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---
layout: post
author: André Maroneze
date: 2020-06-17 12:00 +0100
categories: scripts usability
title: "Analysis scripts: up-to-date information in the Frama-C User Manual"
---
The _analysis scripts_ provided with Frama-C, which have been mentioned
in this blog several times, are now documented in the
[Frama-C User Manual](http://frama-c.com/download/frama-c-user-manual.pdf).
This should provide a more complete and up-to-date experience concerning
these scripts.
## Faster iterations with daily Frama-C snapshots
Deploying analysis scripts usually required very long iteration times: with
one Frama-C release each 6 months, users needed to wait before fixes and new
features, which meant less feedback from users.
With the availability of
[public daily snapshots](https://git.frama-c.com/pub/frama-c), it is now much
easier to provide users with new features and test different approaches.
## Not only for Eva
The analysis scripts were initially developed for usage with the Eva plug-in,
but they were always intended for a more widespread Frama-C usage.
A small section on the Eva user manual mentioned their usage, but without
many details, due to their constant evolution.
As their usage matures, we expect some convergence from other plug-ins, to
provide a more unified approach and to maximize their utility.
Dedicating an entire chapter of the User Manual to them should help achieve
this objective.
## Towards continuous integration with Frama-C
The usage of _analysis scripts_ is shifting from a formal methods-centric
view -- in which the code is considered as "finished" and the main task is
the verification with Frama-C -- towards an agile development-centric view,
in which Frama-C is a tool to be used throughout the development process.
By inserting Frama-C in a continuous integration pipeline, the user should
obtain helpful feedback after each commit.
Current developments in the platform should allow this to become true in the
nearby future, thanks to the support of [EU project SPARTA*](https://sparta.eu).
Stay tuned!
<small>*This project has received funding from the European Union's Horizon 2020
research and innovation programme under grant agreement No 830892.</small>
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