Your organization can get to market faster with higher-quality products when given better insight into the “dark side of the code”—the actual behavior of the full software system. Intended and actual behavior may differ in myriad ways that are not apparent from the source code.
The real test of IoT devices comes after shipping, when thousands of end users start using your product, sometimes in unexpected and untested ways. No software is entirely bug free, so some users will run into those remaining bugs. The question is how many and what you do about it.
Percepio announces Tracealyzer Tracealyzer version 4.4.2, with support for symmetric multiprocessing systems running Azure RTOS ThreadX SMP. The new release also brings improved support for trace streaming over STLINK-V3 debug probes.
Percepio’s French distributor Neomore hosts a webinar on Thursday 4 February at 11.00, about using Percepio Tracealyzer together with ST’s STM32CubeIDE.
One of the biggest problems in embedded development today is understanding what a software stack or demo that you didn’t write is doing. In this post, we’ll examine how we can find this out using the Tracealyzer communication flow diagram.
Quite a few embedded software developers don’t know whether their applications meet their timing requirements. In today’s Tracealyzer Hands On post, we will explore how to use Tracealyzer to verify task timing and scheduling.
Have you ever seen your embedded system behave strangely and had that sinking feeling that you might have a memory leak? Tracealyzer offers several different methods to detect memory leaks.
What if you want to visualize some application data in Tracealyzer, measure the time between two events or monitor a state machine? In this post, we will show how you can set up this kind of custom logging.
In the previous Hands On post we introduced the concept of intervals, which is the time between any two events and can be added to the timeline. In this post, we will take the interval one step further and see how we can use Tracealyzer to monitor state machines.
In this post, we visualise the custom interval and state machine information available in Tracealyzer and explore how we can use it to better understand our application.
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