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kernelshark-v2.3.1
KernelShark 2.3.1 Changes since 2.3.0 - Fixing bugs introduced when Porting KernelShark to Qt 6.
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kernelshark-v2.3.0
KernelShark 2.3.0 Changes since 2.2.1: - Porting KernelShark to Qt 6
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kernelshark-v2.2.1
KernelShark 2.2.1 Changes since 2.0.0: - Fixes segfault in libkshark-tepdata.
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kernelshark-v2.2.0
KernelShark 2.2.0 Changes since 2.1.1: - Fixes for plugin build. - Fixing text indent for function_graph data. The content of table is shown in monospaced font. The C-style indentation of traced functions is now shown correctly. - Multi-line events are no longer truncated and can be shown using the dual marker. - The text to of the events can be selected (is copyable).
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kernelshark-v2.1.1
KernelShark 2.1.1 Fixes: - Improved search for the font file before building. - Various fixes needed by external plugins. - Fixing possible deadlock inn the readout of trace-cmd data. - Fixing memory issue in KsCaptureDialog
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kernelshark-v2.1.0
KernelShark 2.1.0 Changes since 2.0.0: - Adding common APIs and definitions for sched plugins: The APIs are moved out from the 'sched_events' plugin, allowing to avoid code duplication when defining alternative plugins for scheduling events. Fixes: - Handle traces with sched_wakeup but not sched_waking. - README file update. - Fixing segfault in the case when a plugin fails to load. - Improved interface for 'pkg-config'.cay6
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kernelshark-v2.0.2
KernelShark 2.0.2 - Fixing possible segfaults when (de)initializing the 'sched_events' plugin.
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kernelshark-v2.0.1
KernelShark 2.0.1 - Fixing the build failure caused by the recent modifications in libtracefs. - Fixing all compilation warnings caused by the usage of deprecated Qt APIs.
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kernelshark-v2.0
KernelShark 2.0 Major changes since 1.3: - Introduces Data streams: With the help of Data stream, KernelShark is able to load and merge multiple trace files (streams). Each stream can have different plugins or filters, registered for it, which means that the raw trace data of the streams can have different formats, and will allow for a great degree of customization of the provided data visualization. - New design of the plugin interface - instead of having a single interface for loading the plugin, we now have 3 different interfaces: - The one that exists in version 1 of KernelShark is now renamed to Data Processing Interface (dpi). - The first new interface for loading can be used to register user provided implementation of the Data stream readout and is called Data Readout Interface (dri). Via this plugin loading interface the user can open trace data having an arbitrary format. In order to make this possible the user has to provide a plugin that contains an implementation of the data readout methods defined by the kshark_data_stream_interface and to register all those methods. - The second new plugin loading interface is called Control interface and can be used to provide the plugin with an access to the GUI's Main window object. Via this interface the plugin can became capable to modify the GUI. - The modification of the C API are used to implement 3 new plugins: - KVMCombo plugin: The plugin allows the user to visualize the execution flow between the host and guest virtual machines. It exploits the concepts of "Data streams " and "Combo Plots" That allows to have two normal graphs from two data streams stacked together (on top of each other). The plugin uses a "combo" between the task in the host that emulates a virtual CPU and the corresponding CPU graph from the VM. The plugin draws additional graphical elements on top of this "combo", helping the user to intuitively interpret the data and see how the execution flow goes from host to guest and back. - LatencyPlot plugin: The plugin allows the user to visualize the latency between two events under the condition that the values of given data fields in the two events are identical (for example having the same PID). The plugin also registers its own dialog, that allows the user to select the events (and the matching field) to be visualized. - EventFieldPlot plugin: The plugin allows the user to visualize the recorded value of a given data field from a given trace event. The user can select the event and field to be visualized.