Leading quality engineering into the New
June 22, 2018
RESEARCH REPORT
What’s in this article
What’s in this article
- Accenture is evolving testing into a pervasive, real-time, and insight-driven quality engineering function, augmented by AI-led autonomous frameworks.
- In this paper we explain how across five dimensions—data, frameworks, process, technology, and the organization—testing will shift away from the traditional approaches towards new ideas and new methodologies fit for the application engineering world of tomorrow.
- Learn more about some of our innovations (protected by 250+ patents and pending patent applications) and our quality engineering vision to help clients be future ready in an increasingly complex technological environment.
Traditional approaches to application testing are being disrupted with the advent of DevOps and intelligent automation. Delivery timeline expectations have shrunk from months to weeks.
Today, testing has shifted both left and right in the software development lifecycle and evolved into quality engineering, starting upfront as part of the initial application planning and establishing a continuous feedback loop to anticipate and act on the unknown. It will continue to evolve further as we move towards AI, edge computing and IoT in this increasingly complex technological environment.
"We need a new vision for the quality engineering function—one that positions quality engineers to be catalysts for speed, agility and business performance while achieving radical productivity."
– KISHORE DURG, Senior Managing Director, Growth and Strategy Lead – Accenture Technology
Accenture has long been at the forefront of testing innovation. We are leading our clients into the new world of quality engineering at scale. Download our new report, "Quality Engineering in the New," to learn more about our vision for the future of quality engineering and discover the unique patented and patent-pending innovations we have developed to improve the way businesses operate.
"More than 50 percent of software development effort is spent on testing today. Machine learning, analytics and automation can help reduce that significantly."
– SANJAY PODDER, Managing Director, Software Engineering R&D Lead – Accenture Labs
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