How Can Artificial Intelligence Help Game Testers?

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by Mit Thakkar | December 10, 2020 | Game Testing | 0 Comment |
How Can Artificial Intelligence Help Game Testers
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Artificial Intelligence has been a buzz since the 1900s and it still holds the hype around the world. Over the past few decades, Artificial Intelligence has succeeded to perform human alike jobs. Playing games wasn’t an exception. According to the new state of Artificial Intelligence in Software testing, Artificial Intelligence can do the testing for us. When it comes to game app tests, the technique of using Artificial Intelligence does not lag behind.

In case when there are numerous issues linked with manual tests, ‘machine-mind’ can scrutinize and verify every single thing much rapidly than software testers do. Thanks to enabling choosing the required parameter, the leading-edge technology runs hundred of test cases repeatedly in simply ten to fifteen minutes. The advent of advanced technologies powered with AI and ML (machine learning) algorithms promises for automating the entire slew of test cases and create game app testing smoother.

Artificial Intelligence is competent to maximize risk coverage error and detection while reducing execution time, expenses, and the number of test cases by detecting the optimal testing sets. It can discover weak spots in test case groups by spotting unused test cases, flaky test cases, untested necessities, and such test cases that aren’t connected to the requirements. Additionally, Artificial Intelligence has self-healing automation traits, which means it, can mend the broken automated test cases and make automated testing better resilient to modifications. Despite the benefits described above, Artificial Intelligence notices every small thing that could possibly be removed from the structure of a gaming product.

In some circumstances when manual automation leaves out important modifications in the newest build, Artificial Intelligence clicks on the button automatically & draws the user’s to notice things that disappeared from the app. AI may be a headline-grabbing attribute for technology products. However, what is the real-world advantages for development teams and QA engineers of Game Testing Services Providers that invest in Artificial Intelligence-powered test platforms?

Also Read: Transformation of Software Testing with AI

1. AI can detect errors or bugs before they become costly

Bugs or errors become highly expensive to mitigate or fix as the software development procedure evolves. However, AI provides immediate response – which can assist to recognize bugs as early as possible in the process and deliver important cost cuttings. Gaming products developer Ubisoft has built an Artificial Intelligence tool that can alert software programmers to possible flaws or bugs while they enter code. It can easily detect patterns that suggest an error is being generated and alert the software developer so they can easily take action. Bug fixes can take up to 70% of a development budget for a single game app– so Artificial Intelligence stands to provide important financial advantages for their business.

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2. AI and Machine Learning-driven dashboard for higher productivity

There is no shortage of information in the current scenario. Yet, there is a concerning dearth of the capacities for collating the accessible data in one place, obtain important insights from this data, and apply it into everyday operations to improve productivity. Smart dashboards allow the stakeholders to pull and envisage the information from any place and anywhere and share it around the organization for instantaneous status updates.

Also Read: Different Stages of Game Testing

3. Artificial Intelligence can help overcome automated testing bottlenecks

Automated testing is extensively accepted as a vital tool to accomplish modern Quality Assurance and testing objectives; it can easily overcome bottlenecks & unleash the influence of automated testing for DevOps surroundings. Ninety nine percent of software enterprises use DevOps for some section of their business and automated testing plays an essential role in DevOps surroundings and their Continuous Integration/ Continuous Delivery pipelines.

High-end advantages of automated testing comprise:

  • Best reuse of tests cases
  • Decrease in testing costs
  • Enhanced test coverage
  • Better transparency and control of test activities
  • Better identification of flaws or defects
  • Decrease of test cycle time

Some part of software or IT organizations would like to shift to every day, weekly, or hourly, build employment, however, studies proposed that automated testing is utilized in more or less than a quarter of test cases (24 percent) that make it the biggest obstruction or barrier to achieve these levels of responsiveness. Unfortunately, arranging automated tests across CI/CD pipelines is more and more complex and difficult.

Nearly 2/3 rd of higher management decision-makers in business IT functions stated that ‘releases are getting complicated, often including multiple apps with dependencies and varied technologies with potentially conflict resources’. However, AI and ML technologies can allow ‘smart’ test orchestration and detect tests that will be required for every software development cycle. That is why more than a quarter of high management decision-makers believe that AI-driven test implementation is significant orchestration ability.

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4. AI Automated Testing can Control Manual Tests time

Terrors of AI substituting manual testers are likely unfounded. Artificial Testing is expected to carry out recurring tasks and free human beings to use their imagination and critical thinking expertise across a series of industries – counting software testing. Senior- level executives or business executives see immense potential for Artificial Testing to control and lessen recurring tasks and free humans to concentrate on ‘high-end thinking’. However, what does this mean for QA and software tests?

AI could easily script 1000 testing in 1/1000th of the time that an individual could perform. Artificial Testing can perform the ‘heavy lifting’ and carry our recurring jobs like executing, implementing, and scrutinizing tests. Software testers of Game Application Testing Services Provider could increasingly work on high-end functions such as examining tests, making recommendations and providing feedback to the business.

Also Read: Factors to Consider For Successful Mobile Game Testing

5. Artificial Testing Know What Info to Use for Game Testing

90 percent of the flow of data inside the game comprises of template information that can be efficiently classified and organized. Email addresses, field names, search questions for a particular profile, phone numbers, in-app purchase problems, media data, and more – a lot of apps operate on similar information. Yet a small series of input info will be sufficient for building a network of productive tests based on the achievements of Artificial Testing. At the very least, all this is sufficient for anyone to have a trusted and faithful assistant at the development as well as software testing stage.

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Artificial Testing -Powered Tools for Testing Game Apps More Efficiently

Artificial Testing-driven Automated Testing Tools Confirms, the advent of Artificial Testing is inevitable. At present, business and Software Testers talk more about the so-called “3rd wave of automated testing” because of ground-breaking Artificial Testing powered automated test solutions. Let`s take a glance at some of the significant AI-powered tools:

  • Eggplant AI It uses smart algorithms for navigating software, forecasts errors, and mitigates problems with sophisticated data correlation. This incredible tool allows automating any test engine, offers a graphical examination of test coverage and results.

  • io– When there is a requirement of using even the easiest scripts; one still has the danger that owing to any alteration, the script may break. However, if you take benefit of this amazing tool and connect it to CI, you will have a great chance to detect the consequences of modifications made to the game. Also, by doing so, one could easily replace current test scripts & compliment user tests.

Also Read: 7 Different Types of Game Testing Techniques

  • ai– This is an amazing game testing tool that operates based on Selenium (a popular automated testing framework in the circles of testers) and Artificial Intelligence. By making use of it, you can run test cases without the need to code understands the bunch of locators. Testing is implemented in a simple format.

  • Sauce labs– It is also an amazing tools and the first program to execute tests in the cloud. The service launches up to one billion test automation daily. Based on the experience of ML, the Sauce labs developers are working to introduce powerful tools for examining the quality of products.

  • Appvance This is also a well-accepted tool that provides deep scrutiny of software via ML and generates “application blueprints” models applying cognitive generation. Such blueprints assure to produce a lot of test cases within a few mins. Apart from Artificial Intelligence, Appvance implies Test Designer, a playback and record trait.

  • Applitools– This is one of the most popular visual testing tool powered by Artificial Intelligence. The smart cognitive vision helps to summarize the expected design of an application. This amazing tool provides a visual comparison algorithm for detecting and reporting any variations found in the UI of an application. Applitools is better at executing automated tests and finds 1000s of interface inconsistencies in minutes.

  • Testsigma– Artificial Intelligence-driven tool for continuous automated tests. This tool utilizes natural language test processing for writing quality auto-tests. It determines the appropriate test cases for the test run and controls unpredicted test failures.

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Wrapping Up!!

There is definitely buzz around Artificial Intelligence in QA, and continuous attempts are being made to fill the gap between this buzz and realism. Thanks to Artificial Intelligence a group of QA engineers or testers can move beyond the oldest route of manual tests models and increasingly move forward toward a precision-based and automated continuous testing procedure. The QA engineers have to accept the Artificial Intelligence bot as a helpful addition, which will decrease the immense workload and make an engineer’s life much easier.

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