Software Testing and Artificial Intelligence: AIs Influence on the SDLC

Introduction

In the ever-evolving landscape of technology, the use of Artificial intelligence (AI) has been making increasing waves in our industry for quite some time now. It has been integrated into various processes, from customer service to data analysis, and now, it is making its way into the Software Development Life Cycle (SDLC). As AI continues to evolve, its impact and usefulness in software testing is becoming increasingly apparent. In this article, we will dive into the world of software testing and Artificial Intelligence, its current state, and how it will affect the SDLC in the near future.

A Closer Look at Testing Lifecycle and Key Terms

Hello fellow LinkedIn readers and welcome to thoughts of the day. As a child, I would often engage in word puzzles, anagrams and then later learning testing material we used mnemonics to remember things.

As a spin off at my tea-break, I wrote down the word ‘testing’ and reeled off some key terms that feature heavily in testing. All for some light-hearted reading based upon my many experiences over the years.

Why do you test so late?

Common problems I’ve seen during my career (if that’s what you could call this collection of happy accidents), are situations where a project's timelines are placed in jeopardy because testing takes longer than expected; or the scope expands after the requirements are signed off, usually after testing starts.

Now, there may be situations where this is a genuine occurrence. Requirements change, possibly regulations change. Availability of resource may change.

Phases of the Software Development Life Cycle

You’re probably familiar, to one extent or another, with the Software Development Life Cycle (SDLC). You may not, however, be familiar with the SDDC approach to software development. Although, I can almost bet that every person reading this blog has either used it or has purchased software from someone who does.