Software Testing Videos and Tutorials: Load Testing, Unit Testing, Functional Testing, Performance Testing, Agile Testing, DevOps
How many of us have spent those hours just to analyze test failure Automation run reports to first determine whether it was an actual bug or environment specific issue or a test automation issue. We agree that no matter how much robust we make our UI Automation frameworks, we always encounter Automation/Environment specific failures, which increase the time spent on analyzing those failures and spotting actual issues/defects.
Testing strategies for modern software architectures are evolving. As we transition from monolithic structures to team-sized microservices with crisp APIs aligned to bounded contexts, we encounter more stable testing surfaces.
This session concentrates on the strengths of Jenkins and how they can be leveraged to configure and maintain dozens of projects while still keeping each of the pipelines simple and handy for the daily use of the developers.
We are aware of the continuous monitoring of various data intensive systems and services across cloud platforms and on-premise settings. However, when it comes to continuous monitoring in alignment with continuous software testing in a DevOps context of visually heavy live-streaming applications, we are left with the fewer options especially in the open source space.
In the last couple of years, we all witnessed the rise of startups that often lack a software quality assurance approach. These small organizations are driving innovations, but bringing high uncertainty, short planning horizon, and lack of time and resources along.
This presentation about software testing is for software developers and everybody else working in IT. Secret number one: this session is less about software testing as you would expect… Software Development is a complex thing. We are dealing with customers who do not exactly know what they want. We also have to deal with complexity, confusion, changes, new insights and half answers.
Test automation that works is something we strive to achieve in software testing, and sometimes it is difficult to do. Tests fail randomly, and it is not easy to pinpoint the reason for failures.