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Lack of Agility in App Testing: How to Shift Left and Improve testing Efficiency in AI era


In today’s digital world, companies need to build apps quickly. But testing apps can take a long time and isn’t very easy. One big reason is that testing happens late in the app development life cycle and teams don’t work together or lack team collaboration, and too much testing is done manually.

This blog post will explore the reasons behind the lack of agility in app testing, discuss the shift left strategy, and examine how it can improve testing efficiency, particularly when combined with the power of Artificial Intelligence (AI).

Reasons Behind the Lack of Agility in App Testing

1. Late Testing

Testing during the later stages of the app development can result in significant challenges and expenses. Identifying and fixing defects becomes more difficult, which leads to project delays and increased costs. Let’s consider an e-commerce app as an example.

Let’s assume we are testing an app feature on searching an order and completing the payment. If testing is postponed until the end of the development cycle, critical issues such as broken search functionalities or malfunctioning payment gateways might go undetected.

Late Testing

Addressing these problems at this stage can consume more resources, delay the app’s release, and potentially harm the company’s reputation. Incorporating testing earlier in the development process not only ensures a more stable and reliable product but also saves valuable time and resources.

2. Siloed Teams

When developers and testers on an e-commerce website work in separate bubbles without communicating, it’s like chaos. For instance, developers may not know what testers need to check, and testers might miss key information from developers. This lack of teamwork and collaboration delays finding and fixing bugs, making the payment feature less reliable.

3. Manual Testing

Using only manual testing in app testing is slow and tedious, and mistakes are more likely. Also, manual testing isn’t good at finding tricky problems that automated tools can catch easily. Apps often change a lot, so performing tests manually takes a long time. That’s why automation testing is important—it’s faster and more reliable.

What is the Shift Left Strategy?

In simple terms, the “shift left” strategy means moving tasks or activities earlier in the development process. It’s like moving something from the right side of a timeline to the left side. In software/app development, “shift left” refers to performing tasks such as testing and quality assurance earlier in the development cycle rather than waiting until the end. Instead of testing only after the software or application is fully developed, the shift left approach involves testing and addressing issues as soon as possible, even during the initial stages of coding. Here’s how it works:

1. Early Testing

With the shift left strategy, testing starts early in the development process, even before the code is fully written. This includes testing individual components, modules, or features even before the entire application is built. Conducting code reviews and peer reviews regularly can help greatly. Having another set of eyes to look at the code can help identify potential issues, bugs, or design flaws early on. This helps us catch any problems sooner, making it easier and less expensive to fix.

Early Testing

2. Collaboration

In shift left strategy, testers and developers work together right from the start, just like working together. Let us assume the feature under test is Payment, testers share ideas about how the payment feature should work, and developers use that feedback to make sure the feature works smoothly. This teamwork makes the payment feature better and the app more reliable in the end.

How Shift Left Strategy Can Improve Testing Efficiency ?

1. Early Detection

Identification of defects  in the early phase of the app development lifecycle saves time and money. Imagine you’re testing a payment feature, and you notice a mistake in the card usage during the early phase of development. Fixing it at this stage is easier and quicker than waiting until all the payment features with the payment methods like debit card and credit cards are rolled out.

2. Collaborative Environment

Shift left encourages teamwork between developers and testers, like when friends work together on a group project. When everyone pitches in from the start, there’s better communication and understanding. For example, imagine building a sandcastle with your friends. If you all plan together and work side by side, the sandcastle turns out stronger and better. Similarly, when developers and testers collaborate from the beginning, the end product, your application comes out more efficiently and reliably.

2. Collaborative Environment

3. Automation

Automation testing reduces the manual efforts and helps in saving time for the QA team. Automation testing tools can help run tests quickly and without mistakes. For instance, imagine an automation script that can test the payment features with different sets of test data across all the payment methods in less time and with high accuracy . That’s what automation testing does—it speeds up the testing process and reduces the chance of human errors, making testing more efficient.

How Can AI Help in Testing Efficiency ?

AI, or artificial intelligence, can make testing faster and more accurate by handling repetitive tasks, finding patterns in data, and making predictions. Let’s explore how AI can help testing become more efficient:

1. Test Case Optimization

Imagine you’re testing a payment feature in an app. You want to make sure every test you run is useful and necessary. AI algorithms can look at past testing data to see which tests are needed and which ones are not. It’s like cleaning out your test suites and getting rid of test cases which are redundant. This makes testing faster and more efficient because you’re only focusing on the tests that really matter.

2. Defect Prediction

Imagine you’re testing a payment feature in an app. AI is like having a detective that can predict where problems might pop up. AI analyses changes in the app’s code to identify any possible issues. This helps developers fix problems before they become major headaches, saving time and effort in the end.

3. Visual Testing

Imagine you’re testing a payment feature in an app. It’s like comparing two photos to see if they look alike. Sometimes, it’s hard to spot the differences. But with AI-powered image recognition, finding those differences becomes a breeze. Similarly, in testing, AI can quickly check the visual parts of the app, like buttons and screens, for any issues. It’s like having a super-fast assistant who can spot any visual problems in the app. This saves testers a ton of time and effort, making testing much easier and faster.

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Using the shift left strategy and AI can change how companies test apps. It makes testing faster, leading to addressing the lack of agility in app testing.

By breaking down silos between teams, adopting automation, and integrating AI-driven solutions, organisations can ensure that they remain competitive in today’s fast-paced digital environment. By working together and using smart tools, companies can stay competitive in today’s fast digital world. So, let’s work together and make great apps!

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R Dinakar

Dinakar is a Content Strategist at Pcloudy. He is an ardent technology explorer who loves sharing ideas in the tech domain. In his free time, you will find him engrossed in books on health & wellness, watching tech news, venturing into new places, or playing the guitar. He loves the sight of the oceans and the sound of waves on a bright sunny day.

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