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| -rw-r--r-- | README.md | 16 |
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@@ -2,15 +2,18 @@ **dfatool** is a set of utilities for automated measurement of non-functional properties of software product lines and embedded peripherals, and automatic generation of performance models based upon those. -Measurements and models for peripherals generally focus on energy and timing behaviour expressed as a [Priced Timed Automaton (PTA)](https://ess.cs.uos.de/static/papers/Friesel_2018_sies.pdf) with [Regression Model Trees (RMT)](https://ess.cs.uos.de/static/papers/Friesel-2022-CPSIoTBench.pdf). +Measurements and models for peripherals (`generate-dfa-benchmark.py` and `analyze-archive.py`) generally focus on energy and timing behaviour expressed as a [Priced Timed Automaton (PTA)](https://ess.cs.uos.de/static/papers/Friesel_2018_sies.pdf) with [Regression Model Trees (RMT)](https://ess.cs.uos.de/static/papers/Friesel-2022-CPSIoTBench.pdf). -Measurements and models for software product lines focus on ROM/RAM usage and may also include attributes such as throughput, latency, or energy. +Measurements and models for software product lines (`explore-kconfig.py` and `analyze-kconfig.py`) focus on ROM/RAM usage and may also include attributes such as throughput, latency, or energy. The variability model of the software product line must be expressed in the [Kconfig language](https://www.kernel.org/doc/Documentation/kbuild/kconfig-language.txt). Generated models can be used with [kconfig-webconf](https://ess.cs.uos.de/git/software/kconfig-webconf). This allows for [Retrofitting Performance Models onto Kconfig-based Software Product Lines](https://ess.cs.uos.de/static/papers/Friesel-2022-SPLC.pdf). +Models for other kinds of configurable components (`analyze-log.py`) are also supported and work with logfiles that contain "`[::]` *Key* *Attribute* | *parameters* | *NFP values*" lines. +Here, only analysis and model generation are automated, and users have to generate the logfiles by themselves. + The name **dfatool** comes from the fact that benchmark generation for embedded peripherals relies on a deterministic finite automaton (DFA) that specifies the peripheral's behaviour (i.e., states and transitions caused by driver functions or signalled by interrupts). -It is meaningless in the context of software product lines. +It is meaningless in the context of software product lines and other configurable components. ## Energy Model Generation @@ -64,6 +67,13 @@ Refer to the [kconfig-webconf README](https://ess.cs.uos.de/git/software/kconfig We also have a short [video example](https://ess.cs.uos.de/static/videos/splc22-kconfig-webconf.mp4) illustrating this workflow. +## Log-Based Performance Model Generation + +Here, dfatool works with lines of the form "`[::]` *Key* *Attribute* | *parameters* | *NFP values*", where *parameters* is a space-separated series of *param=value* entries (i.e., benchmark configuration) and *NFP values* is a space-separate series of *NFP=value* entries (i.e., benchmark output). +All measurements of a given *Key* must use the same set of parameter names and NFP names. + +Use `bin/analyze-log.py file1.txt file2.txt ...` for analysis. + ## Dependencies Python 3.7 or newer with the following modules: |