README.md
1
2*__NOTE__: This is still a work in progress project, suitable for:*
3*developers, contributors and testers.*
4*None of the provided tests have been extensively evaluated as of January 2017.*
5
6# Introduction
7
8The LISA project provides a toolkit that supports regression testing and
9interactive analysis of Linux kernel behavior. LISA stands for Linux
10Integrated/Interactive System Analysis. LISA's goal is to help Linux
11kernel developers to measure the impact of modifications in core parts
12of the kernel. The focus is on the scheduler (e.g. EAS), power management and
13thermal frameworks. However LISA is generic and can be used for other purposes
14too.
15
16LISA has a "host"/"target" model. LISA itself runs on a *host* machine, and uses
17the [devlib](https://github.com/ARM-software/lisa) toolkit to interact with the
18*target* via SSH, ADB or telnet. LISA is flexible with regard to the target OS;
19its only expectation is a Linux kernel-based system. Android, GNU/Linux and
20busybox style systems have all been used.
21
22LISA provides features to describe workloads (notably using
23[rt-app](https://github.com/scheduler-tools/rt-app)) and run them on targets. It
24can collect trace files from the target OS (e.g. systrace and ftrace traces),
25parse them via the [TRAPpy](https://github.com/ARM-software/trappy)
26framework. These traces can then be parsed and analysed in order to examine
27detailed target behaviour during the workload's execution.
28
29Some LISA features may require modifying the target OS. For example, in order to
30collect ftrace files the target kernel must have CONFIG_DYNAMIC_FTRACE enabled.
31
32There are two "entry points" for running LISA:
33
34* Via the [Jupyter/IPython notebook framework](http://jupyter.org/). This allows
35 LISA to be used interactively and supports visualisation of trace data. Some
36 notebooks are provided with example and ready-made LISA use-cases.
37
38* Via the automated test framework. This framework allows the development of
39 automated pass/fail regression tests for kernel behaviour. The
40 [BART](https://github.com/ARM-software/trappy) toolkit provides additional
41 domain-specific test assertions for this use-case. LISA provides some
42 ready-made automated tests under the `tests/` directory.
43
44# Motivations
45
46The main goals of LISA are:
47
48* Support study of existing behaviours (i.e. *"how does PELT work?"*)
49* Support analysis of new code being developed (i.e. *"what is the impact on
50 existing code?"*)
51* Get insights on what's not working and possibly chase down why
52* Share reproducible experiments by means of a **common language** that:
53 * is **flexible enough** to reproduce the same experiment on different
54 targets
55 * **simplifies** generation and execution of well defined workloads
56 * **defines** a set of metrics to evaluate kernel behaviours
57 * **enables** kernel developers to easily post process data to produce
58 statistics and plots
59
60# Documentation
61
62* [Wiki Home page](https://github.com/ARM-software/lisa/wiki)
63* [Installation](https://github.com/ARM-software/lisa/wiki/Installation)
64* [Quickstart Tutorial](https://github.com/ARM-software/lisa/wiki/Quickstart-tutorial)
65
66More formal API documentation for LISA is a work in progress, however much of
67the API is currently described in the provided tutorial Jupyter notebooks.
68
69# External Links
70* Linux Integrated System Analysis (LISA) & Friends
71 [Slides](http://events.linuxfoundation.org/sites/events/files/slides/ELC16_LISA_20160326.pdf)
72 and [Video](https://www.youtube.com/watch?v=yXZzzUEngiU)
73
74# License
75
76This project is licensed under Apache-2.0.
77
78This project includes some third-party code under other open source licenses. For more information, see lisa/tools/LICENSE.*
79
80# Contributions / Pull Requests
81
82Contributions are accepted under Apache-2.0. Only submit contributions where you have
83authored all of the code. If you do this on work time make sure your employer
84is cool with this.
85