In the first part of the article, we discussed how businesses can improve software quality, deliver at a fast pace, and increase customer satisfaction levels by relying on such significant QA trends as...
- Test automation
- Quality engineering for emerging technologies
- Value stream management
- Sustainable quality engineering.
Today, I suggest having a closer look at three more significant trends to help you enhance the efficiency of your current QA strategies.
Trend 5. Frequently deploy sound functionality at speed with Agile-driven QA
Organizations continue to embrace Agile- or DevOps-based transformations to reap multiple benefits ― seamless customer journeys, accelerated digitization, and more efficient and optimized processes, just to name a few.
While adjusting business models to fit changing requirements and the growing need for speed, quality assurance plays a pivotal role, as it helps provide excellent customer satisfaction and derive desired business outcomes. Due to its implementation in Agile and DevOps, companies can continue attaining well-timed delivery, release faster, enhance software quality, and boost productivity.
For enterprise systems, the Agile adoption path has just begun because of the overall complexity of their architecture and challenges with dividing voluminous business workflows into minor sections to fit them into small development sprints.
As a way out, the World Quality Report 2022-23 (WQR) suggests applying the following test approaches: packaged enterprise system-specific tools for automation, prebuilt test case repository for certifying a sprint, performance testing for all releases, impact analysis solutions, test integrated as automatic quality gates in the CI/CD pipeline.
How can organizations overcome challenges with infusing Agile QA workflows into the SDLC? Among other things, they can bet on people ― full-stack quality engineers who combine both business and technical cross-functional skills and have experience in test automation, CI/CD, performance, cybersecurity, programming, and other high-priority directions.
Regarding seeing the big picture, why not stick to the following best practices to reach higher adoption rates of Agile- and DevOps-based QA processes?
- Expand test automation usage across CI/CD pipelines to cut testing time, boost test coverage, and increase process accuracy. Also, do not bail on performance, cybersecurity, usability, integration, and other verifications to enhance software soundness and operation speed.
- Utilize best-of-breed industry toolkits and frameworks to ensure efficient QA processes and support business owners in case they’d like to get involved in software testing activities.
- Engage accomplished QA experts who are proficient in Agile methodologies, understand customer demands, IT products, and business specifics, as well as regularly upgrade their technical skills to provide unmatched quality in the production environment.
- Apply diverse metrics to track the slightest changes in the software quality level, provide visibility for all team members, and take appropriate action in time.
Trend 6. Adopt cloud servers for test environment provisioning
Cloud servers provide organizations of any size with great opportunities to move faster, increase flexibility and scalability capabilities, save costs, improve collaboration between team members, ensure disaster recovery and data loss prevention, and enhance security levels.
No wonder that 49% of the interviewed organizations utilize the cloud for more than 50% of their non-production environments, the WQR admits. In addition, 44% of companies apply a hybrid environment strategy involving on-premises and a single cloud provider, while 21% utilize only a single cloud platform.
Due to this shift, more opportunities occurred for automated provisioning of test environments, for which organizations prefer a combined toolkit ― open-source, commercial off-the-shelf, cloud.
Another rising tendency concerns cloud testing of diverse application aspects. The WQR mentions that almost all the respondents made it a part of their testing life cycle. However, only 1% of the interviewees find their cloud testing strategy to be highly efficient for all projects.
In this regard, I advise the following: the choice should fully depend on business specifics. For instance, a cloud server can be a perfect match for a growing business when the number of end users is increasing and the requirements for a cloud server are changing. Under these circumstances, it is more cost-effective as it can just be supplemented with novel virtual machines, IP addresses, etc. While an on-premise server is more suitable for companies that have a permanent number of users and therefore constant demands for servers.
Trend 7. Place more emphasis on test data provisioning and validation
The supply of quality, realistic test data to ensure that tests accurately reflect the correct system behavior often is a challenging and time-consuming process ― only one-fifth of all WQR respondents have an enterprise-wide strategy that is fully implemented.
Although 89% of companies must store all test data on-premises according to their policies, cloud usage is picking up steam. For instance, 83% of respondents are currently developing an effective cloud data strategy, 82% ― already stick to using a secure cloud platform for storing all de-sensitized data, while another 78% ― prefer private cloud to keep test data only during the project duration. Considering the prevalence of remote work nowadays, this trend can simplify and secure processes of operating with data.
However, automation of data provisioning is far from being highly successful, at least yet ― only half of the surveyed organizations replaced manual workflows with automated ones, and they are a part of an independent process rather than a CI/CD pipeline.
Taking into account that data provisioning tools can be complicated and have their technology requirements, the problem with test data skills remains topical. To overcome it, the WQR respondents design partnership strategies with tool vendors or system integrators and train their staff internally.
Validating the accuracy and quality of test data is another vital aspect that helps organizations ensure that it meets business requirements, spot duplicated, cluttered, or invalid data, etc. This is proved by the results of the WQR survey ― almost half of all the interviewed consider it to be highly important as they can attain better productivity, customer satisfaction, and decision-making.
The lack of automated tooling and necessary skills, the presence of diverse and complex databases, outdated data, and the high complexity of the overall process impede the application of data validation approaches.
To streamline and simplify working with data, companies can develop a holistic data provisioning approach for the whole organization, opt for multiple tooling opportunities to cover diverse needs and keep data updated.
To summarize
To embark on a journey of innovation and growth, companies use such emerging technologies as Web 3.0, blockchain, AI/ML, metaverse, digital twins, AR/VR. Due to overall complexity, their implementation and further usage can place a burden on project teams.
QA and software testing activities help ensure their proper operation, thus simplifying the adoption across enterprises. To better cope with this task and add value to the testing process, organizations can focus on important industry trends.
Sustainable quality engineering, value stream management, quality engineering for emerging technologies, test automation, a shift to Agile- and DevOps-driven QA, best practices for test environment and data management are among them.
By making them a part of the testing strategies, companies can increase customer satisfaction, enhance software quality, accelerate time to market, and optimize costs.