Why Continuous Testing

They say software is not released; it is allowed to escape.

Huh! What if we could turn that joke into a wake-up call? What if we can make software that catches the user-angle from the word ‘go’?

Just a couple of years back, this may have sounded like fiction, but the advent of Continuous Testing has turned that what-if into a reality; thus, filling a big void.

A sturdy, nimble, and end-to-end testing ecosystem is made possible and powerful by injecting the elements of Continuous Testing. This is a model where testing is embedded as a natural and inherent constituent in the entire software delivery lifecycle.

It makes the road for better, faster, dependable and user-oriented software smooth and easy. With this model, long-running barriers between loosely-coupled user requirements and sloppy code development can be finally erased. And with that, a significant extent of unpredictability, and pressures of the modern-technology world and its inhabitant users can be navigated better.

How to get started?

This model has its underpinnings in the integration of Agile Development philosophy up till QA and Testing — leading to that quintessentially-continuous thread throughout the development cycle. Here iterative QA can commence from the very beginning by embracing sharp requirement-definition in every small step of the development process. This also helps in addressing resolution of change in user needs so that defects and misalignment with user’s context are wiped away.

This is attained by attacking some inherent flaws and limitations of traditional testing where delays are inevitable, defects pop despite the tester’s best efforts and testing is usually relegated towards the end of the cycle. Here’s how yesteryear gaps are plugged with a radical-but-savvy approach.

Be Smarter With Requirements

Active requirements gathering is an essential preamble for making Continuous Testing effective and prolific in a complete sense. There is a pronounced need here to capture the desired user functionality precisely and contextually. It has to be also done optimally and iteratively. Creation of test-cases has to be accomplished with an optimisation-focus and if one needs even the smallest set of test cases for validation of the desired user functionality — so be it. The same rigour should be applied to self–service data provisioning, maintenance and traceability. It is crucial that all dimensions, ramifications, design changes, the user stories, test cases, data and end–points are incorporated well.

If actual user-behaviour is not reckoned for sufficiently, then scalability and stress stop being mere words on paper. They assume a new proportion altogether, so requirements should be accorded their due attention and meticulousness all the time, and well in time.

Practice Test-Driven Development

We cannot deny how functional, regression, user journey and performance tests — and for both applications and APIs — eventually etch their stamp on how the UI should be designed. To wait until after the UI is done, obviously, is a chasm that becomes laden with costs and sloppily-constructed user interactions. Not to forget — the most important aspect that gets damaged when we use UI as a footnote — scars on customer experience.

By adopting a smarter approach to both developing and testing with a ‘continuous’ mindset, one can accomplish:

  • Cutting down on unnecessary and frequent testing of the same functionality.
  • Control over insufficient/out-of-date/production-used/ sanitised test data and scenarios; inadequate test-case definitions; thus equipping testers with the right data for execution of tests.
  • Systematic provisioning of data to testers; and hence eliminating time-taken, cross-team dependencies.
  • Better visibility, data-reporting and tracking (otherwise testers request through rudimentary ways and central teams provision and process these data; that spirals into delays, dependencies and gaps).
  • Availability of production-like environments for testers; instead of a limited number of shared-environments and costly-cum-insufficient pre production infrastructure weighed down by weeks of configuration time.
  • Complete access to unfinished, back-end and composite application related third-party components.
  • Use of service virtualisation to avoid unavailability of components.
  • Tapping automation for short-iteration-intensive areas like regression testing.
  • Presence of all-time testing processes to tackle small chunks of code developed in bursts as well as verification of subsequent code changes.
  • Involvement of QA at a deeper, proactive, more-advisory and stronger level with development instead of letting them ring bells way later in the software process.

Test Automation

The outcomes and quintessential impact of Continuous Testing become possible when testing is embedded well in the overall software delivery pipeline. Here, a well-rounded, well-wedged harness and automated test frameworks come into the picture. They should be easy and ready to deploy for amplifying the process and lifecycle practices well.

The need for automation elevates when we take into account the frequency of builds and code that would surface and delay the development flow. That defeats the very purpose of Continuous Testing. Use of automation tools alone is not enough — their choice, visibility, consistency, holistic ease between various tools, the versatility of formats, update-issues, integration issues, availability of test data or environmental factors that can ruin or augment the whole exercise — everything plays a role.

Happy ending

A Continuous Testing model not only helps in injecting strengths and agility in software; but also manages to attain:

  • An accurate reflection of user needs.
  • Optimum foothold on nooks and corners that conventional testing misses out on.
  • Coverage of even the most-latent scenarios of failure.
  • The pace with today’s time-intensive delivery cycles.
  • Shrinking number of defects and post-delivery penalties.
  • Better efficiency-metrics.
  • Stopping gaps that perpetuate owing to poor requirement-definitions.
  • Removal of monolithic and isolated approaches to user-documentation.
  • Ability to address many layers of complexity and numbers of test paths.
  • Scalability.

The pressures on software creators, systems and people around them are only going to mount new levels every day. The ability to be up-to-speed with the changing world of testing and integration will manifest in new and relevant strengths, and hence, as the topmost choice for supersonic users.

Software should be not just made with pride, but released with confidence. There is a difference between software and cripple-ware. Let that difference not escape your eyes and desks.