Continuous Testing: Perfect Software Is Not the Goal
Because who knows what ''perfect'' software even is?
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In a recent article for VanillaPlus — a leading publication covering digital transformation in the telecom industry — Tricentis CMO Wayne Ariola remarked, "Businesses don't want, or need, 'perfect' software." Never one to shy away from — or to fail to back up — bold statements like that, Ariola goes on to point out that what businesses truly need in order to avoid disruption is "the ability to deliver new, business-differentiating software as soon as possible," and to be able to do that continuously.
For many, that's no small feat, nor is it any easier than delivering whatever "perfect" software is, if that's even possible.
But as Ariola points out earlier in the article, "Continuous everything" is the mantra of today's most successful enterprises. Continuous integration, development, delivery, deployment — teams are leveraging modern processes, methodologies, mindsets, and toolchains to achieve these distinctions, but it's becoming increasingly clear that none of them are maintainable without the adoption of a relative newcomer: Continuous Testing.
At Tricentis, we define Continuous Testing as:
The process of executing automated tests as part of the software delivery pipeline in order to obtain feedback on the business risks associated with a software release candidate as rapidly as possible.
We're hardly the only ones claiming that Continuous Testing is a requirement for success today; a recent report from Forrester, " The Definitive Software Quality Metrics for Agile + DevOps " details how Continuous Testing has become a key differentiator between DevOps "Leaders" vs. DevOps "Laggards." However, while 57% of CXOs believe that their organizations follow the top Continuous Testing practices, only 26% actually do.
Ariola also describes how test automation, while certainly a critical component of Continuous Testing, "is not sufficient on its own." Continuous Testing absolutely requires scaling your test automation rates, but it also requires applying service virtualization, stateful test data management, and exploratory testing throughout the software delivery lifecycle.
Published at DZone with permission of Noel Wurst, DZone MVB. See the original article here.
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