To succeed in the competitive digital landscape, enterprises need to achieve high quality and agility. To meet these objectives, they need to simplify, secure, and modernize their legacy systems. Also, businesses need to have the requisite adaptability and flexibility in choosing the right QA tools. Ensuring the quality of products and services at every step of the way is critical in addressing the ever-changing customer expectations. If that is not enough then the changing market dynamics - mergers and acquisitions, new software rollouts, adherence to risk and compliance norms, data and analytics, mobile commerce, and the incorporation of IoT - have necessitated enterprises to be agile and enhance their quality assurance services.
With cybersecurity scare hovering around, enterprises need to up the ante to make their workflows, products, or services fully quality-compliant. This involves adhering to global quality standards like PCI, Sox, GDPR, etc. Adhering to these standards consistently would be an uphill task for enterprises if they employ traditional QA methodologies. With Agile and DevOps emerging as the preferred methodologies for software development, quality engineering is the way ahead.
It is a process wherein quality of a software is tested and validated throughout the Software Development Life Cycle (SDLC.) It encompasses activities such as analyzing a product’s design and development process to improve the quality of products and services and reduce waste.
QE services differ from traditional waterfall model where QA is an adjunct to the development process. Quality engineering solutions help to prevent as well as detect glitches in a software application. These optimize quality throughout the SDLC and beyond by involving everyone in the organization.
The competitive online landscape requires enterprises to rapidly deliver quality products and services to the market. This calls for implementing quality engineering solutions in the agile led SDLC. The key benefits are as follows:
Implementing AI: Quality engineering can involve Artificial Intelligence to accelerate and enhance their QA practices. AI can help in identifying glitches in the software applications based on analyzing historical data. It can help developers to focus on the specific areas of software development and prevent glitches from setting in.
Strengthening right and improving shift-left testing: The business priorities of today dictate quick launch of software products across social, mobile commerce, and cloud landscape. With Agile and DevOps forming the crux of any software development process and CI and CD being the expected outcomes, any SW quality engineer should do the following -
- Strengthen the delivery of high-quality products
- Enhance the feedback response mechanism.
- Make the sprint involving developers and QA experts seamless and responsive.
Improved agility: Enterprises need to implement Agile and DevOps methodologies to streamline their workflows, improve efficiencies, reduce costs, deliver quality products and services, and achieve ROI. An SW quality engineer can help enterprises in implementing industry best practices and facilitating the adoption of Agile processes.
Better monitoring: With the expectations of customers rising by the day, the success of any software application would depend on key parameters such as performance, accessibility, functionality, and security. However, these need strict monitoring of the development and QA processes. This is where a robust quality engineering strategy can ensure effective quality control and management by leveraging technology, measurable tools, and well-established industry standards.
Prevention is better than cure: Digital quality engineering involves drawing and implementing strategies to prevent glitches from sneaking into the SDLC. It aims at the long-term perspective of preventing glitches rather than getting into the fire-fighting mode every time glitches are detected. By doing so, it helps enterprises to speed up the software development and delivery process and reduce cost.
Implementing quality across the SDLC and beyond: With shorter delivery cycles and faster turnaround time expected of enterprises to deal with the changing market dynamics, the operational workflow needs to be strengthened and streamlined. QE services help enterprises in monitoring and executing a slew of activities - the adoption of new technology tools or automating the testing process. The software quality engineering services monitor the quality metrics and ensure they are met across processes in the SDLC.
Businesses need to become agile and quality compliant to meet the changing market dynamics and rising customer expectations. To achieve these objectives, the entire SDLC should be designed to uphold quality at every level by engaging quality engineering services.