Software Testing Trends | Mammoth-AI

Today every company is a technology company.  Under this premise, we all need to watch the advancements made in the tech industry.  Failing to keep pace will allow our competitors a distinctive advantage in the race for market share and customer delight.  As we live in a time of extraordinary change driven by technology and the digital revolution, the world of software testing is at the centre of these forces.  Here are 7 critical Software Testing Trends that one should watch out for in 2020. 

Agile And DevOps 

Organizations have incorporated Agile as a response to quickly shifting requirements and customer and consumer demands.  To keep pace with the change of continuous development, integration and deployment, a discipline called Development Operations, or DevOps has evolved to meet the demand for swiftness. DevOps includes practices, instructions, procedures, and tools that aid in the orchestration of operation activities for code development. This reduces the time from development to operations for a software.  

DevOps has turned out to be an effective model for organizations that are looking to shorten the software lifespan – from conception to development, delivery, test and deployment.  The implementation of both Agile and DevOps models has fast become the adopted approach to deliver quality software sooner; in some circles also known as “Quality of Speed”. This approach will only accelerate in the days ahead.   

To execute DevOps practices efficiently, software teams cannot disregard test efforts as a client or consumer-facing bugs can have a significant impact on business agility and, in the case with the latter, financial performance. As test cycles add significant time delays to productions release, many dev shops tend to curtail test coverage. However, they do so them moment peril starts knocking. 

Enter the surge to implement automation into the testing function. While not new to the software lifecycle, test automation has gained significant momentum. As development cycles have shortened and faulty code released into production has garnered headlines. A good example is the US Government’s debacle of 2013.  To keep pace, software shops are looking for anyplace to add automation to their operations and testing is a juicy place to take a bite. 

API And Services Test Automation  

The demand for greater feature, functionality and speed have necessitated the proliferation of application integration (API) and web services. Of course, the need to test these integrations is swelling alongside. As with general automation testing, the trend for API and services test automation will only continue to grow. 

Perhaps outdoing functionality testing on user interfaces handled by end-users.  The unique nature of each environment will challenge automation efforts in this area. But it remains an open opportunity for IT organizations across the board. 

Artificial Intelligence for Testing  

Applying artificial intelligence and machine learning (AI/ML) tactics to meet the challenges in software testing is a greenfield opportunity. The redundant nature of testing opens a lot of opportunities to use AI/ML in testing. Nevertheless, the use of AI/ML in testing is still in infancy. And, challenges around the cost of computing power must be addressed. Furthermore, AI/ML processes are industrialized to produce improved test cases, scripts, data, and reports. Predictive models may steer dev shops about what, where and when to test. Additionally, smart analytics can offer visibility into root causes, test coverage, and high-risk scenarios.  Look for AI/ML utilization in addressing difficulties such as:  

  • Fault classification and assignment 
  • Quality prediction, and  
  • Test case prioritization 

The mobile apps are a face-to-face interaction of our businesses to internal clients. As well as, external partners and customers in general. The needs to test these platforms with speed, agility and accuracy, has never been more critical. Nevertheless, the current acquisition of mobile test automation is limited. Shortage of tools and solutions that do address key areas in need of test at

  • Scale,
  • Functional,
  • Performance, 
  • Load,
  • Penetration, etc.

The need for automated testing for mobile apps remains an opportunity. And, one that industry players and startups are seeking to solve.  We have our odds-on favourite in Appvance’s AIQ.  If your firm is looking to solve this hurdle, give us a call to discuss and demo. 

The proliferation of Edge Computing (the Internet of Things or IoT) adds an additional wrinkle for dev and test teams. Being able to simulate test scenarios at scale. Especially, the vast amount of data collection always at the end. The demand is going to rise for a novel approach. Progress is in motion for presenting and using cloud-based, containerized test environments. Leveraging AI/ML to simulate test data and the growth of data are some solutions for the absence of test data.  

Clearly, with all the challenges, hurdles and opportunities the choice is limited. Smart thinking is to harness an enterprise Test Solution platform, as well as that is also able to:

  • Easily interoperable with DevOps frameworks,
  • processes and solutions

To maintain a smooth and well-orchestrated model – It will take intelligent systems. And, processes that leverage the best trends – and employ and demand.  Such solutions are built with continuous integration. And, continuous delivery in mind from the ground up – allowing development teams to execute with agility and quality. Let us know what you think if these Software Testing Trends. And, if you’ve incorporated any of these in your business model.

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