3. Installation of GNATprove

In general, you will need to install a recent version of GNAT toolchain (that supports Ada 2012 syntax) to compile SPARK programs. You will need to install one toolchain for each platform that you target, for example one toolchain for native compilation on your machine and one toolchain for cross compilation to an embedded platform.

For analyzing SPARK programs, we recommend to first install GNAT Studio and then install GNATprove under the same location. Alternatively, you can install the GNATbench plug-in for Eclipse instead of GNAT Studio, using the Eclipse installation mechanism. The same version of GNAT Studio or GNATbench can support both native and cross compilations, as well as SPARK analysis.

If you choose to install GNATprove in a different location, you should also modify the environment variables GPR_PROJECT_PATH (if you installed GNAT). On Windows, edit the value of GPR_PROJECT_PATH under the Environnement Variables panel, and add to it the value of <GNAT install dir>/lib/gnat and <GNAT install dir>/share/gpr (so that SPARK can find library projects installed with GNAT) and <SPARK install dir>/lib/gnat (so that GNAT can find the SPARK lemma library project installed with SPARK, for details see Manual Proof Using SPARK Lemma Library). On Linux/Mac with Bourne shell, use:

export GPR_PROJECT_PATH=<GNAT install dir>/lib/gnat:<GNAT install dir>/share/gpr:<SPARK install dir>/lib/gnat:$GPR_PROJECT_PATH

or on Linux/Mac with C shell:

setenv GPR_PROJECT_PATH <GNAT install dir>/lib/gnat:<GNAT install dir>/share/gpr:<SPARK install dir>/lib/gnat:$GPR_PROJECT_PATH

See below for detailed installation instructions of GNAT Studio and GNATprove.

3.1. System Requirements

Formal verification is complex and time consuming, so GNATprove will benefit from all the speed (CPU) and memory (RAM) that can be made available. A minimum of 2 GB of RAM per core is recommended. More complex analyses will require more memory. A recommended configuration for running GNATprove on large systems is an x86-64 machine running Linux 64bits or Windows 64bits with at least 8 cores and 16 GB of RAM. Slower machines can be used to analyze small subsystems, but a minimum of 2.8Ghz CPU and 2 GB of RAM is required.

In addition, if you want to use the integration of CodePeer static analysis in GNATprove (switch --codepeer=on) you will need approximately 1 GB of RAM per 10K SLOC of code. In other words, in order to analyze 300K SLOC of code with CodePeer, you will need a 64bits configuration with at least 30 GB of RAM. Note that these numbers will vary depending on the complexity of your code. If your code is very simple, you will need less memory. On the other hand if your code is very complex, then you will likely need more memory.

3.2. Installation under Windows

If not already done, first run the GNAT Studio installer by e.g. double clicking on gnatstudio-<version>-i686-pc-mingw32.exe and follow the instructions.

Note

If you’re using GNAT Commnunity instead of GNAT Pro, you should run instead the GNAT Commnunity installer, which installs GNAT Studio and SPARK.

Then similarly run the GNATprove installer, by e.g. double clicking on spark-<version>-x86-windows-bin.exe. If you intend to install GNATprove in a location where a previous installation of GNATprove exists, we recommend that you uninstall the previous installation first.

You should have sufficient rights for installing the package (administrator or normal rights depending on whether it is installed for all users or a single user).

3.3. Installation under Linux/Mac

If not already done, you need to extract and install the GNAT Studio compressed tarball and then run the install, e.g.:

$ gzip -dc gnatstudio-<version>-<platform>-bin.tar.gz | tar xf -
$ cd gnatstudio-<version>-<platform>-bin
$ ./doinstall

Then follow the instructions displayed.

Note

If you’re using GNAT Commnunity instead of GNAT Pro, you should install instead the GNAT Commnunity package, which installs GNAT Studio and SPARK.

Then do the same with the SPARK tarball, e.g.:

$ gzip -dc spark-<version>-<platform>-bin.tar.gz | tar xf -
$ cd spark-<version>-<platform>-bin
$ ./doinstall

Note that you need to have sufficient rights for installing the package at the chosen location (e.g. root rights for installing under /opt/spark).