology. The key points are:
- Software testing is the process of executing a program to evaluate its quality and identify errors. It involves designing and running tests to verify requirements are met.
- The testing process includes planning, specification, execution, recording results, and checking for completion. Regression testing is also important to check for unintended changes.
- Defining expected results is crucial, as it allows testers to properly evaluate actual outputs. Good communication and independence from development are also important aspects of testing.
The document discusses software testing, outlining key achievements in the field, dreams for the future of testing, and ongoing challenges. Some of the achievements mentioned include establishing testing as an essential software engineering activity, developing test process models, and advancing testing techniques for object-oriented and component-based systems. The dreams include developing a universal test theory, enabling fully automated testing, and maximizing the efficacy and cost-effectiveness of testing. Current challenges pertain to testing modern complex systems and evolving software.
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.
Today we need everything reliable and accelerated, so to attain prompt results we are using varied automation testing tools. An automation tool is a piece of software that is run by little human interaction. Different testing tools are used for automation/manual testing, unit testing, performance, web, mobile, etc., more to that we have some open source testing tools as well.
This is my complete introductory course for Software Test Automation.If you need full training that includes different automation tools (Selenium, J-Meter, Burp, SOAP UI etc), feel free to contact me by email (amraldo@hotmail.com) or by mobile (+201223600207).
We know that Code Reviews are a Good Thing. We probably have our own personal lists of things we look for in the code we review, while also fearing what others might say about our code. How to we ensure that code reviews are actually benefiting the team, and the application? How do we decide who does the reviews? What does "done" look like?
In this talk, Trisha will identify some best practices to follow. She'll talk about what's really important in a code review, and set out some guidelines to follow in order to maximise the value of the code review and minimise the pain.
This document discusses automation testing. It begins by defining automation testing and listing its benefits, which include saving time and money, improving accuracy, and increasing test coverage. It then covers levels of automation testing, frameworks, approaches like record and playback, modular scripting, and keyword-driven testing. The document also discusses the automation testing lifecycle, how to choose a testing tool, types of tools, when to automate and who should automate, supporting practices, and skills needed for automation testing.
This document provides an overview and agenda for a presentation on automation testing using IBM Rational Functional Tester. It discusses what automation testing is, why it is useful, and when it should be implemented. It also addresses common myths about automation testing and provides tips for successful automation. Finally, it covers features of IBM Rational Functional Tester, including how to set up a test environment and record scripts to automate testing.
This document provides an introduction to automation testing. It discusses the need for automation testing to improve speed, reliability and test coverage. The document outlines when tests should be automated such as for regression testing or data-driven testing. It also discusses automation tool options and the types of tests that can be automated, including functional and non-functional tests. Finally, it addresses the advantages of automation including time savings and repeatability, as well as challenges such as maintenance efforts and tool limitations.
Sonar is a software quality management platform that enables developers to access and track code analysis data ranging from styling errors and potential bugs to code defects, duplications, lack of test coverage, and excess complexity. It supports over 20 programming languages. Some key features include over 600 coding rules, standard software metrics, the ability to drill down to source code details, a time machine feature to analyze technical debt and code smells over time, security measures, an extensible plugin system, and integrations with tools like Jenkins. Sonar also covers 7 axes of code quality and has an architecture that allows for analysis of code in a continuous integration workflow.
Term Paper - Quality Assurance in Software DevelopmentSharad Srivastava
This document provides an overview of software quality assurance. It discusses the evolution of SQA from an initial focus on "code and ship" in the 1960s-1980s to today's emphasis on SQA processes. Key concepts covered include quality, quality control, quality assurance, and the cost of quality. Elements of SQA like activities and models are described. Leading organizations' SQA practices are examined through case studies. The document aims to explain the importance of SQA for software development organizations.
Quality Assurance and its Importance in Software Industry by Aman ShuklaAbhishekKumar773294
Quality assurance is important for software companies to eliminate bugs and reduce costs. Some of the most expensive software errors in history include a $169 million error for the Mariner 1 spacecraft in 1962 due to a hyphen, and Mt. Gox losing $850,000 in bitcoins in 2014 due to a hacking incident. Companies implement quality assurance practices like maintaining a dedicated security testing team, integrating testing into development using test-driven development, and ensuring all tests are part of continuous integration/delivery pipelines. Testing frameworks like behavior-driven development, test-driven development, and acceptance test-driven development provide better testing approaches and efficiency. Quality assurance is necessary to deliver bug-free applications and satisfy customers.
This document provides coding standards and conventions for Java programming. It covers topics such as program structure, file organization, indentation, comments, declarations, statements, naming conventions, and programming practices. The goal is to improve code readability, understandability, and maintainability. Projects may customize the standards as needed based on customer requirements.
This document discusses quality management in software engineering. It covers topics like quality assurance, standards, design, control, and software measurements. The key points are:
1) Quality assurance aims to create standards that lead to high quality software. It involves planning quality standards and processes, and controlling development to ensure standards are followed.
2) Standards include both product standards (documents, code) and process standards (specification, design, validation). They are based on past mistakes and ensure continuity.
3) Quality design defines quality attributes and goals for a project. It considers attributes like security, reliability, and usability.
4) Quality control monitors the development process through reviews and automated testing to check if standards are
This document provides technical security criteria and evaluation methodologies for assessing the security of computer systems. It defines four divisions of security protection for systems - Minimal, Discretionary, Mandatory, and Verified. Each division contains classes that represent increasing levels of security. The purpose is to provide a standard for evaluating how much trust can be placed in a system's security and to provide guidance to manufacturers for building secure products. It also aims to provide a basis for specifying security requirements in acquisition. The criteria focus on security features and how to determine if they are present and functioning as intended. While intended to be application independent, the specific requirements may need interpretation for certain system types.
Welcome to International Journal of Engineering Research and Development (IJERD)IJERD Editor
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This document presents an embedded C coding standard with rules focused on reducing bugs and improving code readability and portability. It covers general rules for code style, comments, whitespace, modules, data types, procedures, variables, and expressions. Key points include:
- Code must comply with C99 and use fixed-width integer types. C++ keywords and features are prohibited.
- Lines are limited to 80 characters. Braces always surround blocks and are placed consistently. Parentheses are used for clarity.
- Common abbreviations are allowed but others require approval. Casts require explanatory comments due to risks.
- Comments use acceptable formats and are placed for maximum usefulness. Whitespace and indentation are standardized.
Deployment of Debug and Trace for features in RISC-V CoreIRJET Journal
1) The document discusses verification and debugging techniques for RISC-V cores, specifically using instruction and data tracing.
2) It describes the phases of verification including test planning, testbench building, test writing, code coverage analysis, and debugging.
3) Debugging with tracing allows reconstructing the program flow by decoding traced instruction and data accesses and comparing them to the simulation flow to check for errors.
This document is a draft version 3.4 of the Standard for Software Component Testing produced by the British Computer Society Specialist Interest Group in Software Testing (BCS SIGIST). The standard provides guidelines for software component testing including defining a testing process, recommended test case design techniques, and test measurement techniques. It aims to enable the measurement and comparison of testing performed on software components to improve testing quality. The document describes the scope and objectives of the standard, as well as the testing process it recommends including test planning, specification, execution, recording, and completion checking activities. It also provides details on various test case design techniques such as equivalence partitioning, boundary value analysis, state transition testing, and others. Test measurement techniques are also defined to
An Approach To Software Development Life CycleBettyBaker
The document describes the waterfall software development life cycle (SDLC) approach and a modified implementation of it. The waterfall approach consists of five phases: requirements, design, coding, testing, and maintenance. The modified approach combines the requirements and design phases into a systems engineering phase. It also implements coding in mini code locks with testing after each lock rather than once at the end. Both aim to systematically structure the development process.
This webinar was co-hosted by Testery.io and Curiosity Software on 10th November 2022. Watch the on demand recording here: https://www.curiositysoftware.ie/hitting-the-right-test-coverage-ci-cd-webinar-testery
Testing today too often faces a choice between introducing bottlenecks to software delivery, or allowing an unacceptable level of negative risk. A lack of traceability between tests, changing code, user stories and data leaves testers no way of knowing reliably which tests to run, when. They further have no time to create the tests required for optimal in-sprint coverage, instead being held back by slow and manual test creation. Pipeline configuration and environmental constraints further force testing behind parallelised development, rendering true CI/CD an unobtainable ideal for many organisations.
This webinar will set out how you can automatically identify, generate, and execute optimized tests at the speed of CI/CD. Curiosity Software’s CTO, James Walker, and Testery CEO Chris Harbert will discuss how automated test generation and test orchestration integrate into CI/CD pipelines, running the right blend of tests to de-risk continuous deployments. A live demo will then show you how you can execute these targeted tests on-the-fly, setting out how:
1. Model-based test generation dynamically creates the smallest set of tests needed to satisfy different risk profiles on demand.
2. Automated test orchestration triggers the right blend of tests to de-risk deployments, executed across environments and ranging from smoke tests to full regression.
3. Sequentially triggering tests from different repositories targets bugs across APIs, UIs, and back-end systems, delivering rigorously tested software at speed.
Watch the on demand webinar: https://www.curiositysoftware.ie/hitting-the-right-test-coverage-ci-cd-webinar-testery
This document contains a summary of Vamsi Kumar Paidi's career objective, qualifications, and experience. He has over 2.6 years of experience in VLSI design and ASIC verification. He is proficient with Verilog, SystemVerilog, UVM, and seeks a position as a VLSI Design and ASIC Verification Engineer. His experience includes projects verifying SATA 3.2 and APB 3.0 environments using UVM and developing test plans, testbenches, and debugging failures.
Sample Cloud Application Security and Operations Policy [release]LinkedIn
This document provides a sample cloud applications security and operations policy to guide organizations in developing security policies for cloud applications. It includes sections on authentication and administration, auditing, business continuity, data security, communication security, vendor governance, and brand reputation. For each section, it outlines baseline requirements and additional requirements for applications handling data at different security levels (1-3), based on the potential impact of unauthorized access. The goal is to balance security and usability by applying more stringent requirements to higher risk or sensitive data.
Cloud-native testing is a quality assurance procedure specifically designed for cloud-native applications. The latter are created based on standards and enhancements that could impact computing capacity with distributed systems, such as microservices engineering
This document provides an overview of security in the Java platform, covering topics like the Java language's security features, bytecode verification, the basic security architecture including security providers and file locations, cryptography, public key infrastructure (PKI), authentication, secure communication techniques, access control including permissions and policy, and built-in security providers. It describes the key principles of implementation independence, interoperability, and extensibility that the Java security APIs are designed around.
This document discusses formal coverage analysis (FCA) as a way to improve the coverage closure process for digital hardware designs. It presents the underlying concepts of FCA and details an implementation using Synopsys tools. The key points are:
1. FCA uses formal verification tools to automatically analyze coverage targets and determine if they are reachable or unreachable, saving significant engineering effort compared to manual analysis.
2. An FCA flow is demonstrated using Synopsys VCS for simulation, VC Static for formal verification, and Verdi for viewing results. VC Static proves whether targets are reachable/unreachable and generates an exclusion file of unreachable targets.
3. Practical considerations for implementing an FCA flow
End to End Cloud App Deployment SolutionZuhaib Ansari
This document outlines the need for an end-to-end framework for cloud applications. It proposes a framework that automates the process from code check out and builds to deployment. The key steps include running unit tests and code coverage analysis, deploying to dev environments, running integration tests, deploying to QA environments, acceptance testing, and final deployment. This framework provides advantages like continuous and automated delivery, coupling development and deployment, lower development to deployment time, decreased testing efforts, and cost savings.
This document provides an introduction and overview of the Communications-Electronics Security Group's (CESG) Infosec Assurance and Certification Services (IACS). IACS evaluates and certifies IT security products against standards like Common Criteria and ITSEC. The directory includes sections on certified products, protection profiles, the CESG Assisted Products Scheme, and TEMPEST approvals. It aims to guide developers, vendors, and users on choosing assured security products that meet clear standards.
This document provides guidelines for key performance indicators (KPI) for optimizing GSM networks. It lists important downlink parameters to measure such as RX_LEV, RX_QUAL, C/I, and timing advance. It describes how to calculate thresholds for design, prediction, and measurement of cell coverage based on these parameters. The thresholds take into account factors like handover margin, prediction error, and indoor/outdoor environments. The document aims to help technicians identify radio problems and optimize network performance through analysis of KPI measurements.
The document discusses software reliability engineering and its goals of balancing reliability, availability, delivery time, and cost based on customer needs. It addresses three key questions: 1) What is software practitioners' biggest problem in meeting conflicting customer demands? 2) How does software reliability engineering approach resolving this issue? 3) What has been the experience with software reliability engineering? The process involves defining the product and users, implementing operational profiles to efficiently test critical functions, and engineering the right level of reliability through failure analysis and testing to deliver the product on time and at an acceptable cost.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
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1. A Code Coverage Study
Code Coverage – Ensuring
Quality
Benefits . Tooling Evaluations . Case Study.
Strategy
Vijayan Reddy, Nithya Jayachandran
A Study
2. Table of Contents
January 2,
CODE COVERAGE – ENSURING QUALITY
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Table of Contents
1.0. Introduction .................................................................................................................................. 3
2.0. Why Code Coverage...................................................................................................................... 3
3.0. Benefits of Code Coverage............................................................................................................ 4
4.0. Code Coverage Terminologies ...................................................................................................... 4
4.1. Instrumentation ........................................................................................................................ 4
4.2. Merge ........................................................................................................................................ 4
4.3. Coverage Types ......................................................................................................................... 4
5.0. Code Coverage Analysis ................................................................................................................ 5
6.0. What Code Coverage is and is Not................................................................................................ 6
7.0. Tooling Infrastructure ................................................................................................................... 7
8.0. Tool Deployment .......................................................................................................................... 8
8.1.1. Cobertura : Integrated Instrumentation with the build process .......................................... 9
8.1.2. Cobertura : Deployment of Code Coverage instrumented application ................................ 9
8.1.3. Cobertura : Auto-Collection of Coverage data during testing ............................................ 10
8.1.4. Cobertura : Merge & Final Report Generation ................................................................... 10
8.2. NCover Deployment for .NET based Applications .................................................................. 12
9.0. Tools Evaluation .......................................................................................................................... 12
10.0. Some Popular Tools Reference ................................................................................................... 14
11.0. Appendix ..................................................................................................................................... 14
Table of Figures
Figure 1 : Global Summary Report .................................................................................................................................5
Figure 2 : Package Summary Report ..............................................................................................................................5
Figure 3 : Class Summary Report ...................................................................................................................................5
Figure 4 : Class Detail Report .........................................................................................................................................6
Figure 5 : Tool Deployment Workflow ...........................................................................................................................7
Figure 7 : Tool Evaluation Parameters .........................................................................................................................13
Figure 8 : Popular Tool References ..............................................................................................................................14
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1.0. Introduction
Code Coverage is an important measurement in Software Quality Engineering. While Software testing
ensures correctness of the applications, a metric is required to track the completeness and effectiveness
of the testing undertaken. Code Coverage helps achieve reliable quality through identifying untested
areas of the application.
It is still a challenge to identify the right Code Coverage tooling solution. The next challenge lies in
formulating the strategy for deployment of the tool and the process. This paper discusses Code
Coverage tooling solutions and deployment strategy for quick benefits.
2.0. Why Code Coverage
Software testing is a challenging function. The testers need to ensure complete functional and non-
functional correctness of the product. Considering the complex workflows and use cases of modern day
applications, the number of unique cases that the software can be used often run into millions, which is
not feasible to be covered under testing exercise. The testers thus need to
- While Planning Tests
o Ensure covering all workflows in terms of decision trees in the code
o Ensure covering all data values – by identifying patterns rather covering millions of
values
- While testing
o Ensuring the testing is completely exercising the whole application with planned and
exploratory tests.
At the end of testing, the decision to stop testing and release the product still remains subjective, based
on the presence or absence of bugs, inflow of new bugs, success rate of each test cycle, confidence
rating of the testers or users, etc. Whereas the definitive metric of quantifying how much of the
application was really tested, is missed.
Code Coverage is measured as quantification of application code exercised by the testing activities. Code
Coverage can be measured at various levels – in terms of programming language constructs – Packages,
Classes, Methods, Branches or in terms of physical artifacts - Folders, Files and Lines.
For Eg. A Line Coverage metric of 67% means the testing exercised 67% of all executable statements of
the application. A Code Coverage metric usually is accompanied by Code Coverage Analysis Report –
which helps identify the un-tested part of the application code, thereby giving the testers early inputs
for complete testing.
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3.0. Benefits of Code Coverage
• Objective Indicator of Test Coverage of application code
o Pointers to uncovered Packages / Classes / Methods / Branches
o Pointers to uncovered Folders / Files / Lines
o Drill down to untested part of source code and devise new tests
• Early Indicator for Testing Quality and Fixing it by adding new tests.
• Remove redundancy in testing
• Increased Confidence for Releases
4.0. Code Coverage Terminologies
4.1. Instrumentation
Instrumentation is the process to add code to the application to be able to output Code Coverage data.
Instrumentation can be done at Source Level or at Intermediate language level, and rarely at run-time as
information collection.
• Source Level Instrumentation: Prior to compilation, instrumentation code are inserted by the
code coverage tool to the application. This will be compiled into the application code.
• Object level Instrumentation: Post compilation of the Application, executable lines to collect
Coverage data are injected into the Object code.
4.2. Merge
Ability to run tests in batches, or in different environments, yet consolidate the overall coverage reports.
Most of good coverage tools support offline merge feature.
4.3. Coverage Types
• Folder Coverage
• File Coverage
• Lines Coverage
• Package Coverage
• Class Coverage
• Method Coverage
• Branch Coverage
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5.0. Code Coverage Analysis
Code Coverage Metrics in isolation are of limited help. But Code Coverage Report helps in analyzing the
uncovered areas of code.
The following report tracks the code Coverage at Package level for a Java based application – The tool
used below is Cobertura, and the Code Coverage report was on Cobertura’s testing.
Figure 1 : Global Summary Report
Attached below is Code Coverage report at Class Level. The following report lists all the classes in a
particular package, and tracks Branches & Lines Covered.
Figure 2 : Package Summary Report
Detailed Class level report – Header below: This report states the percentage of lines covered -79% (75
of 95 lines) and branches covered.
Figure 3 : Class Summary Report
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The following is an example of detailed code coverage report. The tool links to the source code – and
reports the untested lines. The color scheme used is GREEN for hit code and RED for unhit code. The
second column registers the number of times the code is visited.
The tester thus gets two sets of valuable inputs:
1) Track the un-tested code and create a new test case that exercises the code effectively.
2) Identify duplicate tests that visit the same part of code redundantly – thereby reducing the tests
without compromising quality and reducing the test cycle times.
Figure 4 : Class Detail Report
6.0. What Code Coverage is and is Not
- 100% Code Coverage Does Not say the product is bug free, it ensures product is 100% tested. If
the product was tested wrongly, Code Coverage can’t help.
- Code Coverage testing does not require any special test methods – On the instrumented build –
any testing that is carried out will generate coverage data. Regular using of the instrumented
application will generate coverage information as well.
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- Code Coverage is not about Whitebox testing. Code coverage is generated when you test the
application in Any way. To analyse the code, the review happens at Code Level. It is not
Whitebox testing.
- Code Coverage is not only through Unit Testing or Automated Testing.
- Code Coverage does not require extra testing efforts
- Code Coverage is not an end game activity, the earlier the better. It gives scope to improve tests
and cover more code, thereby ensuring higher quality.
- Code Coverage instrumented builds can’t be used for Performance Testing. It will add
performance overhead.
7.0. Tooling Infrastructure
For Code Coverage analysis the ideal infrastructure would be
- Integrated Instrumentation with the build process
- Deployment of Code Coverage instrumented application
- Auto-Collection of Coverage data during testing
- Merge & Final Report automation
Code Coverage reports can be generated on every test cycle if tests.
• Source / Object Level Instrumentation
Instrument • Generate Instrumented Object, Blank Coverage Files
• Deploy Instrumented Build & Coverage Files
Run Test • Perform Regular Testing on the Instrumented Build
• Merge Coverage Files if done in different sessions/environments
Report • Generate Analysis Reports
Figure 5 : Tool Deployment Workflow
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8.0. Tool Deployment
To illustrate the usage of Code Coverage tools, two popular tools that are rich in features, ease of
integration with existing build & test processes and documentation. These two tools are picked, one
each from a leading enterprise application development technology.
• Cobertura for Java/J2EE
• NCover for .NET
The following section is not meant as User manual for any tool, but for illustrating the ease of use and
integration with the build process, the usage is showcased. Please refer the product manuals for more
details.
8.1. Cobertura Deployment for Java based Applications
We will study the Code Coverage Deployment using Cobertura for Java/J2EE applications. Cobertura
offers excellent integration with build processes with Command line based executables, or with
Cobertura ANT tasks. We will discuss both briefly.
In order to use Cobertura’s command line executables, please add the Cobertura installation directory
to the System path.
The ANT Snippets are used from Cobertura’s online documentation for consistency
for reference.
In order to use Cobertura’s ANT tasks, we must do
- Add Cobertura.jar that ships with Cobertura tool, to the ANT’s lib directories – or
Add it in the class path reference variable in the build script.
Eg.
<property name="cobertura.dir" value="<<<SPECIFY COBERTURA INSTALL DIR>>>" />
<path id="cobertura.classpath">
<fileset dir="${cobertura.dir}">
<include name="cobertura.jar" />
<include name="lib/**/*.jar" />
</fileset>
</path>
To be a able to use the ANT Tasks, the following code snippet would help:
<taskdef classpathref="cobertura.classpath" resource="tasks.properties" />
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8.1.1. Cobertura : Integrated Instrumentation with the build process
ANT Usage:
Cobertura supports a task “Cobertura-instrument” for the instrumentation process. The parameters
supported are,
• datafile (Optional – defaults to ‘Cobertura.ser’ in the current directory. It is advised to set this
explicitly to a convenient place that can be used to store and be picked for reporting)
• maxmemory (Optional – Good to set larger JVM max memory, if the instrumentation covers
large number of classes)
• todir (Optional – To avoid the not instrumented classes being overwritten with the
instrumented classes, it is good practice to specify output directory)
Eg for cobertura-instrument usage
Please note that it is a good practice to delete the Instrumentation serialized file (“Cobertura.ser” in the
snippet below).
<delete file="cobertura.ser" />
<cobertura-instrument todir="${instrumented.dir}">
<ignore regex="org.apache.log4j.*" />
<fileset dir="${classes.dir}">
<include name="**/*.class" />
<exclude name="**/*Test.class" />
</fileset>
<fileset dir="${guiclasses.dir}">
<include name="**/*.class" />
<exclude name="**/*Test.class" />
</fileset>
<fileset dir="${jars.dir}">
<include name="my-simple-plugin.jar" />
</fileset>
</cobertura-instrument>
Commandline Usage:
The command-line usage for Cobertura is :
cobertura-instrument.bat [--basedir dir] [--datafile file] [--destination dir] [--
ignore regex] classes [...]
Eg:
cobertura-instrument.bat --destination C:MyProjectbuildinstrumented
C:MyProjectbuildclasses
8.1.2. Cobertura : Deployment of Code Coverage instrumented application
After generation of the instrumented classes, pointed to by
- ${instrumented.dir} in the ANT task or
- --destination dir in the Commandline usage
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Please deploy the ‘instrumented application’. If the build process creates a JAR, WAR or a EAR file as
part of the build process, or any other processing, the usage of originally compiled classes be replaced
with the instrumented classes.
Rest of build and deployment process remains unchanged for either ANT or manual methods.
8.1.3. Cobertura : Auto-Collection of Coverage data during testing
While testing, please ensure the Cobertura classpath is set –
- If the tests are run through an ANT script, then add Cobertura classpath to the test task’s
classpath (Explained below)
- If the tests are run though batch file, command-line or any other mode, ensure that the current
system path, and any classpath passed to the JVM as arg, has Cobertura classpath included, and
the instrumented classes are in classpath before the un-instrumented classpath.
ANT Usage:
In case of ANT, the following snippets can be used in any task that runs the tests, the referred
• fork="yes" arg to be passed for ANT
• <sysproperty key="net.sourceforge.cobertura.datafile" file="cobertura.ser" />
(Please ensure the file reference is right, or provide the right path to this file)
• <classpath location="${instrumented.dir}" />
(The variable instrumented.dir is referred the way it is used in example snippets above)
• <classpath refid="cobertura_classpath" />
(The variable Cobertura.classpath is referred the way it is used in example snippets above)
8.1.4. Cobertura : Merge & Final Report Generation
Once the tests are completed, we may need to
- Merge the separate .SER files,
o if we used different instrument tasks with separate .SER files for the application and we
need to integrate them to a single report
o If we used different copies of the same .SER file for different environments and need to
merge for overall report
o If we used different copies for the same .SER files for different kinds of testing and need
to merge for the overall report
- Create the Report in HTML / XML
ANT Usage:
Cobertura-merge task is used to merge the different .SER files. It majorly requires two inputs –
• List of input .SER files, the folder and file name for each of them
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• Where the output datafile to be created (defaults to “Cobertura.ser”, as illustrated in the
example below where no datafile has been specified).
Eg.
<cobertura-merge>
<fileset dir="${test.execution.dir}">
<include name="server/cobertura.ser" />
<include name="client/cobertura.ser" />
</fileset>
</cobertura-merge>
Cobertura-report task is used for report generation. It accepts parameters such as,
• Datafile (Location & Name of the .SER file from which the coverage data is read)
• Destdir (Where the generated report will be written to)
• Format (defaults to HTML)
• Srcdir (Where the source code for the instrumented classes are located – this is important for
source linking from the coverage reports)
• Maxmemory (JVM param, optional, but recommended to set for larger value for large code
bases).
Eg.
<cobertura-report format="html" destdir="${coveragereport.dir}" >
<fileset dir="${src.dir}">
<include name="**/*.java" />
<exclude name="**/*Stub.java" />
</fileset>
<fileset dir="${guisrc.dir}">
<include name="**/*.java" />
<exclude name="**/*RB.java" />
</fileset>
</cobertura-report>
Command-line Usage:
cobertura-merge.bat [--datafile file] datafile [...]
Eg.
cobertura-merge.bat --datafile C:MyProjectbuildcobertura.ser
C:MyProjecttestrundirservercobertura.ser
C:MyProjecttestrundirclientcobertura.ser
cobertura-report.bat [--datafile file] [--destination dir] [--format (html|xml)] source code directory [...] [-
-basedir dir file underneath basedir...]
Eg.
cobertura-report.bat --format html --datafile C:MyProjectbuildcobertura.ser --
destination C:MyProjectreportscoverage C:MyProjectsrc
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8.2. NCover Deployment for .NET based Applications
NCover supports integration with build process through MS Build & NAnt. The tasks are supported by
the DLLs provided as part of NCover.
For using NCover NAnt Build tasks, the DLL should be included like,
<loadtasks assembly="NCoverExplorer.NAntTasks.dll"/>
For using NCover MSBuild Tasks, the inclusion should be done like,
UsingTask TaskName="NCoverExplorer.MSBuildTasks.NCoverExplorer"
AssemblyFile =
"C:Program FilesNCoverBuild Task PluginsNCoverExplorer.MSBuildTasks.dll"/>
<UsingTask TaskName="NCoverExplorer.MSBuildTasks.NCover"
AssemblyFile =
"C:Program FilesNCoverBuild Task PluginsNCoverExplorer.MSBuildTasks.dll"/>
<UsingTask TaskName="NCoverExplorer.MSBuildTasks.NUnitProject"
AssemblyFile =
"C:Program FilesNCoverBuild Task PluginsNCoverExplorer.MSBuildTasks.dll"/>
More information along the usage and deployment of NCover using MS Build and NAnt is available in
the Online documentation for NCover.
9.0. Tools Evaluation
To evaluate good Code Coverage tools, one would require listing the evaluation parameters and rating
the tools on these. With that in mind, this paper lists major requirements for Code Coverage tools.
These need to be diligently checked and applied as relevant.
Parameter Weightage Notes
Coverage Levels
Package /Namespace Level Coverage 2 Java – Package, .NET –NameSpace
Class Level Coverage 2
Method level Coverage 3
Block Coverage 3
Line Coverage 3
File Level Coverage 2
Report Clarity
Source Linking 3 Ability to link Coverage report and Source files.
Hit Count 3 No. of times the statement/code block has been hit.
Exclusion Management Being able to exclude certain areas of code from reporting
Exclusion Provision 3
Namespace/Package level Exclusion 2
Class Level Exclusion 2
Method Level Exclusion 3
Line Level Exclusion 2
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Exclusion Patterns Definition 1
Source File Exclusion 2
Exclusion Reporting & Validation 2
Advanced Reporting Exportable Reports
HTML reports 2
Spreadsheet Export 2
Baselining & Versioning 2 To track coverage for only the newly added code
Incremental Reporting 2
Platform & Coverage
GUI Support 3
Command Line / Batch Mode
Support 1
Windows Vista Support 2
Windows - 64 bit support 2
Support for Build Script 2
Child Process Coverage 3
Stand Alone .NET apps Support 3
IIS Hosted ASP .NET apps 1
Windows Service Apps 3
Licensing & Logistics
Detailed Documentation 3
Open Source 2
Commercial 2
Paid Support 3
Community based Free Support 3
Technical Aspects
Source Level Instrumentation 3
Object Level Instrumentation 2
Auto Saving Frequency 3
Performance Increase 1
Compilation Time Increase 3
Merging 3
Standalone Instrumentation
independent of build 2
Code Size Increase 1
Figure 6 : Tool Evaluation Parameters
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10.0. Some Popular Tools Reference
S.No Technology Tool Names
1 Java Emma, Cobertura
2 .NET NCover, PartCover
3 C/C++ BullsEye, CoverageMeter
4 .NET & C++ DevPartner, Rational
PureCoverage etc.
5 Flex FlexCover
Figure 7 : Popular Tool References
11.0. Appendix
1. http://en.wikipedia.org/wiki/Code_coverage : Has very limited information – has list of some
tooling solutions
2. http://www.bullseye.com/coverage.html
3. http://www.cenqua.com/clover/doc/coverage/intro.html
4. http://cobertura.sourceforge.net/anttaskreference.html
5. http://www.ncover.com/documentation/buildtasks
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