This document discusses establishing code review processes for a team. It outlines the benefits of code reviews, including finding bugs earlier, increased maintainability, and coaching opportunities. It provides suggestions for an effective code review process, such as using checklists, keeping reviews small in scope, and measuring the results. While code reviews require commitment and can be challenging to implement, the document argues they are important for improving code quality and the team.
The document discusses challenges faced by companies with both in-house and outsourced software testing. It introduces predictive analytics as a solution to address common challenges like managing multiple releases and tools, measuring productivity, and generating customized reports. Predictive analytics uses models to analyze test data and predict issues, risks, delays and determine how to optimize testing. Integrating predictive analytics into a testing framework can help reduce costs, improve quality and make better decisions.
Decreasing false positives in automated testingSauce Labs
QASource presented on reducing false positives in automated testing. Some key points:
1. False positives occur when tests are incorrectly marked as failed when they should have passed. Common causes include reliance on UI elements, synchronization issues, and unstable test code.
2. False positives can impact automation by wasting time investigating failures, decreasing productivity, and obscuring real bugs.
3. Strategies to reduce false positives include using stable locators, short independent tests, dynamic synchronization, teardown logic, and re-execution of failed tests.
4. Eliminating false positives leads to more certainty in test results and reduced costs of automation.
This document discusses how machine learning can be applied to various activities in software testing. It describes how machine learning works using training and test data to make predictions. Supervised and unsupervised learning techniques are discussed. Specific applications mentioned include software defect prediction, test planning, test case management, debugging, and refining blackbox test specifications. Challenges include availability of past data and finding predictable patterns, while potential steps forward include expanding machine learning to more blackbox techniques, identifying the right patterns for different test activities, algorithm analysis, and crowdsourcing.
eXtreme Programming (XP) is an agile software development methodology that focuses on rapid software development and delivery through practices like continuous integration, pair programming, and frequent refactoring. It aims to address common software project problems like schedule slips, high defect rates, and changing requirements by having short development cycles, automated testing, and close collaboration between developers and customers. Key XP practices include planning game, small releases, simple design, testing, refactoring, pair programming, and on-site customer involvement. Adopting XP can benefit both developers through better requirements and technical empowerment, and customers through timely delivery of valuable software that can adapt to changes.
Presentation -Quality Metrics For Agile DevelopmentNabilahmed Patel
This document discusses quality metrics for agile software development. It outlines metrics for defects tracking, code coverage, and other measures of quality. Other metrics mentioned include cohesion and coupling, which measure how well code elements belong together and depend on each other. Additional metrics discussed are source lines of code, cyclomatic complexity, function point analysis, and program runtime, which provide information on code size, complexity, functionality, and performance. All of these metrics can help measure aspects of software quality.
This is a free module from my course ISTQB CTFL Agile Tester revised to 2014 syllabus. If you need full training feel free to contact me by email (amraldo@hotmail.com) or by mobile (+201223600207).
This document discusses establishing code review processes for a team. It outlines the benefits of code reviews, including finding bugs earlier, increased maintainability, and coaching opportunities. It provides suggestions for an effective code review process, such as using checklists, keeping reviews small in scope, and measuring the results. While code reviews require commitment and can be challenging to implement, the document argues they are important for improving code quality and the team.
The document discusses challenges faced by companies with both in-house and outsourced software testing. It introduces predictive analytics as a solution to address common challenges like managing multiple releases and tools, measuring productivity, and generating customized reports. Predictive analytics uses models to analyze test data and predict issues, risks, delays and determine how to optimize testing. Integrating predictive analytics into a testing framework can help reduce costs, improve quality and make better decisions.
Decreasing false positives in automated testingSauce Labs
QASource presented on reducing false positives in automated testing. Some key points:
1. False positives occur when tests are incorrectly marked as failed when they should have passed. Common causes include reliance on UI elements, synchronization issues, and unstable test code.
2. False positives can impact automation by wasting time investigating failures, decreasing productivity, and obscuring real bugs.
3. Strategies to reduce false positives include using stable locators, short independent tests, dynamic synchronization, teardown logic, and re-execution of failed tests.
4. Eliminating false positives leads to more certainty in test results and reduced costs of automation.
This document discusses how machine learning can be applied to various activities in software testing. It describes how machine learning works using training and test data to make predictions. Supervised and unsupervised learning techniques are discussed. Specific applications mentioned include software defect prediction, test planning, test case management, debugging, and refining blackbox test specifications. Challenges include availability of past data and finding predictable patterns, while potential steps forward include expanding machine learning to more blackbox techniques, identifying the right patterns for different test activities, algorithm analysis, and crowdsourcing.
eXtreme Programming (XP) is an agile software development methodology that focuses on rapid software development and delivery through practices like continuous integration, pair programming, and frequent refactoring. It aims to address common software project problems like schedule slips, high defect rates, and changing requirements by having short development cycles, automated testing, and close collaboration between developers and customers. Key XP practices include planning game, small releases, simple design, testing, refactoring, pair programming, and on-site customer involvement. Adopting XP can benefit both developers through better requirements and technical empowerment, and customers through timely delivery of valuable software that can adapt to changes.
Presentation -Quality Metrics For Agile DevelopmentNabilahmed Patel
This document discusses quality metrics for agile software development. It outlines metrics for defects tracking, code coverage, and other measures of quality. Other metrics mentioned include cohesion and coupling, which measure how well code elements belong together and depend on each other. Additional metrics discussed are source lines of code, cyclomatic complexity, function point analysis, and program runtime, which provide information on code size, complexity, functionality, and performance. All of these metrics can help measure aspects of software quality.
This is a free module from my course ISTQB CTFL Agile Tester revised to 2014 syllabus. If you need full training feel free to contact me by email (amraldo@hotmail.com) or by mobile (+201223600207).
Automation in the Bug Flow - Machine Learning for Triaging and TracingMarkus Borg
Issue management is a costly part of software development. In large projects, the continuous inflow of issue reports contributes to the information overload in a project, i.e., "a state where individuals do not have time or capacity to process all available information". In issue triaging, an initial step in issue management, a developer must be able to overview existing issue reports and easily navigate the software engineering project landscape. In this presentation, we present support for two work tasks involved in issue management: 1) issue assignment and 2) change impact analysis. We use machine learning to harness the ever-growing number of issue reports, by training recommendation systems on previous issues. Our industrial evaluations on 50,000+ issue reports in two large software development organizations indicate that automated issue assignment performs in line with current manual work. Moreover, we present how traceability from already resolved issue reports to various artifacts can be reused to jump start change impact analyses for newly submitted issues. Finally, we speculate on future ways to tame information overload into helpful software engineering recommendations.
This document discusses agile test automation and addresses whether it is an essential truth, oxymoron, or lie. It notes that agile emphasizes parallel teamwork between development, testing, and business. While test automation may initially require extensive ramp-up time and skills acquisition, building a library of automated scripts and using programmatic test tools can help achieve faster feedback, consistency, and avoid technical debt. The document advocates automating tests in parallel with development in each sprint to allow for easy, flexible regression testing. It argues that with an evolving approach to automation and a focus on reusing test data, process knowledge, and results, agile test automation can be an essential part of the agile process.
This document describes visual regression testing, which compares the visual output of software to detect changes. It introduces the Antenna House Regression Testing System (AHRTS), a tool that automatically compares PDF output documents on a pixel-by-pixel level to test for regressions in new releases of Antenna House Formatter software. AHRTS addresses challenges with manual visual regression testing by offering high-speed performance on large document sets and generating detailed reports on any differences found. The automated approach significantly reduces testing time and effort while improving accuracy and reliability over manual methods.
This document discusses using a genetic algorithm to develop a machine learning model for predicting fault-prone software classes. It begins by introducing software reliability and fault prediction. It then explains that a genetic algorithm is a search technique that evaluates potential solutions, keeps the best ones, and generates new solutions iteratively. The algorithm uses software metrics like coupling, cohesion, inheritance, and size as inputs to classify classes as faulty or fault-free with 80.14% accuracy, helping to identify areas for improvement.
Defect root cause analysis, Андрей ТитаренкоSigma Software
This document outlines a process for defect root cause analysis with the following goals:
1) Control defect costs and delivery through early defect elimination to save budget.
2) Contract with the team to map potential defects to root causes and SDLC phases.
3) Mine data to accurately define defect root causes and focus on solving real problems by adjusting team process and prevention strategies, then monitoring progress to ensure effectiveness.
Why Automated Testing Matters To DevOpsdpaulmerrill
“Automated testing is a pain in my ear! Why can’t QA get it right? Why do the tests keep breaking? And for Pete’s sake, stop blaming the infrastructure!”
…Ok, maybe you chose a different word than “ear”.
How often do you have thoughts like this? Daily?
Let’s talk about these frustrations, why they exist and how we can use them to improve our systems!
In this talk, Paul Merrill, founder and Principal Automation Engineer at Beaufort Fairmont explores why automated testing matters to DevOps. Join us to learn how automated testing can be a useful tool in the creation and release of your systems!
Agile driven development main principlesTanya Epstein
The document discusses the principles of agile driven development, including that projects have become shorter but more complex, requiring a user-centric approach. It outlines the agile manifesto which values individuals, working software, customer collaboration and responding to change over documentation, contracts and strict plans. Key principles of agile include open communication, incremental changes and rapid feedback. Success requires teamwork, quality assurance, resolving dependencies, and software integration and availability through continuous builds. A combined approach uses both rolling wave and agile planning with high-level milestones and detailed iterations.
Agile Testing - presentation for Agile User Groupsuwalki24.pl
The document discusses agile testing principles and processes. It compares agile testing to waterfall testing and outlines some key differences. It also addresses topics like continuous integration, test automation, managing test cases and issues, and transitioning from waterfall to agile. Pseudo-agile projects are described as those that claim to use agile but lack key elements like automation, continuous integration, or involvement of testers throughout the process.
DevOps Tactical Adoption Theory tries to make the transition process as smooth as possible. It hypothesis each step towards DevOps maturity should bring a visible business value empowering management and team commitment for the next step. The innovative idea here, it is not required to add the tools/processes to stack from sequential beginning to end, but seeking benefit.
The reason behind the theory is to encourage practitioners to apply each step one-by-one and then having the benefits in projects. Consequently, each step is tested in terms of utility and proved method validity for the further steps. In contrast to previous adoption models, our model indicates concrete activities rather than general statements.
Theory built on the claim that many DevOps transition projects considered problematic, impractical or even unsuccessful causing concept to become a goal more than a technique. Basically, theory consists of different areas of interest describing various actions on a schema.
In the session, it is planned to demonstrate “DevOps Tactical Adoption Theory” with focus on Delivery Pipeline/Testing Practices sectioned "Continuous Testing in DevOps".
Building the rights Right. Use the concept of continuous validation (hypothesis driven development) to prevent that your automated software development pipeline becomes a vehicle to deliver crap fast and helps you focus on the goals that software should help you achieve
This document discusses software verification. It defines software verification as evaluating software to determine if it satisfies requirements. It notes that software verification checks if the right product is being built, while validation checks if the product is being built right. The document outlines various methods for software verification including model checking, theorem proving, dynamic execution, and runtime verification. It discusses key challenges in software verification like performance and automation. Finally, it provides examples of industries where software verification is important, such as aeronautics, space exploration, medical technology, autonomous transportation, and energy.
like Google, Improve your Test perception & practices and learn how Test might be a key lever to improve your business.
- Understand the different types of Test
- Best & Worst practices of Test
Testing automation is important in agile environments to allow for frequent testing of software increments without relying solely on manual testing. In agile, testing automation is treated as part of the development process from the beginning by including automation activities in the backlog and having automation developers work closely with the entire scrum team. Testing automation executes after each code delivery and the results are analyzed by the whole team to help keep the code clean and move the project forward through ongoing automated testing as part of the agile way of life. This differs from the traditional waterfall model where testing automation was more isolated, focused only on regression testing, and had lower priority and integration with the development team.
This document presents an overview of agile testing. It discusses how agile testing differs from general testing by following the principles of agile software development and involving all team members, including testers. The document notes that specification by example is used to define desired and undesired behaviors to guide coding. Some benefits of agile testing are more testing time, continuous testing, face-to-face communication, self-organization, less manual testing, and competency development.
This document summarizes a concise QA and testing process developed for a small startup. It includes protocols for building, testing, managing changes, and releasing software. The build protocol ensures testing receives builds and information about changes. The test cycle protocol defines different types of testing cycles. The change protocol establishes feature freezes and code freezes to control changes late in development. The release protocol details the release approval and packaging process.
This document discusses using parallel_calabash to run automated tests in parallel to speed up test execution time. It describes how parallel_calabash works by grouping test features, spawning multiple processes across devices, and summarizing results. Running tests in parallel utilizes multiple CPU cores and significantly reduces test feedback time from over an hour to under 15 minutes, allowing for faster development cycles.
Gamification in outsourcing company: experience report.Mikalai Alimenkou
Most of us used to hear word gamification only for end user engagement into product usage. Some of us know about usage of similar approaches in product development teams to improve and tune development process. But almost nobody believes that gamification is possible in the context of outsourcing companies and teams. This talk is experience report of gamification usage on very large project with detailed reusable framework demonstration. If you want to bring some fun and really engage your team, then this talk is for you.
The document discusses Coverity Development Testing which helps reduce risks in software development through continuous integration and development testing. It highlights how software complexity and speed of development have outpaced traditional testing methods. Coverity aims to move quality, security and testing earlier in the software development lifecycle through static analysis, issue management, and developer workflow integration. The document provides an overview of how Coverity's static analysis works and how it can find critical defects that are difficult to detect with traditional testing alone.
[Europe merge world tour] Coverity Development TestingPerforce
Development testing can reduce costs, accelerate development, and protect brands by:
1) Finding defects earlier in the development process before they escape to production through continuous integration and static analysis.
2) Prioritizing testing of critical code and ensuring all code impacted by changes is tested.
3) Optimizing developer workflows by integrating testing into the development process and minimizing redundant testing.
Effective Testing Practices in an Agile EnvironmentRaj Indugula
This is a practitioner’s view of testing and testing practices within an iterative development environment. We will explore the challenges of testing within such an environment and ways to better integrate the QA professional into what is inherently a developer-centric methodology. If quality is paramount, then we ought to move testing to the front of the line and test early and often. Automation lies at the heart of agility and we will look at how test automation techniques and test-first design philosophy might be applied at multiple-levels to drive quality.
Automation in the Bug Flow - Machine Learning for Triaging and TracingMarkus Borg
Issue management is a costly part of software development. In large projects, the continuous inflow of issue reports contributes to the information overload in a project, i.e., "a state where individuals do not have time or capacity to process all available information". In issue triaging, an initial step in issue management, a developer must be able to overview existing issue reports and easily navigate the software engineering project landscape. In this presentation, we present support for two work tasks involved in issue management: 1) issue assignment and 2) change impact analysis. We use machine learning to harness the ever-growing number of issue reports, by training recommendation systems on previous issues. Our industrial evaluations on 50,000+ issue reports in two large software development organizations indicate that automated issue assignment performs in line with current manual work. Moreover, we present how traceability from already resolved issue reports to various artifacts can be reused to jump start change impact analyses for newly submitted issues. Finally, we speculate on future ways to tame information overload into helpful software engineering recommendations.
This document discusses agile test automation and addresses whether it is an essential truth, oxymoron, or lie. It notes that agile emphasizes parallel teamwork between development, testing, and business. While test automation may initially require extensive ramp-up time and skills acquisition, building a library of automated scripts and using programmatic test tools can help achieve faster feedback, consistency, and avoid technical debt. The document advocates automating tests in parallel with development in each sprint to allow for easy, flexible regression testing. It argues that with an evolving approach to automation and a focus on reusing test data, process knowledge, and results, agile test automation can be an essential part of the agile process.
This document describes visual regression testing, which compares the visual output of software to detect changes. It introduces the Antenna House Regression Testing System (AHRTS), a tool that automatically compares PDF output documents on a pixel-by-pixel level to test for regressions in new releases of Antenna House Formatter software. AHRTS addresses challenges with manual visual regression testing by offering high-speed performance on large document sets and generating detailed reports on any differences found. The automated approach significantly reduces testing time and effort while improving accuracy and reliability over manual methods.
This document discusses using a genetic algorithm to develop a machine learning model for predicting fault-prone software classes. It begins by introducing software reliability and fault prediction. It then explains that a genetic algorithm is a search technique that evaluates potential solutions, keeps the best ones, and generates new solutions iteratively. The algorithm uses software metrics like coupling, cohesion, inheritance, and size as inputs to classify classes as faulty or fault-free with 80.14% accuracy, helping to identify areas for improvement.
Defect root cause analysis, Андрей ТитаренкоSigma Software
This document outlines a process for defect root cause analysis with the following goals:
1) Control defect costs and delivery through early defect elimination to save budget.
2) Contract with the team to map potential defects to root causes and SDLC phases.
3) Mine data to accurately define defect root causes and focus on solving real problems by adjusting team process and prevention strategies, then monitoring progress to ensure effectiveness.
Why Automated Testing Matters To DevOpsdpaulmerrill
“Automated testing is a pain in my ear! Why can’t QA get it right? Why do the tests keep breaking? And for Pete’s sake, stop blaming the infrastructure!”
…Ok, maybe you chose a different word than “ear”.
How often do you have thoughts like this? Daily?
Let’s talk about these frustrations, why they exist and how we can use them to improve our systems!
In this talk, Paul Merrill, founder and Principal Automation Engineer at Beaufort Fairmont explores why automated testing matters to DevOps. Join us to learn how automated testing can be a useful tool in the creation and release of your systems!
Agile driven development main principlesTanya Epstein
The document discusses the principles of agile driven development, including that projects have become shorter but more complex, requiring a user-centric approach. It outlines the agile manifesto which values individuals, working software, customer collaboration and responding to change over documentation, contracts and strict plans. Key principles of agile include open communication, incremental changes and rapid feedback. Success requires teamwork, quality assurance, resolving dependencies, and software integration and availability through continuous builds. A combined approach uses both rolling wave and agile planning with high-level milestones and detailed iterations.
Agile Testing - presentation for Agile User Groupsuwalki24.pl
The document discusses agile testing principles and processes. It compares agile testing to waterfall testing and outlines some key differences. It also addresses topics like continuous integration, test automation, managing test cases and issues, and transitioning from waterfall to agile. Pseudo-agile projects are described as those that claim to use agile but lack key elements like automation, continuous integration, or involvement of testers throughout the process.
DevOps Tactical Adoption Theory tries to make the transition process as smooth as possible. It hypothesis each step towards DevOps maturity should bring a visible business value empowering management and team commitment for the next step. The innovative idea here, it is not required to add the tools/processes to stack from sequential beginning to end, but seeking benefit.
The reason behind the theory is to encourage practitioners to apply each step one-by-one and then having the benefits in projects. Consequently, each step is tested in terms of utility and proved method validity for the further steps. In contrast to previous adoption models, our model indicates concrete activities rather than general statements.
Theory built on the claim that many DevOps transition projects considered problematic, impractical or even unsuccessful causing concept to become a goal more than a technique. Basically, theory consists of different areas of interest describing various actions on a schema.
In the session, it is planned to demonstrate “DevOps Tactical Adoption Theory” with focus on Delivery Pipeline/Testing Practices sectioned "Continuous Testing in DevOps".
Building the rights Right. Use the concept of continuous validation (hypothesis driven development) to prevent that your automated software development pipeline becomes a vehicle to deliver crap fast and helps you focus on the goals that software should help you achieve
This document discusses software verification. It defines software verification as evaluating software to determine if it satisfies requirements. It notes that software verification checks if the right product is being built, while validation checks if the product is being built right. The document outlines various methods for software verification including model checking, theorem proving, dynamic execution, and runtime verification. It discusses key challenges in software verification like performance and automation. Finally, it provides examples of industries where software verification is important, such as aeronautics, space exploration, medical technology, autonomous transportation, and energy.
like Google, Improve your Test perception & practices and learn how Test might be a key lever to improve your business.
- Understand the different types of Test
- Best & Worst practices of Test
Testing automation is important in agile environments to allow for frequent testing of software increments without relying solely on manual testing. In agile, testing automation is treated as part of the development process from the beginning by including automation activities in the backlog and having automation developers work closely with the entire scrum team. Testing automation executes after each code delivery and the results are analyzed by the whole team to help keep the code clean and move the project forward through ongoing automated testing as part of the agile way of life. This differs from the traditional waterfall model where testing automation was more isolated, focused only on regression testing, and had lower priority and integration with the development team.
This document presents an overview of agile testing. It discusses how agile testing differs from general testing by following the principles of agile software development and involving all team members, including testers. The document notes that specification by example is used to define desired and undesired behaviors to guide coding. Some benefits of agile testing are more testing time, continuous testing, face-to-face communication, self-organization, less manual testing, and competency development.
This document summarizes a concise QA and testing process developed for a small startup. It includes protocols for building, testing, managing changes, and releasing software. The build protocol ensures testing receives builds and information about changes. The test cycle protocol defines different types of testing cycles. The change protocol establishes feature freezes and code freezes to control changes late in development. The release protocol details the release approval and packaging process.
This document discusses using parallel_calabash to run automated tests in parallel to speed up test execution time. It describes how parallel_calabash works by grouping test features, spawning multiple processes across devices, and summarizing results. Running tests in parallel utilizes multiple CPU cores and significantly reduces test feedback time from over an hour to under 15 minutes, allowing for faster development cycles.
Gamification in outsourcing company: experience report.Mikalai Alimenkou
Most of us used to hear word gamification only for end user engagement into product usage. Some of us know about usage of similar approaches in product development teams to improve and tune development process. But almost nobody believes that gamification is possible in the context of outsourcing companies and teams. This talk is experience report of gamification usage on very large project with detailed reusable framework demonstration. If you want to bring some fun and really engage your team, then this talk is for you.
The document discusses Coverity Development Testing which helps reduce risks in software development through continuous integration and development testing. It highlights how software complexity and speed of development have outpaced traditional testing methods. Coverity aims to move quality, security and testing earlier in the software development lifecycle through static analysis, issue management, and developer workflow integration. The document provides an overview of how Coverity's static analysis works and how it can find critical defects that are difficult to detect with traditional testing alone.
[Europe merge world tour] Coverity Development TestingPerforce
Development testing can reduce costs, accelerate development, and protect brands by:
1) Finding defects earlier in the development process before they escape to production through continuous integration and static analysis.
2) Prioritizing testing of critical code and ensuring all code impacted by changes is tested.
3) Optimizing developer workflows by integrating testing into the development process and minimizing redundant testing.
Effective Testing Practices in an Agile EnvironmentRaj Indugula
This is a practitioner’s view of testing and testing practices within an iterative development environment. We will explore the challenges of testing within such an environment and ways to better integrate the QA professional into what is inherently a developer-centric methodology. If quality is paramount, then we ought to move testing to the front of the line and test early and often. Automation lies at the heart of agility and we will look at how test automation techniques and test-first design philosophy might be applied at multiple-levels to drive quality.
Venkat Subramaniam's presentation focuses on caring about code quality and characteristics of high quality code. Some key points discussed include: good code has high cohesion, low complexity, and is easy to understand and maintain. Code reviews and testing are important for improving quality. Metrics like cyclomatic complexity can help measure quality, and refactoring code can reduce complexity and technical debt over time. The presentation emphasizes that developing quality code is important for agility and avoiding costly defects.
The document discusses predictions for the future of testing and QA. It predicts that test automation will significantly increase from 31% currently to become a major part of the QA process. It also predicts that testing responsibilities will move earlier in the development cycle, with more testing by developers and end users. Requirements testing will also improve with automation and new technologies that provide 100% test coverage and automatically generate test cases.
The document discusses predictions for the future of testing and QA. It predicts that test automation will significantly increase from 31% currently to become a major part of the QA process. It also predicts that testing responsibilities will move earlier in the development cycle, with more testing by developers and end users. Requirements testing will also improve with automation and new technologies that provide 100% test coverage and automatically generate test cases.
Behavior Driven Development—A Guide to Agile Practices by Josh EastmanQA or the Highway
The document discusses Behavior Driven Development (BDD) and how it can help increase quality and prepare an organization for increased business demands. It describes BDD as an industry practice where the whole team collaborates on system testing and definition of done. BDD promotes requirements using examples, collaboration between roles, finding defects earlier and more often through automation, and keeping technical debt low.
Test Design + Environment Management: Scaling UI Automation for AgileSmartBear
Environment Manager allows QA teams to easily and quickly execute and report on TestComplete tests across more than 500 test environments. Right from inside TestComplete, without setup or configuration, you get an access to a real device lab for executing GUI tests across a range of browsers, operating systems, and resolutions.
This document discusses quality management in software projects. It describes quality management as having four main components: quality planning, quality control, quality assurance, and quality improvement. It also discusses various quality management techniques like software reviews, formal inspections, defect amplification and removal models, and statistical software quality assurance approaches like six sigma. The document emphasizes that quality management is important for project success and reducing costs from software defects.
We all have seen our share of bad code. We certainly have come across some good code as well. What are the characteristics of good code? How can we identify those? What practices can promote us to write and maintain more of those good quality code. This presentation will focus on this topic that has a major impact on our ability to be agile and succeed.
Learn how to establish a greater sense of confidence in your release cycle, along with the practices and processes to create a high-performing engineering culture within your team.
Ben Walters - Creating Customer Value With Agile Testing - EuroSTAR 2011TEST Huddle
EuroSTAR Software Testing Conference 2011 presentation on Creating Customer Value With Agile Testing by Ben Walters. See more at: http://conference.eurostarsoftwaretesting.com/past-presentations/
Scope master introduction presentation feb 2020 w vidColin Hammond
This document discusses automated analysis of software requirements using ScopeMaster. It provides an overview of ScopeMaster, describing it as a tool that analyzes user stories and requirements documents to find problems, help fix issues before coding, and provide better estimates. It highlights benefits like reduced costs, fewer defects, and faster delivery. Examples are given showing ScopeMaster finding 150 defects in requirements in 2 days and identifying potential savings of $100k or more in just a few hours of analysis.
Arcadian Learning is an Industrial Training Company with 50 years of Industry Expertise on Planning, Implementation and Operation of the Networks Offering six months Industrial Training program on Cloud Computing, Telecom, Big Data and Application Development.
http://www.arcadianlearning.com/index.html
IT Quality Testing and the Defect Management ProcessYolanda Williams
This document provides an overview of defect management processes. It discusses defining defects, defect prevention, discovery, resolution and process improvement. The key aspects covered are:
- Defining goals as preventing defects, early detection, minimizing impact and process improvement.
- Activities like root cause analysis, escape analysis and process metrics.
- The defect lifecycle of prevention, discovery, resolution and continuous improvement.
- Examples of defect analysis and status reporting including metrics like density, backlog and mean time to repair.
Traditional testing isn't keeping pace with the speed of DevOps and Continuous Delivery, but hope is not lost. AI will be used to make testing faster and more accessible to all.
Existing QA solutions were built for a world where software changed infrequently. Highly adopted tools such as Selenium, Appium, and JUnit require a specialized skillset, and require too much maintenance once you start factoring in the brittle nature of tests, and the infrastructure required to run tests at scale. But there is still hope for QA in machine intelligence.
Next-generation ML tools are here to help QA keep up with the agility of modern software delivery practices. You'll learn what ML strategies are being employed to make this possible, and what the future of QA - intelligent testing - looks like.
Takeaways:
- An overview of the QA tooling and vendor landscape
- Demystifying the buzzwords - what machine intelligence in testing means today and tomorrow
- How implementing DevTestOps can help increase test coverage and improve product quality
Software organizations that want to maximize the yield of Software Testing find that choosing the right testing strategy is hard, and most testing managers are ill-prepared for this. The organization has to learn how to plan testing efforts based on the characteristics of each project and the many ways the software product is to be used. This tutorial is intended for Software professionals who are likely to be responsible for defining the strategy and planning of the testing effort and managing it through its life cycle. These roles are usually Testing Managers or Project Managers.
This document discusses Test Driven Development (TDD). TDD helps create clean, simple code designs with low coupling between components. Writing tests first allows developing code with confidence as tests accumulate. It helps avoid technical debt by refactoring code as needed. TDD produces documentation in the form of executable tests and enables continuous integration and delivery. The TDD process follows the "Red-Green-Refactor" mantra of writing a failing test first, then code to pass the test, and refactoring code as needed. Tests should be written to be fast, independent, repeatable, self-validating, and timely. Tools and coding dojos can help practice and improve TDD skills.
The presentation provided an overview of software quality management and emerging trends in software testing. It discussed fundamentals like the software testing lifecycle, principles of testing, and types of testing. Emerging trends that were covered include increased test automation, use of testing tools, and the evolving role of artificial intelligence in quality assurance. The presentation also discussed how testing roles differ based on software development lifecycles like agile and DevOps. It concluded with an overview of career opportunities in software testing and the skills required to be an effective tester.
1) Complex software is everywhere and software development is difficult, time-consuming, and expensive.
2) There are often large gaps in software development processes which creates risks like inconsistent processes, lack of productivity reporting, and unpredictable development.
3) Visual Studio 2012 aims to address issues in software development through features like integrated testing tools, storyboarding for early feedback, load testing, and monitoring of applications in production.
Similar to Defect free development - QS Tag2019 (20)
This document discusses Acceptance Test Driven Development (ATDD), an agile practice that focuses on collaboratively defining acceptance criteria for user stories before implementation. It notes that ATDD aims to eliminate bugs through early testing, refactoring, and obtaining fast feedback. The document outlines the benefits of ATDD such as preventing regression, fixing defects immediately, and enabling continuous learning. It also acknowledges some challenges to adopting ATDD and provides suggestions for coping with them, such as improving gradually and obtaining assistance.
Test Automation Maturity Model (Israel Test Automation meetup 12/11/2018)Arnon Axelrod
Just few years ago most people didn’t know a thing about test automation. Today most companies either use test automation or plan to start doing it soon. However, even companies that use test automation regularly often have a long way to go in order to realize the full potential of test automation. In this talk I’ll try to outline a typical evolution of the test automation in an organization in the way to realizing its full potential.
This is the presentation I gave at Sela on 29/10/2018. It covers the importance of clean code and refactoring skills to productivity and business value
This is the presentation I gave at Sela on 29/10/2018. It covers some best practices for writing clean code and for doing refactoring efficiently. It also describes some of Resharper's features for refactoring and code analysis.
This document summarizes a presentation on moving beyond the page object pattern for test automation. It discusses other design patterns like the singleton, template method, decorator, factory, and builder patterns that can be applied to test automation. It also covers principles like SOLID, 4ROSD, and Poka-Yoke that can help create simpler, more maintainable test code. The presentation argues that while page objects are useful, other patterns may be better suited depending on the needs of the automation and that testers should not feel restricted only to the page object pattern.
In the Israel Test Automation meetup meeting on July 10, 2017, I gave this presentation about the relationships between test automation and architecture, and its importance to the reliability of the tests.
Make sure to read the notes, as they contain more-or-less the spoken content.
This document discusses unit testing, test-driven development (TDD), and acceptance test-driven development (ATDD). It begins with introductions and then discusses the importance of quality testing. It describes different types of tests including unit, integration, and acceptance tests. The bulk of the document focuses on explaining TDD and ATDD processes and benefits, including how they help improve code quality and design. It also addresses some limitations and challenges with applying these techniques.
The document discusses software quality and specification by example (SbE). It begins with defining quality and discussing why bugs occur. It then introduces SbE, describing how it can be used to collaboratively specify requirements through examples to derive automated tests and documentation. SbE benefits include improved communication, fewer bugs, and living documentation. The rest of the document provides examples of how to apply SbE, including through a simulation game, and discusses test scope and writing good automated acceptance tests.
The document provides an overview of C# and .NET concepts including:
- C# versions from 1.0 to 5.0 and new features introduced in each version such as generics, LINQ, lambda expressions etc.
- .NET Framework concepts such as Common Language Runtime (CLR), Just-In-Time (JIT) compilation, garbage collection.
- Value types vs reference types, stack vs heap memory.
- Language Integrated Query (LINQ) and expression trees.
- Various C# language concepts are demonstrated through code examples.
DECODING JAVA THREAD DUMPS: MASTER THE ART OF ANALYSISTier1 app
Are you ready to unlock the secrets hidden within Java thread dumps? Join us for a hands-on session where we'll delve into effective troubleshooting patterns to swiftly identify the root causes of production problems. Discover the right tools, techniques, and best practices while exploring *real-world case studies of major outages* in Fortune 500 enterprises. Engage in interactive lab exercises where you'll have the opportunity to troubleshoot thread dumps and uncover performance issues firsthand. Join us and become a master of Java thread dump analysis!
INTRODUCTION TO AI CLASSICAL THEORY TARGETED EXAMPLESanfaltahir1010
Image: Include an image that represents the concept of precision, such as a AI helix or a futuristic healthcare
setting.
Objective: Provide a foundational understanding of precision medicine and its departure from traditional
approaches
Role of theory: Discuss how genomics, the study of an organism's complete set of AI ,
plays a crucial role in precision medicine.
Customizing treatment plans: Highlight how genetic information is used to customize
treatment plans based on an individual's genetic makeup.
Examples: Provide real-world examples of successful application of AI such as genetic
therapies or targeted treatments.
Importance of molecular diagnostics: Explain the role of molecular diagnostics in identifying
molecular and genetic markers associated with diseases.
Biomarker testing: Showcase how biomarker testing aids in creating personalized treatment plans.
Content:
• Ethical issues: Examine ethical concerns related to precision medicine, such as privacy, consent, and
potential misuse of genetic information.
• Regulations and guidelines: Present examples of ethical guidelines and regulations in place to safeguard
patient rights.
• Visuals: Include images or icons representing ethical considerations.
Content:
• Ethical issues: Examine ethical concerns related to precision medicine, such as privacy, consent, and
potential misuse of genetic information.
• Regulations and guidelines: Present examples of ethical guidelines and regulations in place to safeguard
patient rights.
• Visuals: Include images or icons representing ethical considerations.
Content:
• Ethical issues: Examine ethical concerns related to precision medicine, such as privacy, consent, and
potential misuse of genetic information.
• Regulations and guidelines: Present examples of ethical guidelines and regulations in place to safeguard
patient rights.
• Visuals: Include images or icons representing ethical considerations.
Real-world case study: Present a detailed case study showcasing the success of precision
medicine in a specific medical scenario.
Patient's journey: Discuss the patient's journey, treatment plan, and outcomes.
Impact: Emphasize the transformative effect of precision medicine on the individual's
health.
Objective: Ground the presentation in a real-world example, highlighting the practical
application and success of precision medicine.
Data challenges: Address the challenges associated with managing large sets of patient data in precision
medicine.
Technological solutions: Discuss technological innovations and solutions for handling and analyzing vast
datasets.
Visuals: Include graphics representing data management challenges and technological solutions.
Objective: Acknowledge the data-related challenges in precision medicine and highlight innovative solutions.
Data challenges: Address the challenges associated with managing large sets of patient data in precision
medicine.
Technological solutions: Discuss technological innovations and solutions
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WWDC 2024 Keynote Review: For CocoaCoders AustinPatrick Weigel
Overview of WWDC 2024 Keynote Address.
Covers: Apple Intelligence, iOS18, macOS Sequoia, iPadOS, watchOS, visionOS, and Apple TV+.
Understandable dialogue on Apple TV+
On-device app controlling AI.
Access to ChatGPT with a guest appearance by Chief Data Thief Sam Altman!
App Locking! iPhone Mirroring! And a Calculator!!
UI5con 2024 - Bring Your Own Design SystemPeter Muessig
How do you combine the OpenUI5/SAPUI5 programming model with a design system that makes its controls available as Web Components? Since OpenUI5/SAPUI5 1.120, the framework supports the integration of any Web Components. This makes it possible, for example, to natively embed own Web Components of your design system which are created with Stencil. The integration embeds the Web Components in a way that they can be used naturally in XMLViews, like with standard UI5 controls, and can be bound with data binding. Learn how you can also make use of the Web Components base class in OpenUI5/SAPUI5 to also integrate your Web Components and get inspired by the solution to generate a custom UI5 library providing the Web Components control wrappers for the native ones.
UI5con 2024 - Keynote: Latest News about UI5 and it’s EcosystemPeter Muessig
Learn about the latest innovations in and around OpenUI5/SAPUI5: UI5 Tooling, UI5 linter, UI5 Web Components, Web Components Integration, UI5 2.x, UI5 GenAI.
Recording:
https://www.youtube.com/live/MSdGLG2zLy8?si=INxBHTqkwHhxV5Ta&t=0
Unveiling the Advantages of Agile Software Development.pdfbrainerhub1
Learn about Agile Software Development's advantages. Simplify your workflow to spur quicker innovation. Jump right in! We have also discussed the advantages.
What to do when you have a perfect model for your software but you are constrained by an imperfect business model?
This talk explores the challenges of bringing modelling rigour to the business and strategy levels, and talking to your non-technical counterparts in the process.
Microservice Teams - How the cloud changes the way we workSven Peters
A lot of technical challenges and complexity come with building a cloud-native and distributed architecture. The way we develop backend software has fundamentally changed in the last ten years. Managing a microservices architecture demands a lot of us to ensure observability and operational resiliency. But did you also change the way you run your development teams?
Sven will talk about Atlassian’s journey from a monolith to a multi-tenanted architecture and how it affected the way the engineering teams work. You will learn how we shifted to service ownership, moved to more autonomous teams (and its challenges), and established platform and enablement teams.
Measures in SQL (SIGMOD 2024, Santiago, Chile)Julian Hyde
SQL has attained widespread adoption, but Business Intelligence tools still use their own higher level languages based upon a multidimensional paradigm. Composable calculations are what is missing from SQL, and we propose a new kind of column, called a measure, that attaches a calculation to a table. Like regular tables, tables with measures are composable and closed when used in queries.
SQL-with-measures has the power, conciseness and reusability of multidimensional languages but retains SQL semantics. Measure invocations can be expanded in place to simple, clear SQL.
To define the evaluation semantics for measures, we introduce context-sensitive expressions (a way to evaluate multidimensional expressions that is consistent with existing SQL semantics), a concept called evaluation context, and several operations for setting and modifying the evaluation context.
A talk at SIGMOD, June 9–15, 2024, Santiago, Chile
Authors: Julian Hyde (Google) and John Fremlin (Google)
https://doi.org/10.1145/3626246.3653374
Baha Majid WCA4Z IBM Z Customer Council Boston June 2024.pdfBaha Majid
IBM watsonx Code Assistant for Z, our latest Generative AI-assisted mainframe application modernization solution. Mainframe (IBM Z) application modernization is a topic that every mainframe client is addressing to various degrees today, driven largely from digital transformation. With generative AI comes the opportunity to reimagine the mainframe application modernization experience. Infusing generative AI will enable speed and trust, help de-risk, and lower total costs associated with heavy-lifting application modernization initiatives. This document provides an overview of the IBM watsonx Code Assistant for Z which uses the power of generative AI to make it easier for developers to selectively modernize COBOL business services while maintaining mainframe qualities of service.
Consistent toolbox talks are critical for maintaining workplace safety, as they provide regular opportunities to address specific hazards and reinforce safe practices.
These brief, focused sessions ensure that safety is a continual conversation rather than a one-time event, which helps keep safety protocols fresh in employees' minds. Studies have shown that shorter, more frequent training sessions are more effective for retention and behavior change compared to longer, infrequent sessions.
Engaging workers regularly, toolbox talks promote a culture of safety, empower employees to voice concerns, and ultimately reduce the likelihood of accidents and injuries on site.
The traditional method of conducting safety talks with paper documents and lengthy meetings is not only time-consuming but also less effective. Manual tracking of attendance and compliance is prone to errors and inconsistencies, leading to gaps in safety communication and potential non-compliance with OSHA regulations. Switching to a digital solution like Safelyio offers significant advantages.
Safelyio automates the delivery and documentation of safety talks, ensuring consistency and accessibility. The microlearning approach breaks down complex safety protocols into manageable, bite-sized pieces, making it easier for employees to absorb and retain information.
This method minimizes disruptions to work schedules, eliminates the hassle of paperwork, and ensures that all safety communications are tracked and recorded accurately. Ultimately, using a digital platform like Safelyio enhances engagement, compliance, and overall safety performance on site. https://safelyio.com/
How Can Hiring A Mobile App Development Company Help Your Business Grow?ToXSL Technologies
ToXSL Technologies is an award-winning Mobile App Development Company in Dubai that helps businesses reshape their digital possibilities with custom app services. As a top app development company in Dubai, we offer highly engaging iOS & Android app solutions. https://rb.gy/necdnt
Malibou Pitch Deck For Its €3M Seed Roundsjcobrien
French start-up Malibou raised a €3 million Seed Round to develop its payroll and human resources
management platform for VSEs and SMEs. The financing round was led by investors Breega, Y Combinator, and FCVC.
9. The Cost of Quality
Quality
Features
Delivery
Speed
9
10. The Cost of Quality
Quality
Features
Delivery
Speed
Quality
Features
Delivery
Speed
Good Eng. SkillsBad Engineering Skills
10
11. “High performers understand that they don’t
have to trade speed for stability or vice versa,
because by building quality in they get both.”
“Astonishingly, these results demonstrate that
there is no tradeoff between improving
performance and achieving higher levels of
stability and quality. Rather, high performers do
better at all of these measures.”
11
24. The Connextra format
As a <Role>
In order to <Achieve a goal>
I want <a behavior of the application>
24
25. The ATDD Process
PO defines the problem (User Story)
PO & team collaborate on simplest solution
Define Acceptance Criteria
Implement automated test
Implement Code & Refactor
Exploratory testing
Get customer feedback
25
26. Eliminating Defects with ATDD
Coding mistakes
Design or architectural flaw
Misunderstood requirements
Requirements don’t meet user expectations
Test coverage
Refactoring
Collaborative Acceptance
Criteria
Fast feedback
cycle
26
27. Handling Escaping Defects
1.Top Priority!
2.Create an automatic test to reproduce
3.Fix the bug
4.Perform a RCA and Apply to prevent similar issues
27
35. Low Hanging Fruits
Collaborate on User Stories and
Acceptance Criteria
Root-Cause Analysis
Write Automatic tests before fixing a
defect
Write new tests according to Acceptance
Criteria
35
38. Regressions can be eliminated (almost) completely
ATDD ensures full coverage
Full coverage enables refactoring and evolving the design
Simple design eliminates defects
Perform Root-Cause Analysis and Retrospectives
Measure and adopt
Investing in Quality improves Delivery speed
Summary
38
(3min)
Senior consultant
Author
Before that I worked in a team that applied most of the practices
4min
6min
Well, it depends on the definition…
Broadly speaking…
It is subjective, but we all know a defect when we see it
New behavior
Missing functionality are actually opportunities
(10min)
Note that even *preventing regression” in our own code base seems to most people as not feasible! (If you’ll get something out of this session and it would be to prevent regression in your own codebase at all price – it will be a great breakthrough). Most teams I know are far from achieving that goal.
10min
There’s a very common misconception that quality costs time and money. “In order to get higher quality we need to invest more in testing”. The truth is the opposite: good engineering practices and supportive culture, drive both higher quality and improves delivery, which saves time and money.
This is demonstrated very clearly by the most thorough study that was done on this subject, which is described in the book Accelerate.
thorough scientific research
2014-2017
23,000 people
2000 organizations
13min
thorough automated testing suite
We’ll discuss how to reach there
Minimizing defects in new and changed features, and reaching full regression suite
Coding mistakes
Design or architectural flaw
Misunderstood requirements
Requirements don’t meet user expectations
We’ll discuss mitigations
17min
Design is rarely attributed to defects
Defects hide in dirty places
We must keep our code and design clean
Components, micro-services (only if architected correctly!)
Minimum inter-dependencies
Higher confidence in changes
Less, simpler and faster tests
Examples: strong-typing (e.g. TypeScript vs. JavaScript), correct use of Encapsulation (private/public), Immutability, Generics
This is all cool and nice in theory, but…
Theory vs. reality…
(This is more like what my house look like. I failed to teach my kids defect-free behavior )
Reasons:
Changing requirements (and our understanding of the business)
The knowledge we gain over time about the technology
The evolution of the technologies we use
Lack of discipline (due to time pressure, lack of awareness, etc.)
This is the source for many defects
difficult to fix
It’s costly to add and modify features
22min
Series of small steps
Refactoring allows to evolve the design and improve it over time while adding new features
25min
ATDD is a key technique in Zero Defects. One that is very under utilized…
One key element of ATDD is the way user stories are defined
Misconceptions
Many people believe that the PO should define the user stories in a very detailed and clear way, so that the developers can understand exactly what they need to do, and the testers will know exactly what to test. Most people also believe that in order to come up with the best architecture, the entire feature should be planned, and only then be split into user stories, as a mean to project planning.
The essence: Problem definition
The team should collaborate on the solution
And as you can see, it covers all the faults.
33min
Consider this event and all the next steps as top priority!
Create an automatic test to reproduce
Fix the bug
Perform a RCA and apply the learning to prevent similar issues
Examples of RCA learnings can be:
Process improvements (e.g. who should review what and when)
Improve coding practices and guidelines (e.g. avoid returning null from functions). As much as possible automate these validations using Lint/Code analysis tools
Missing Code inspections – could be mitigated either by code review or by Static Code Analysis
Naïve assumptions – mitigate using reviews, knowledge sharing, etc, and other types of tests
Improve and simplify the design:
Remove duplication and coupling
Separate concerns into different classes or components
Error prevention: strong-typing, single source of truth
Fail fast: assertions, mainly in initialization.
But we should not wait only for detected defects in order to improve our codebase and apply these kinds of improvements. Assuming we have a thorough automated testing suite, we can (and should) constantly refactor to make these kinds of improvements, especially as we add new features.
37min
Hardware failures (not exactly a defect!)
3rd party components and services
Hardware issues
HA is a feature
Changed 3rd party behavior should be rare, due to backward compatibility
run some tests in production + monitoring
Treat production = escaping defects (see previous process)
50 ways…
Important: Action items and follow-up
40 min (5 left)
This all sounds great in theory, assuming we start the project using these practices. But in the real world, even projects that are considered “green field” start as a Q&D POC. So how do we reach this defect-free state in a legacy project?
If you apply these practices very early on in a new project, it may be easier
Otherwise, Don’t try to get it all at once
Here are some low hanging fruits that you can start with more easily:
Collaborating on user stories and acceptance criteria
RCA on chosen defects. Mainly in new components
Write automated tests to reproduce defects before fixing them
Write new tests according to acceptance criteria (or alike)
Here are some low hanging fruits that you can start with more easily:
Retrospectives
Run tests more often (by developers)
Experiment with ATDD, on isolated features
Cover with automated tests loosely coupled components and refactor
Refactor/re-architect to break direct dependencies
Add monitoring to production
Perform deeper RCA and act upon them accordingly
Continue to learn from retrospectives and improve your processes