Although Continuous Integration/Deployment methods advance their own technology, QA engineers are not keeping pace with development in their field. In other words, in addition to developing an application, developers are creating smarter methods of testing; but QA professionals are not reaching their highest potential benefit from these new technologies.
A QA Roadmap is now a critical component of every enterprise strategy to exploit recent developments in QA methodology. The way organizations develop software has changed, and so have the testing methods and challenges. QA teams work with agile, DevOps, TestOps, and Lean practices. There is a new wave of testing software which now includes the pervasive influence of machine learning. A plethora of new testing and deployment technologies such as containers and parallelism in testing must be mastered by QA engineers if they intend to deliver competitive performance.
Continuous integration methods merge code revisions with the main branch as often as possible. Continuous integration puts great emphasis on testing automation to ensure that new commits to one module do not break other parts of the application when integrated into the main branch. Continuous delivery extends continuous integration to make possible the release of new changes to customers quickly and sustainably. Continuous deployment is real-time deployment: every change that passes all stages of the production pipeline is released to the customer. Continuous deployment is an excellent way to accelerate the feedback loop with customers. And continuous deployment is like continuous delivery, except that releases happen automatically and rapidly.
Agile software development methodology is a process for developing software which exhibits some similarities to other software development methodologies, such as Waterfall, V-Model, and Iterative, but which asserts substantial improvements in workflow and management. Agile literally means ‘the ability to move quickly and efficiently’ and, ‘responding swiftly to change.’ Agile software development is so popular that it embellishes the familiar meaning, and describes an approach to software development which makes collaboration an imperative, and through its plan generates self-organizing cross-functional teams among developers and customers. It advocates adaptive planning, evolutionary development, early delivery, and continuous improvement, and it encourages rapid and flexible response to change. Agile software development methods support a broad range of the software development life cycle with some focus on the practices (XP, pragmatic programming, agile modeling). There is also an emphasis on managing the flow of work (Scrum, Kanban). Some programs support activities for requirements specification and development (FDD), while some seek to cover the full development life cycle (e.g., DSDM, RUP).
Agile Software Development Case Study
Google is developing a product to compete with MS Word, a product which provides all the features of MS Word and any other features requested by the marketing team. The final product needs to be ready in 10 months. Let us see how this project is executed in traditional and Agile methodologies.
The Waterfall model:
- At a high level, the project teams would spend 15% of their time on gathering requirements and analysis (1.5 months), 20% of their time on design (2 months), 40% on coding (4 months) and unit testing, 20% on System and Integration testing (2 months).
- At the end of this cycle, the project may also have 2 weeks of User Acceptance testing by marketing teams.In this approach, the customer does not get to see the product until the end of the project, when it is too late for significant changes.
With Agile development methodology:
- Each project is broken up into several ‘Iterations’.
- All Iterations should be of the same time duration (between 2 to 8 weeks).
- At the end of each iteration, a working product should be delivered.
- In simple terms, in the Agile approach the project will be broken up into 10 releases (assuming each iteration is set to last 4 weeks).
- Rather than spending 1.5 months on requirements gathering, in Agile software development, the team will decide the basic core features of the product, and which of these features can be developed in the first iteration.
- Any remaining features that cannot be delivered in the first iteration will be taken up in the next iteration or subsequent iterations based on priority.
- At the end of the first iteration, the team will deliver working software with the features that were finalized for that iteration. There will be 10 iterations and at the end of each iteration
- The customer is delivered a working software that is incrementally enhanced and updated with the features that were shortlisted for that iteration.
- The great improvement in Agile is the regular ability to interact, test, and revise during development!
Slow development processes become outdated quickly as the market becomes increasingly Agile-centric, more customer-centric, and more performance-driven. Manual processes are severely deprecated. The weaknesses observed by the participants in achieving the overall target of quality assurance include a lack of QA and test automation, time, resources, current software development methods, and efficient ways of working. The adoption of continuous integration and continuous delivery is seen as a complex strategy with a steep learning curve by most companies. While CI-based development reduces the cost of mistakes and productivity, adoption requires substantial budget and time investment, the burden of which is the requirement to hire and retain QA automation engineers that will incrementally cover an evolving product with automated tests. The groundwork for QA automation may take anywhere from 6 to 18 months. Sometimes development teams face difficulties adopting new software and integrating it with their habitual workflows. If a new feature is proposed which can’t pass testing, everyone concentrates on removing the bug, even if the feature at hand is not a priority.
One of the leading tenets of Agile software development is to always maintain a shippable product. Doing so allows a steady flow of code from the development team to the customer. Regular releases to customers offer real users the ability to provide feedback on the software to drive development. It gives the customer the feeling of being in motion, that quintessential feeling of progress. Development and test teams that quickly respond to customer feedback are more successful. Atlassian’s JIRA Capture, Issue Collector, and JIRA Mobile Connect can enable users to report valuable feedback efficiently.
Agile and DevOps are the main trends that are commonly used in software development, and quality assurance is an essential part of both agile and DevOps. Test automation is currently seen as one of the most important factors in improving the quality of software. Overall quality can be assured by automating all necessary functionalities including regression testing. Test environments should be automated and version control and functional requirement management should continuously support testing. Automation gives you a lot of confidence that things are working. It empowers your QA testers to go off and do the most valuable tasks. A lot of QA teams spend way too much time doing regression tests, and that’s where automation really does help. Without automation, the scope of your testing is incomplete, because you’re only going to do regression testing for what you can remember.
Agile development has become commonplace in IT. In a recent survey over 52% of respondents said that their company used Agile in one form or another. Business needs software to be competitive and to change and deliver faster than ever before. Agile is becoming an effective way for software teams to align more directly with business, to avoid scrap and rework, and to deliver greater value. Functionize provides a fully integrated automation framework (test, deployment, continuous integration) and enables teams to get a handle on the speed and volume of work required to generate reliable testing coverage.