What Are the Latest Trends in Software Testing in 2024?

Top Software Testing Trends in 2024

Codeless Automation Testing

Built on visual modeling and Artificial Intelligence technology, codeless automated testing allows QA engineers to test case scenarios without knowing how to code. Software testing technologies are on the rise, especially codeless automated testing. It accelerates the testing process by reducing the time that is spent on recurring test cases.

Some of the advantages of codeless automated testing are:

• Simple to review
• Low learning curve
• No wasted resources
• Effective

Machine Learning and Artificial Intelligence for Automation

Artificial Intelligence (AI) usage continues to grow in every facet of technology due to the number of apps that are making their way to the market. Machine Learning (ML) and AI technologies allow companies to improve their automated test strategies.

It is expected that more AI apps will be heading to the testing zone so that companies can keep pace with recurrent releases. Both ML and AI testing will be able to do this with the help of analytics and reports. However, ML technology is one of the latest trends in testing, a fairly new concept that is expected to grow over the years.

Things you can expect when both AI and ML technologies combine are:

• Test suite optimization
• Log analytics
• Defect analytics
• Predictive analytics

Agile Test Automation

This technique was born to be used in projects applying Agile methodology. With the ability to quickly adapt to changes throughout the software development lifecycle, Agile teams surely can achieve more superior quality and instant feedback through automated testing. By leveraging test automation using various test automation tools, Agile support teams are better able to perform recurring jobs, identify bugs, and test coverage, further resulting in quicker feedback loops and continuous improvement.

This method provides high test coverage in every sprint when working in Agile to help businesses save a great amount of time, manpower, and cost. This trend is gaining popularity and will be beneficial to companies to help their team optimize the testing process.

IoT and Big Data Testing

The Internet of Things is a fast-growing concept and will soon accept the 5G standard. By extracting large volumes of data generated every minute through IoT sensors and using them to serve testing processes, the testing industry has released several new gadgets and testing methods in the marketplace and collectively refers to them as “IoT and big data testing.”

The combinations for testing are numerous and allow for testing between devices, protocols, platforms, and operating systems. IoT testing focuses on evaluating the performance of IoT devices under various load conditions and is crucial for enhancing system reliability by preventing unexpected bugs or issues.

As the number of IoT devices increases over time, creating an increasingly open information network, IoT testing is expected to become increasingly popular, especially for businesses that use IoT technology as their main strategy.

The advantages of IoT and big data testing are as follows:

• Validate information
• Create data-driven verdicts
• Improve consumer targeting
• Address security vulnerabilities

Performance Engineering

The performance of an app can determine the success of a business, which is why performance engineering is needed. Any issues after the app is introduced into the market can cause millions of dollars in loss.

Most companies are now reconsidering their priorities and are taking a more consumer-focused approach on every stage of the SDLC. The reason for this is to solve and prevent any performance issues at the very beginning of the developmental procedure. This trend is the reason we have been seeing more frequent releases and shorter software development cycle of apps.

DevOps and Agile Testing Integration

The combination of DevOps and Agile is most preferred for several organizations because they are designed to favor swift deployment and strong teamwork between developers and QA engineers. While Agile is the go-to for development and testing, DevOps is known for the association of cross-departments. Together, they facilitate top-quality products at an impressive rate.

This trend reflects a holistic approach to testing that aligns with modern software delivery practices while maintaining high standards of customer satisfaction and product reliability.

Key benefits to this trend are:

• Provide faster time to market
• Increase productivity
• Identify bugs in the initial stages
• Enable quick feedback loops

Blockchain Test

Blockchain-powered services are the best fit for progressively leading enterprises worldwide. Providers in the automotive and financial field may need to store a ton of data securely and need to use blockchain technology.

However, this may come at a price as blockchain testing comes with the highest adoption costs, privacy, and compliance issues just to name a few. It is a complicated procedure that includes, encryption, decryption, validation, and transmission of heaps of data.

Cybersecurity and Risk Compliance

With higher cybersecurity threats present, businesses are putting security testing at the top of their list to ensure the safety of their data. It is of utmost importance to perform security testing on a company’s system, network, applications, and software to guarantee that the data is safe and has no holes, code errors, or leaks.

As one of the latest trends in testing, security testing reduces the damage associated with cybercrime. Companies large and small are all targets so it is better to be safe than sorry. Security testing can secure data as well as money and will continue to be a priority as long as cybercrime continues to grow.

Benefits of security testing include:

• Secure data and money
• Catch weak points before attackers
• Fix any error or leaks susceptible to attacks

Digital Twin Models

The biggest challenge with traditional testing methods is the inability to predict unexpected events and accurately mirror real-life situations. This is why digital twin models are expected to become more popular in the near future, as they can bridge the gap between simulation and reality.

How? Digital twin models allow the development team to create digital replicas of software applications and conduct testing right in those virtual spaces without impacting the actual production system. Because these controlled testing environments mimic the characteristics of the app’s real-world counterparts, testers using digital twin models easily assess how the software functions under specific conditions, thereby gathering valuable insights and improving predictive capabilities.

QAOps

Quality assurance engineers and software testers are involved in each stage of the SDLC instead of being restricted to software testing. QAOps seeks to bring operations, testers, and developers together to guarantee the best end product.

DevOps as mentioned before cuts down the SDLC time and allows teams to fix bugs, build features, and push regular updates. QAOps strengthen the communication between developers and testing engineers by including software tests in the Continuous Integration and Continuous Delivery pipeline.

QAOps is not only for large tech businesses as this practice can be scaled high or down to fit companies of any size and can be defined in 2 main principles:

• Quality assurance actions are integrated into the CI/CI pipeline.
• It provides QA testers and software developers an opportunity to work together through the CI/CD process.

Autoscaling CI/CD Runners for Supporting Parallel Tests

To fast-track the software testing cycle, test automation is the one method to save time and effort. However, to get faster results and maximize profits, DevOps testing groups will look to auto-scale CI/CD runners to match the speed of Agile.

The parallel test provides the opportunity to run a test script over multiple test environments at the same time or test multiple test scripts simultaneously. Auto-scaling runners will seek to handle trouble with several servers to handle queues in a professional manner in the event of parallel testing.

Robotic Process Automation

Robotic Process Automation (RPA) tools cover a wide area in the QA and software testing sector. RPA reduces the time it takes for software testing which in turn leads to reducing funds. It helps companies to perform more comprehensive tests to retain high stability.

Companies can integrate this trend almost immediately since the cost is relatively low and requires no out-of-pocket investments. Artificial Intelligence and the software testing ecosystem have seen improvements that pave the way for RPA.

AI, IoT, Cognitive Computing, RPA, and ML all seek to transform sectors and reinvent the business process management side of things. One trend that is going to rise and be in great demand in 2024 is Hyper automation. Hyper automation reduces human involvement in digital and physical tasks by combining AI, RPA, ML, and business management software.

Mobile Application Automated Testing

As the name suggests, mobile application automated testing does not need much description.

Almost everyone has a gadget in their hands today, so the need for apps is growing rapidly. Millions of apps are listed on different operating systems on a day-to-day basis.

Mobile application software testing will always be in demand as the mobile app market grows. Smartphones are becoming more powerful and capable of performing many other tasks to meet distinct user needs. For this reason, more comprehensive testing needs to be done for these complicated apps.

Shift-left Testing

Realizing the undeniable importance of product quality testing, businesses regardless of size are increasingly focusing on software testing at every stage. The rise of shift-left testing proves this.

Instead of testing taking place at the end of each development process, shift-left testing advocates for a proactive testing mindset that prioritizes early defect detection. By moving all testing activities “to the left” of the timeline, which means testing is conducted earlier in the software development lifecycle, the shift left testing approach helps developers detect and resolve bugs as early as possible before they leave behind.

The shift left testing process often takes place throughout the development cycle, starting from the requirements phase and continuing through design, coding, and integration stages for improved software quality, better test coverage, continuous feedback, and a faster time to market.

You can use cloud testing platforms like LambdaTest to support shift left testing processes.

User-centric Testing Approaches

Software products are born to serve the needs of users in a specific aspect of life. A product without users is a product that does not bring profit. User centric approach first introduced also with this ideal. So how do we ensure that the product meets the correct end user usability requirements? Yes, conduct a testing approach centered around the customer, or what we call using user centric testing methods.

User-centric testing approaches focus on evaluating software product quality through the perspective of end users to ensure that the final product meets their expectations. These kinds of approaches may start from defining user personas representing the target audience of the software application, to assessing customer attitudes towards different versions of features through user surveys, interviews, and feedback sessions, for example.

Regularly performing customer-centric testing activities helps your business improve user satisfaction and increase adoption rates and product success in the market.