The rise of quality engineering and assurance services

  • marzo 19, 2024
1437529_DCS_Revolutionizing_app_testing_Blog_420x250.jpg

Before a software-dependent product goes live, there are several challenges it must overcome. Random bugs can lead to long and delayed testing cycles, increasing the time to market (TTM). Manual testing can be error-prone and ineffective in resolving complex technical glitches. Software support teams functioning in siloes can bring about a sense of disarray between business line managers and app developers, making matters worse. Moreover, when application testing isn't preemptive in fixing errors, the damage done weighs heavily on the incurred costs and product launch schedule.

With modern development environments' speed and evolving demands, traditional testing methods can’t keep pace. Dedicated teams that focus on Quality Engineering and Assurance (QE&A) in application testing can prove to be a cure-all, improving the quality, functionality and reliability of software.

Companies with high stakes in software for business continuity and growth understand this importance. To deliver high-quality apps faster and more effectively, they are embracing the power of Cloud, Agile and DevOps application testing. The worldwide digital assurance market, which covers earnings from Agile/DevOps, Artificial Intelligence (AI) and Cloud testing services, surged from $4.9 billion in 2022 to $5.79 billion in 2023.

  • Breaking down the disruption
    The movement to the Cloud and Agile and DevOps methodologies has disrupted traditional testing structures, fostering a more integrated and continuous approach to development and testing.
  • Embracing the Cloud
    For scalable, on-demand and cost-effective testing architectures with accessibility to multiple tools and platforms
  • Incorporating DevOps
    For faster delivery, better quality and higher performance by bridging the gap between business line managers and software support teams
  • Adopting an Agile methodology
    For promoting an iterative and incremental app development cycle that pays heed to end-user experience through frequent feedback loops
  • Post-Agile maturity in software and IT
    For aligning business and IT operating models with concepts like ITIL v4, SAFe, DevSecOps, Value Stream Management and AIOps

The result is a fundamental shift in the way testing is performed and managed.

QE&A: Welcome to the new paradigm

Going above testing, QE&A encompasses the entire software development lifecycle (SDLC). Leading analysts emphasize the need to embed quality into every stage of the SDLC, from planning to deployment and beyond. So, how did you get there?

It begins with a dedicated team of developers and application testers who are continuously involved in:

  • Documenting and architecting code for future use
  • Automating testing to preempt bugs, saving time and costs
  • Prioritizing end-user feedback for enhanced user journeys
  • Using appropriate frameworks or open-source tech for efficient testing

The use of intelligent tools of automation tools can further enhance the efficiency of the QE&A process, transforming testing from a quality gate to a quality enabler. With a combination of machine learning (ML) algorithms, natural language processing (NLP) and computer vision, software development teams can augment human intelligence, generate test cases, identify defects and provide business improvement insights.

With the advent of generative AI (GenAI), quality engineering teams are ready to step into the next frontier of application testing. New possibilities are emerging for integrating tools to streamline the CI/CD or DevSecOps pipelines, optimizing test dependencies and enabling faster test execution cycles.

Here’s a breakdown of how leveraging analytics and automation, in combination with the latest advancements in AI, enhances testing capabilities and outcomes:

  • Comprehensive coverage: Algorithms analyze code to identify potential vulnerabilities, providing comprehensive test coverage. This involves building diverse test scenarios from real user stories and synthetic data — a role that is perfectly suited for the unique capabilities of GenAI.
  • Rapid test cycles: Automated test scripts are executed across various platforms and configurations, reducing human errors and making week/month-long testing cycles a thing of the past. Today, GenAI is helping enterprises modernize their test architecture faster than ever, enabling autonomous script migration from older to newer tech.
  • Proactive intervention: Continuous monitoring detects anomalies in real time, enabling proactive bug identification and rapid remediation. GenAI is especially adept at analyzing vast datasets to identify patterns and abnormal application behavior quickly.

This synergy of artificial intelligence and automation enhances overall software quality and accelerates development. It provides a robust framework for consistent, reliable and efficient software products. The result? Improved user satisfaction and faster time to market.

Quality Engineering Graphic
An illustration of the NTT DATA’s Quality Engineering Lifecycle (depicting the stages and processes involved in making sure data quality)

A closer look at QE&A strategies

Businesses can deploy a combination of strategies to get the most out of QE&A, aligning their business needs with software development practices.

  • Shift-left versus shift-right testing: Businesses must choose between conducting application testing closer to the source (left) or closer to the user (right). Shift-left involves early quality integration within agile practices, with an emphasis on automation for continuous improvement. On the other hand, shift-right involves quality initiatives in operations, with a focus on maintaining software post-deployment, addressing technical debt and responding promptly to issues through automation.
  • Continuous testing: This methodology automates and integrates testing across the SDLC pipeline, providing quicker delivery, heightened confidence in each software patch and release and reduced potential risks.
  • Performance and security engineering: To meet application and non-functional requirements, including performance, scalability, reliability and security, businesses must adopt security engineering practices. The outcomes range from enhanced user experience, minimized downtime, data protection and complete adherence to standards and regulations.

What does the future hold?

QE&A isn't a static concept, but a dynamic one that evolves with the changing needs and expectations of the market, the users and technology.

The road ahead looks exciting, with an imminent shift from traditional testing centers of excellence to competency centers with embedded testing in multidisciplinary teams that collaborate across the SDLC. The emphasis will be on greater adoption of cloud-native applications that leverage microservices, containers and serverless architectures, requiring new approaches to testing such as service virtualization, contract testing and chaos engineering. Additionally, an even more proactive approach to quality assurance is on the horizon - one which harnesses the potential of GenAI to anticipate user needs, preferences, and behaviors, using predictive analytics, sentiment analysis and user feedback.

Accelerate your quality engineering journey with NTT DATA

With the right expertise in Cloud, agile and DevOps methodologies in QE&A, organizations can completely revolutionize their application testing setup and reap the rewards. As part of NTT DATA Digital Application Services (DAS), QE&A delivers agile pre-production controls that provide stable and secure applications critical to smooth business operations.

A snapshot of our QE&A capabilities:

  • Test Assessment
  • Intelligent Automation
  • Regression Testing
  • System Integration Testing (SIT)
  • User Acceptance Testing (UAT)
  • Performance Testing
  • Load/Stress Evaluation
  • Usability and Accessibility Testing
  • Compliance Testing
  • Test Data Management (TDM)

It’s time to elevate the quality of your application services, drive continuous innovation and supercharge your digital transformation journey.

As a global leader in quality engineering, we can help you take the next quantum leap in your pursuit of modernization. We have a proven track record of delivering immediate and future benefits to clients by combining industry domain expertise with reusable automation frameworks, tools, and solution accelerators.

If you want to learn more about how QE&A can help your organization achieve its business goals, contact us today for a free consultation.

Subscribe to our blog

ribbon-logo-dark
1437529-Drew-Gregory-headshot.jpg
Drew Gregory

Drew’s previous experiences across a spectrum of IT services including multiple levels in leadership have enabled him to holistically drive connectivity between business strategies and IT solutions. Today, he leads NTT DATA’s Digital Application Services (DAS) offering including application management, application modernization, quality engineering and assurance, performance monitoring and observability, security, and portfolio management.

 

Related Blog Posts