How can you ensure the transparency of QA automation processes?

(1) Define goals and objectives for QA automation workflow after performing GAP analysis using best practices. (2) Communicate your QA automation processes and results. (3) Seek feedback and improvement for your QA automation processes.

Define your Automation goals, scope and socialize your roadmap with stakeholders. Conduct monthly update session to provide where you are in your journey Celebrate the wins and encourage collaboration Automation is a not a one shot solution Demonstrate through time savings all the efficiencies gained

Todo projeto de automa??o bem feito come?a um com planejamento detalhado em que s?o levantados os objetivos de teste, ferramentas e cobertura. Com essas informa??es em m?os é possível ser mais assertivo na execu??o, planejando esfor?o, pessoas , conhecimento e ambiente.

To improve transparency in QA automation I think a great idea is to share it with the development&test team and even have it as part of a regular session as a retro of the test team. Output of the automation as logs, screenshots and test results document can be shared on the company documentation platform. Having good tests that can be repeatedly run with the same results on different servers is a win win for everyone. Go QA!

Before automating tests, collaborate and define clear QA automation goals: A well-defined QA automation plan ensures efficient testing and project success. Business Value: Enhance user experience; align goals with business objectives. Test Coverage: Prioritize scenarios based on feedback; regularly reassess and update. Test Types: Automate unit, integration, regression tests; balance based on needs. Tools Selection: Choose tools. Adaptable Environments: Configure for various browsers, devices; implement robust environment management. Progress Tracking: Establish KPIs; analyze regularly, create a feedback loop. Maintain a crucial balance; regularly review and update to align with dynamic project requirements.

Fixing mistakes and bugs is important, but we should also pay attention to unexpected issues. Deciding how much automation we need is crucial. Also, it's suggested not to complicate our tests with too much logic, this way, we can focus on making our tests better.

From the my experience, it is better to understand where we should use this rule and where shouldn’t. When you start a new project, usually you have small amount of time and need results here and now, moreover, sometimes this projects intends to be small and one time. Should we spend several weeks for creating the processes in this case? I think, that it will be unnecessary wasting of time in this case. In order to have results here and now, you may temporary neglect complicated setup in favour of simple process. But every specialist should understand and tell his manager/client, that if such projects will grow, you need to replace whole foundation instead of small refactoring.

Always ask yourself: - What are the benefits of following coding rules? - How is this commonly applied in my field of practice or my organization? Usually it is not clever to follow rules that not any other developer in your organization uses. Those rules are always meant to contribute to a better and more efficient cooperative workflow. Get your team involved in this process and maybe create a set of rules for your own environment.

Automation plays an important role when you have a large number of repetitive test cases that need to be executed in order to access the impact, also some complex scenarios where an ample amount of time is spent in data creation, in such cases data set up can also be automated which will give more time for testers in validation. Few best practices can be 1. Methods should be small and reusable. 2. Reporting should be well designed so that it can be reviewed by wider teams 3. Complex calculations can be broken down into smaller methods so that any change in functionality can be easily accomodated. 4. Integration with version control and execution tools like Jenkins can reduce manual intervention in execution.

It is also important how to create new data or use existing data. Usually it is best to keep the scripts creating data and validating processes separate. While running stitching the data and process scripts is the key. It is also important to keep the data strategy to be very dynamic instead of hard coding data in the automated scripts.

This is I believe most important aspect of automated testing process. A good reporting system creates good test documentation and evidence that things actually works. Pump it up by adding debugging information so you never drop on hard to reproduce defects.

The automation testing tool, should truly be automated including the scenarios, test cases, parameters for each test case/script, along with capturing the screen during execution of each step. On the failed step, the screenshot becomes much more critical for the dev team to debug. Finally the results summarized for leadership team to get a quick view.

Ideal Reporting system should - (1) report test failure and exact cause of it (2) report flacky tests and number of times certain test's failure in past ( historical data analysis for tests) (3) report webpage or web element loading in expected duration or not (4) report action, transaction or scenario completed within expected time or not. (5) track each actions taken by automation on website No single reporting tool today achieve this. Most available reporting tools report #1. Observability platforms like datadog can be useful to give #2, #3 and #4. #5 can be achieved by hotjar or mixpanel.

transparency in QA automation processes is achieved through a combination of documentation, communication, version control, test reports, code review, collaborative tools, training, feedback loops, environment details, and regular meetings. By implementing these strategies, teams can create an environment where information flows seamlessly, fostering trust, collaboration, and ultimately, the successful execution of QA automation processes.

Automation reports play a major role in understanding the behaviour and statistics of the particular release. 1. Reports can have details of the passed/ failed count with execution time. 2. Detailed error messages can be mentioned ( or masked) in the reports to make it simple for reviewing people to debug it. 3. Test case summary can also be included to make it readable to business, it gives clarity on the kind of test cases executed for a particular release. 4. In case of browser automation screenshots can be helpful as evidence. 5. In case of APIs the responses can be included in reports. 6. Reporting can be in the form of pdf or html pages for good readability and can be sent over mails to the respective audience for each execution.

Most test management tools have built-in tracking system to show coverage and results. Automation coverage is no different. For example, using dashboards in Azure DevOps can help visualize the build and automation results. Using different widgets and queries displays metrics to help visualize trends over time as well as overall coverage. These reports can be accessed by the whole product team and enforces transparency to everyone. This will also help drive discussions on what areas to focus on from a business perspective.

The easiest way is just marking Test Cases as Automated within your test cases tracking system. In that case, you can keep any documentation related to automation process and nuances with the rest of test documentation. As for results, try and use metrics for QA effectiveness, such as bug leakage, release velocity (or testing velocity) and compare them between the proportional amount of manual and automated test cases. Those will help you identify whether your automation strategy is paying off without having to puzzle together a bunch of scattered reports, documents and test code.

Sharing the automation process, opens the door to new spectrum of ideas which will benefit all teams within the organization, as it gives clarity on automation covered areas and showcase the capabilities of automation and how it can be utilized. Automation by itself is colorful and involving the audience makes it vibrant.

Il faut en amont s'assurer de la capabilité machine et pour assurer la transparence enregistrer les échantillons dans un journal de production avec système spc.

Automated and customized reports communicated and discussed over required frequency with various stakeholders is the best way for ensuring transpareny in automated quality control processes...

Never neglect the developers experience of using your process. In small company or really huge and old company automation engineers usual work separately and make automation reports for the only, but as soon as team grows, developers will start to check tests results and, in ideal approach, starts to write or change tests. And if you have a complicated and messy system, you will spend tons of time to review and meeting. Moreover, you may use such improvements to speed up future onboarding - clear process requires less time for understanding for the newbie.

Feedback is a non negotiable process in quality assurance processes and with the digitalization many tools can be created to have timely feedback from your internal and external stakeholders for a automated and rugged quality assurance progrramme...

Il faut un système simple où la communication est faite de fa?on horizontale et verticale pour que le feedback soit optimal.

Effektives Feedback in QA-Automatisierungsprozessen erfordert die Gewichtung von Rückmeldungen basierend auf dem Kenntnisstand der Beteiligten. Regelm??iges Einholen von Feedback von einer vielf?ltigen Gruppe, einschlie?lich Entwicklern, Managern und Kunden, ist für eine umfassende Perspektive wichtig. Nutzen Sie unterschiedliche Methoden wie Umfragen und Interviews, um ein breites Spektrum an Meinungen zu erfassen. Analysieren Sie das Feedback sorgf?ltig, um gezielte Verbesserungen zu identifizieren und implementieren Sie diese. überwachen Sie die Auswirkungen der Ma?nahmen mit Metriken, um die kontinuierliche Optimierung zu gew?hrleisten.

One of the main benefits of automation is the reduction of time and effort it takes to execute repetitive manual test cases. Engaging with the functional test team to identify regression tests that are most frequently run with high impact on the system, is crucial in ensuring that the automation effort is adding benefit to the team and ensuring high quality code is released with as few defects in critical areas, as possible.

In my experience (all 19 years of pure QA :)), I have seen a significant share of QA automation effort put into building reporting dashboards with metrics (some useful, some blah) for a snapshot view of all the existing automation run results. However, the fundamental loophole was the absence of data tracking the test_case-to-automation_coverage mapping. As a result, regressions started creeping in that went undetected by automation as the corresponding test wasn't automated in the first place! I believe this fundamental aspect should be monitored thoroughly which is when the dashboard data becomes more relevant.

Model your QA automation infrastructure, develop key metrics, collect big data on your process, integrate with your companies favorite analytics program, make data driven decisions on process improvements WITH key stakeholders.

1) Keep clear and updated test documentation like checklists, test cases, framework guidelines, and other artifacts accessible to all team members. This gives a crucial understanding of what is covered - and what is not 2) Use tools linking Jira and GitHub for visible progress tracking of each task 3) Adhere to best principles like KISS and DRY, and annotate your code with clear comments and explanations. It makes code not only easier to read but also much more maintainable in the future 4) Integrate reporting tools like Allure in your framework, and add clear step annotations to methods - so test results can be interpreted easier and faster 5) Consider regular code reviews, team training on automation, and knowledge sharing in the team

To continually improve transparency in quality control automation processes, it is critical that everyone involved adopts a documentation approach, allowing the algorithms and models used to be easily understood and audited internally and externally for better quality control. This generates processes where all employees and customers involved can trust automated systems, promoting constant improvements in the processes involved.

1-Analyse what test scenario you have to do and think of the approach you are going to follow to test it. 2 -Before starting your automation discuss the approach with your leads and continue . 3- Share the results and take feedback if any ammendments are required or not.