haros 3.10.9

Static analysis framework for ROS

HAROS is a framework for quality assurance of ROS-based code, mostly based on static analysis.

Static analysis consists on extracting information from the source code without executing it (and, sometimes, even without compiling it). The kind of properties that can be verified include simple conformity checks, such as checking whether a variable is initialised, to more complex properties, such as functional behaviour of the program. This allows early detection of problems in the software development life cycle, which would otherwise go unnoticed into later stages or even into production.

Needless to say, sometimes in robotics it is very hard (or very expensive) to properly test software, not to talk about possible risks. Hence the appeal of static analysis.

There is a demo page of the HAROS visualizer available on GitHub, a short video presentation of the current state of HAROS on YouTube and a (slightly outdated) demo video on YouTube as well.

Current Status

HAROS is still being developed, as of August 2021. Help improve HAROS by participating in a short user survey.

Installing

To install HAROS, make sure that you have Python 2.7 or greater. Simply run the command:

pip install haros

For alternative methods, and to install external dependencies required for some features, see INSTALL.

How to Use

See USAGE for basic commands and usage instructions.

Bugs, Questions and Support

Check whether your question has an answer in the FAQ.

Please use the issue tracker for issues or feature requests directly related to HAROS.

For issues related to plugins, please use the respective plugin repository.

If you run into errors, or feel that something is not working, run HAROS in debug mode, so the log files do not miss any information, e.g.,

haros --debug analyse ...

Then, you can share the log file, found by default within ~/.haros/log.txt.

Citing

See CITING.

Contributing

See CONTRIBUTING.

Acknowledgment

Until March 2021, this work was financed by the ERDF – European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia within project PTDC/CCI-INF/29583/2017 (POCI-01-0145-FEDER-029583).