The introduction of innovative technologies has brought the latest updates in terms of software testing, development, design and delivery. Cost optimization is a top priority for companies around the world. In this case, most IT managers believe in integrating the latest IT technologies into their organization. Digital transformation is another important goal for industries and companies outside of the cloud and business analytics.
Automated practices have also become mainstream, allowing for flawless testing practices.
Furthermore, artificial intelligence and machine learning seem to have reached a new level.
Big data testing today is all about testing data, so the internet can be the center of things. This is a priority for which all software testing companies should be treated with caution. Particular attention is paid to factors such as reliability and quality, which reduces the number of software bugs and improves the security and performance of the program.
Changing trends in program testing also has a significant impact on program testing and quality assurance. Companies have increased budgets for testing programs, especially in the service, transportation and energy sectors. Companies are now unveiling their tests, formerly Program Lifecycle (SDLC), which use test methods such as Agile. It also includes the operation of T-European agencies with a test mechanism for constructive business development issues, all organized into commodities.
Some organizations also hire independent testing companies to meet program requirements. In this mode, they pay less for commissions and tests and no longer need internal resources. There are many other important trends in the field of quality assurance and software testing. Therefore, all software companies must adapt to the latest trends in testing around the world, which will help them adapt to the needs of today’s developed world. This article will help you explore the most popular trends to watch in 2021.
Software test: “Technologies of the future”
The program scenario checks for changes in the scenario. The latest trends are more suitable than ever for businesses and seasoned professionals, because modern users live forever and need what’s available. Just as the number of programs used by organizations does not increase and security costs increase, so much attention is now being paid to test programs, and for better reasons.
According to the World Quality Report, 60% of companies cite cost as the highest testing problem. Total test budgets are increasingly distinguishable from software sources and production budgets. Quality control will continue to be integrated into development work, in part through increased skills such as continuous testing and DevOps. As a result and direct impact, more and more companies are beginning to appreciate the value of quality assurance by trying to test software and quality assurance consultancy to assist them in this particular task.
Although AI is a useful tool that makes test automation and operational quality assurance tools generally more efficient, it does not meet the requirements of experienced test experts who can produce a cost-effective, high-quality test solution . Plus, testing users with the right people remains an important factor in ensuring your product works, is valuable, and easy for your customers to use.
1. Non-coded automatic test
The increased use of decoded testers is a major trend in the case of testing in 2021, which is remarkable. Decoded testers are created with advanced artificial intelligence technology, and visual modeling allows you to create test guides that provide faster automated testing. With these tools, IT staff can create simple test cases without knowing the code and reduce the time spent on repetitive test cases.
Some of the main advantages of decoding tests are efficiency, ease of analysis, low learning curve and saving of valuable resources. Basically, all of these factors combine, which means that in the case of unencrypted test automation, you don’t need to test the automated test frameworks or the technology that the program primarily relies on to test quickly. On the outside, the road to success through automated testing seems feasible. Automated testers based on a visual approach such as selenium also offer an opportunity for non-programmers. Over time, other features have been added such as RC, IDE, network management which have increased its importance and value. Selenium IDE technology was created by people who didn’t want to do any coding. Selenium currently supports multiple programming languages such as Python, Java, Ruby, C # and others. This allows them to create, manage and run automated tests on their own without having to learn to code.
How do uncoded self-tests work?
The decoded self-test is the same as the decoded software test. The basic principle of automatic test decoding is that no code is required to create a test. Since there are many
decoded test automation tools on the market, Frontend has a variety of resources to make them work. For them, the most common is the image transition from the UI to the machine, which means the background code to use at the end.
For example, in a tool like Testsigma, test cases are written primarily in plain language, such as English, using NLP. These reports are converted into (return) code for execution.
Below are some of the more popular test vending machines that use decoded test methods to enable automation of test cases:
- TOSCA: This amazing Tricentis instrument uses a model-based testing method. Previously, test creation was tied to a test schedule template, test data, and test cases. Here, too, some program changes are automatically corrected.
- test.ai: This is one of the most popular automated tools that automatically tests your mobile app for user experience. No coding or maintenance is required here. It works with the program’s artificial intelligence, after which it automatically generates test cases; Run them to produce results relevant to the user experience.
- Ranorex: This tool offers several solutions in one amazing function to make the recorder easy to record and play.
- Ghost Inspector: Every move of this tool can be created without coding. The tool makes it easy to verify that your site is functioning correctly.
- TestComposed is ready – a special smart bear tool that uses keyword testing automation instead of code.
- Machine learning and artificial intelligence for machine use
The use of artificial intelligence is expected to continue to grow in nearly all areas of creative technology as the number of programs we use on our connected planet increases. In North America alone, current investments in artificial intelligence are estimated at $ 6-7 billion. By 2025, global investment in artificial intelligence will be $ 200 billion.
We expect AI witnesses in several test areas, most of them for analysis and reporting:
Test suite optimization: Identify unnecessary and unnecessary test versions and delete them.
Log Analysis: Find exceptional test cases that require manual and automated testing.
Error Analysis: Identify program areas and defects related to business risk.
Proactive Analysis: Evaluates key parameters and configurations of end-user behavior and identifies areas of the program to focus on.
Test Report Confirmation: Get keywords from Demand Tracking Matrix (RTM). Program testing and quality control teams can use machine learning (ML) and artificial intelligence (AI) to improve their automated testing techniques and keep up with repetitive posts, learning and reporting. For example, software testers can use artificial intelligence algorithms to identify and prioritize the scope of automated testing. In addition to controlling test loads, the program allows artificial test programs to optimize test sets by identifying unnecessary test cases and verifying RTM keywords.
The column where the smart machine is located is ML. According to Capgemini’s Global Quality Report, 38% of companies expect to complete machine learning projects by 2019. Business experts predict that the number will increase next year. While mirroring end-user behavior patterns is always a difficult task for intelligence, predictive analytics of machine learning can improve human intelligence by detecting components that have not been studied in programs. This information can be used to predict likely parameters of user behavior using available historical data. Although testing machine testing software is an electrified prospect rather than a widely accepted practice, we can expect analysis-centric ideas to accelerate identification of potential in the years to come.
3. Automated testing in agile teams
Test automation is the only method that allows you to properly test the high coverage of each test and provides the best quality, immediate response and responsiveness we seek when working in Agile. Without self-testing, the Agile project will gradually become a waterfall project. Automated testing dominates when 44% of IT companies automate at least 50% of all testing in the last years 2019-2020. We believe the introduction of test automation in 2021 will steadily increase.
According to a recent report by MarketsAndMarkets, “The size of the global test automation market is projected to increase by 18.0% with a CAGR (Composite Annual Growth Rate) of 18.0% from $ 12.6 billion in 2019 to $ 28.8 billion by 2024. Automated Testing Support teams for repetitive and consistent feedback and test coverage make it easy for companies to save huge human resources, time and costs by integrating test automation into their assurance processes. quality.
According to a Gitlab study, automated testing is becoming more and more popular, and 12% of companies have fully automated testing capabilities. These cutting-edge trends in automated testing make quality control highly productive and help teams detect errors early on, complete repetitive tasks, provide ongoing feedback, and cover testing.
4. Add a requirement for big data testing
Industrial companies continue to process huge amounts of data and various data. Extracting the amount of unstructured or structured data defined as big data requires end-to-end testing. Big data testing helps you make more accurate decisions by examining accurate data and improving business strategies and marketing goals with new decisions in this big data analytics.
According to MarketsAndMarkets, the overall value of the Big Data market is estimated due to the increased use of IoT devices in enterprises and higher government initiatives to accelerate the use of digital technology. Increased reliance on data at the core of each vertical zone requires successful big data testing to ensure the integrity, accuracy, reliability and quality of the data needed to make informed decisions for all businesses. In particular, data testing helps make decisions about the range of services and products that are used and analyzed in order to provide companies with relevant information.
5. Efficiency techniques
As the number of platforms for any app indicates a fast-paced market, the customer experience boosts trust. It’s a powerhouse for rapidly changing needs, shorter development times, and more often emissions.
In response to this trend, IT and software companies began rethinking their priorities, with SDLC focusing on consumers every step of the way by focusing on quality standards, primarily to solve and avoid potential problems. life cycle. As a result, the performance test objectives, such as program stability, scalability, and speed in various situations, have been modified to assess poor performance and underlying system knowledge in the development method.
When done correctly, the design enables performance designers, testers, and programmers to create the performance metrics required by the initial design. Because corporate culture is not a set of skills, performance strategies require teams to run scripts to explore all parts of the system, count customers, and evaluate the business.
The effectiveness of any program can have a significant impact on an organization’s results. Each crash can cost thousands of millions of dollars, even identifying the source of an error in an increasingly complex system can take time. This in turn means that a seamless user experience and app performance needs to be incorporated immediately throughout the life of the app, not just when it is first launched. As DevOps teams continue to use the software, performance engineers need to be tested regularly to ensure the stability and quality of the integration.
6. Cybersecurity and response
The new digital world has its own challenges, including cyber attacks and dangers. Therefore, the new generation is dependent on the digital lifestyle and security testing is becoming more and more important. The product, network and application must be adequately protected from cyber attacks and various risks. Secure code practices will be used in 2021. Attacks on the network can take any form, both by the user and by the server. Security testing has become important today, not only in transaction and money management applications, but also to protect end users. By 2021, we can expect an increasing number of cyber attacks and we should all be prepared.
7. Automatic testing of mobile applications
This trend does not require much explanation. The use of portable devices and applications is ever increasing. Millions of different mobile apps are listed in the operating system repositories for various operating systems. Larger and more advanced applications have been developed to meet the diverse needs of customers. Extensive testing is required. Therefore, the growth in mobile phone test automation will continue until 2021.
8. Key Testing Tools
Testing tools play an important role in the software process. Testers and inspectors should review and modify the source code of the software. Personalization allows teams to work more efficiently, creating a smooth learning curve for new testers and more specific project requirements. The use of open source tools in software testing will increase in 2021. This will make testing unique, innovative and experimental. Each test tool in 2021 is expected to include a robot, Cypress and JMeter.
9. Apply the penetration test
More and more IT companies have begun to test deployment. Penetration testing helps identify software product deficiencies before a product is released to market. Penetration testing also works for APIs, microservices, and backend systems. The need to reduce security vulnerabilities is increasing and will continue until 2021.
10. Internet test (Internet of Things)
The Internet of Things (IoT) is growing with recent technological advances. In IoT, testers should be aware of the opportunities to test and assess all risks and threats by publishing an IoT-based tool. There is a need to develop simpler processes to replicate and reduce problems in a timely manner. Security, usability, device compatibility, data integrity, performance, and scalability are at the heart of IoT testing. According to the study, the growth of the Internet of Things is significant, as are the related reviews. The IoT test should not be ignored in 2021.
software in the future
To improve the marketability of a product, many companies pay special attention to quality and rely on professionals who work in company testing programs. The solutions offered by these companies will help you find fast resources and software testers or quality assurance engineers who are mature in performance and application technology. The number of independent studies is expected to increase in the coming decades. Focusing on safety and automated testing can also be a smart move. In 2021, as the impact of your business evolves, it may be best to re-teach quality control for the user experience and build it according to DevOps and live best practices. In order to deliver products quickly, it is best to consult independent programs so that companies can be tested.
These are the latest trends in testing that are very useful for organizations and companies. Whether you are a testing company or a quality control expert, you need to master the software testing trends mentioned above to stay competitive and in an ever-changing industry.