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BDD is Not Only Gherkin or Cucumber

Regression Testing
BDD (Behavior Driven Development) strives to communicate clearly whenever any stakeholder's understanding of the desired system changes and attempts to have stakeholders in diverse positions interacting smoothly in parallel to maintain a near-constant grasp of the intended system behavior. If that understanding has been misaligned, it should be updated, or it should be synthesized with a new understanding of the intended system. This ensures that all stakeholders are pulling in the same direction.
One of the agile approaches used to carry out development work is Behavior Driven Development. Its goal is for improved communication and cooperation among technical and non-technical team members while allowing business representatives to maintain project control. In that aspect, as we mentioned in a previous post, a software test plan is essential when using an Agile approach or just when not having enough time to planify a set of tests. They are not excuses for not using a Test Plan. The truth is that a test plan is useful regardless of the lifecycle strategy since it guarantees sufficient resources will be available to accomplish the testing goals.
BDD, like other kinds of iterative development, must be able to move this agreed-upon vision quickly from concept to release. Simultaneous design, development, and testing must be rapid enough to keep up with changing user demands while progressively upgrading the most recent system to better meet them.

The primary prerequisite for successful BDD is to maintain an up-to-date awareness of changing user demands. The capacity to correctly provide those rapidly changing user demands in production is the second.
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How to evaluate BDD: Criterias and Strategies

When the Behaviour Driven Development technique is just used for testing, the assumption surrounding its use differs from its actual implementation in the project. As a result, BDD no longer refers to a software development method, but rather to the process of developing automated tests. How can we avoid situations like this while implementing Behavior-Driven Development?
In many occasions, the reasons vary: the business may need more time (and money) to make available ready-to-use scenarios in the form of "Given, When, Then", or the individuals involved are unwilling or inadequately capable. Typically, the Product Owner gives the business needs in the language most familiar to him, and translation into Gherkin Syntax is set aside. In this scenario, the tester cannot just copy the content and paste it into the code. As a result, the job that should have been done much earlier falls on the tester, who must rewrite the business requirements rather than concentrate on testing.
On other cases, the fundamental idea of TDD and BDD, that tests should be a driving force in the software development process, has been ignored. The BDD goals cannot be accomplished if the scenario is developed subsequently, rather than - as best practices encourage - before developing a particular functionality. Non-simultaneous testing and development activities is also an issue.
If the scenario was not supplied previously, the tester develops one based on documentation and the developer's work. As a consequence, tests are enhanced just towards the end, when the Sprint is closed, and testers do their best to test the functionality and conclude all tasks.

Why BDD is so Beneficial?

With the use of the documentation provided in natural language, a team may find the benefits of BDD and Gherkin or Cucumber immediately. Natural language documentation is provided to all project participants, including non-technical teams, and aids in developing of applications at various phases. This way, team members have a common understanding and may discuss documentation in before implementation and in-progress meetings, and subsequently use it to visualize the state of the project in automatic tests and reports (if created).
Non-technical team members, such as business individuals, can also get an understanding of which business processes are covered by automated testing. This allows them to ensure that the application is designed in compliance with the expected business purposes from the start.

What's not BDD but it could be Gherkin

Requirements collection models such as Feature Files or user stories are significantly more adaptable than trying to maintain monolithic requirements papers. That's good for BDD, and Gherkin is a popular syntax for this.
As mentioned before, another key advantage of using Gherkin in Behaviour-Driven situations is that it uses normal language, which is easily understood by a wide variety of stakeholders in a Business project.

Although, on the other hand, while firing off scenarios in Gherkin Feature Files allows you to make changes rapidly, it seldom indicates how the new Feature Files connect to previously established situations. Fragmentary Feature Files, in turn, frequently rise up, offering no information on how the huge system logic should be related, or what has to be altered throughout the present system:
The usage of natural language in Gherkin adds to the possibility of ambiguity. Its lack of logical accuracy increases the likelihood of mistakes as written language is translated into logically exact (and unforgiving) code. This raises the likelihood of misunderstanding, problems, and time-consuming rework in the end.

That's not to imply Gherkin shouldn't be used in Behavior-Driven methods. It may and should be used in many circumstances; but, it must be accompanied with a larger strategy for keeping a logically accurate, up-to-date, and thorough understanding of the desired system behavior.

Furthermore, this knowledge must be one that can be immediately used in testing and development without the possibility of errors or mistranslation. The Feature Files must provide a conceptually exact representation of the desired system behavior, full with dependency mapping across components, to accomplish this. This allows for precise effect analysis whenever a new request for revision is received.

Common BDD Bottlenecks to Consider

BDD must be capable of efficiently converting intended system behavior into code in addition to retaining an up-to-date, common knowledge of the desired system behavior. The upgraded system must be supplied as soon as possible to keep up with rapidly changing user demands of nowadays.

This requires a quick iterative delivery process, with concurrent development and testing based on Behaviour-Driven requirements. To assure the quality of each release, QA must be capable of developing up-to-date tests, frequently while or before code is being produced.

However, time-consuming dependencies and complex manual methods usually make full testing of fast-changing systems in short cycles impossible to implement. These consume time and reduce test coverage, requiring test execution fall behind releases. As a result, the chance of production systems properly reflecting planned system behavior decreases.
Some of these BDD bottlenecks are found here:
1.- Manual test design is just too sluggish for properly testing complicated systems in short iterations. It's difficult to tell what logic need testing when systems change, and manually produced test cases generally focus on "easy to test features". This omits the vast majority of negative tests, leaving significant system logic vulnerable to malicious vulnerabilities.
2.- Regular test artifacts updates: The most common hurdle to thorough testing in short cycles is the need to maintain current test artifacts. Following a system update, QA teams must look at their current assets due to an absence of dependency mapping between requirements, code, and tests. They must then manually update a large number of test cases, scripts, and data to ensure that all artifacts stay in sync.
3.- Slow and manual text scripting: Repetitive test writing may undo the benefits of automated testing. When testing fast-changing, sophisticated systems, test execution must be automated since there are now more tests than can be executed manually in-sprint. Copying, pasting, and updating repeated code, on the other hand, typically substitutes one bottleneck for another: manual test creation is substituted with sluggish and manual test scripting.
4.- Test Management: Another difficult procedure that might affect test coverage is test management. In production, users may employ a wide range of configurations comprised of devices, operating systems, and supporting applications. However, there is no time to manually spin up hundreds of alternative configurations for test run, and the hardware and software would be prohibitively expensive. Cloud-based execution provides a faster alternative to physical device execution, but it does not address the issue of incomplete or unavailable software dependencies in test settings.
TestQuality as a Test Management case solution is the most suitable tool in this regard. since TestQuality can simplify test case creation and organization, it offers a very competitive price used within your GitHub workflows or Jira Test Management providing Rich and flexible reporting that can help you to visualize and understand where you and your dev or QA Team are at in your project's quality lifecycle. But also look for analytics that can help identify the quality and effectiveness of your test cases and testing efforts to ensure you're building and executing the most effective tests for your efforts.
Regression suites can comprise thousands of tests, making it almost impossible to manually update all existing artifacts following each change. At this point iis where a Test Management solution such as TestQuality helps to organize within it test case repository and as a result, test teams are compelled to prioritize either testing newly introduced logic or performing the regression required to uncover integration issues and unforeseen system effects. In either case, system logic is not reviewed prior to deployment, exposing systems to potentially harmful defects.

Once again, the structure of system requirements is typically the source of these delays. The text-heavy Gherkin Feature Files' lack of logical accuracy and 'flat' style preclude automated or systematic test design. Meanwhile, a lack of Gherkin dependency mapping and traceability to test artifacts inhibits automatic maintenance of test assets following a system update.

TestQuality and Gherkin

TestQuality's import capabilities also allow you to import requirements, tests, and issues by uploading Gherkin Feature Files easily with an import data option menu even when using a Gherkin based Test results JSON file.
Gherkin feature files can be uploaded via TestQuality REST interface via curl, a popular command line tool.
Once your file has been added, you can optionally choose a Cycle and Milestone that you would like to link to your Test Run result.

Gherkin Feature Files with your tests can be easily imported with TestQuality

TestQuality is designed around a live integration core that allows TQ to communicate directly with GitHub and integrate with Jira in real-time linking issues and requirements with the key tools in your DevOps workflows.

TestQuality's integration engine also allows you to connect to pull in automated test results from popular CI/CD, Test Automation, and Unit Testing systems.

If you are using a CI platform such as Jenkins, Cloudbees, Circle CI, Travis CI and want to upload your test results, you can add TestQuality to your scripts.

To connect via command line, you can use the command files TestQuality CLI (Command Line Interface) then using the file from your system, log in with username and password, or we can provide you with a personal access token so you do not have to provide your login details in the command.In Conclusion

In conclusion

Instead of being on the verge of discovering too late that you've misunderstood your intended system, test and development would be a constant path of understanding the system being developed. Meanwhile, software engineers would know exactly what to prioritize when upgrading rapidly changing systems in short updates.
BDD has evolved in popularity in the QA community, and is now a standard idea in big corporations and fintech companies, however "doing BDD" for these QA teams frequently entails writing scenarios in a specification language like Gherkin and executing them as tests in a test automation framework like Cucumber. Many of the procedural and philosophical obstacles that BDD attempted to eliminate are still present, with automation frameworks and specification languages acting as point solutions to specific problems such as Communication errors, issues, and bottlenecks continue to plague the organization as a result of inaccurately stated needs and an isolated strategy. Bugs are often identified late due to too manual QA that begins late. Numerous pre-'BDD' issues exist when seen through the lenses of people, process, and technology.
Gherkin and Cucumber may be a fantastic choice when you need everyone on the team to be informed without digging into technical intricacies. However, this combination may make test automation more complicated than necessary in the long term.

The choice is yours, but before you make it, carefully consider the advantages and disadvantages of each syntax and solution. The most important aspect is that you and your team have access to the necessary test management tools, such as TestQuality, for your testing tasks. Test management
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