Security has become a necessity in our day-to-day activities. Are we aware of how we can uncover these vulnerabilities? Do we understand the basic security tests that we run? Can we analyze and understand whether the threat found is a false positive or not? How can we make Static Application Security Testing and Dynamic Application Security Testing (DAST) work hand in hand for our benefit? How can we have DAST Automated with our dear Selenium? How can we apply DAST on Mobile Apps? How can we have DAST part of CI/CD pipeline?
The Predictive analysis carries to extract valuable information from the data sets with the help of the statistical algorithms and machine learning to forecast the trends and performance patterns. When it comes to software testing, predictive analytics makes everything clear about what to test and predict the quality issues before and after the production.
In the bustling Ad Tech industry, we are constantly presented with challenges. These range from segmenting browsers, targeting devices, users (consumers) and even environments. Ad presentation specifications are constantly changing, as new devices are always coming onto the market. Machine Learning model techniques are adopted to engage and know consumer preferences through ‘sentiment’ surveys or other polls. After performing automation on the newest (and oldest) mobile devices, a new connected TV device appears with unique challenges.
When testing software, it is not uncommon to hear that one hundred percent coverage is unachievable. What happens, then when we are asked to do such a thing. If the software that is being tested is used in critical infrastructure (power systems, water, medical, banking, etc.) then an escaped bug is not a trivial thing.
In this webinar, Lisa Crispin will explore these two sets of principles, how they relate to each other, how teams can benefit from them, and how they might shape the future of testing and quality.
Shopping for new tools is not unlike dating. You need to ask yourself the same questions: “What am I looking for?” “Do they fit in with the picture I have for my future?” “Will it get along with my friends colleagues?” On top of that, the testing tool landscape has changed so much in just the past few years. What expectations should you have? Where do you even go to “meet” these tools?
Since managing performance and assuring it is acceptable is not a trivial task neither just a matter of running load, the webinar will go through all of the possible routes an organization should become familiar to achieve great performance.
We learn from Cathy’s customer feedback and experiences around automation strategy, artificial intelligence, and some possible new capabilities coming to the Applause solutions.
Have you ever wondered if you want/need/able to test in production? Is it even possible without bringing harm to your users? Does it bring any value?
No need for antacids or a doctor, just come to this session to find out all the juices and spices necessary to make that delicious secret sauce of automated tests that allows CenterEdge Software to continuously deploy most of its web software, both micro-services and monoliths.
Acceptance Test Driven Development has become an industry buzz word, and that buzz has reached your automation doorstep. With all of the promises of conversational language test cases, increased communication, and productivity, this paradigm almost seems too good to be true.
With the inception of smartphones, the mobile app market has seen explosive growth. Hence enterprises are focusing more on the quality of apps so that they can provide the best user experience to their customers. Consequently, we can see exponential rise and rapid technological evolution in the field of Mobile App Testing. Achieving quality with speed is the key concern in Mobile App Testing and this can be achieved through automation testing and improving its quality. There are several tools available in the market for automation testing and one of the best automation tools is Appium. Now let us explore the features of Appium.