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Wednesday, October 2 2019

SATE VI Workshop: Frama-C satisfies the Ockham Criteria

During the SATE VI Workshop, organized by the NIST SAMATE project, Frama-C was confirmed as having satisfied the Ockham criteria for sound analysis tools. Frama-C previously satisfied the SATE V Ockham criteria (2013-2016) and found hundreds of errors in the test material.

We reported in this blog about our analysis of SATE VI's Juliet 1.3 test suite. The code is available on Github, so that anyone can install Frama-C and reproduce the results.

In this post, we summarize some of the discussions that took place during the workshop, including future directions for SATE VII.

The SATE VI Workshop took place at MITRE who are responsible, among other things, for the Common Weakness Enumeration, and focused mostly on the Classic track, which had the most tools participating in. With Frama-C, we briefly examined part of the DARPA CGC test suite, one of the code bases available for SATE 6 Classic, finding some unintentional bugs.

The official report is still being finalized, but a few interesting points could be observed from the presentations and discussions:

  • The Wireshark code base was a bit too large for some tools, while the SQLite code base seemed to hit a sweet spot between code size and bug complexity.
  • The bugs injected via GrammaTech's Bug Injector tool were not as diverse as one might expect, but nevertheless it managed to insert bugs that were able to discriminate sufficiently between tools. That is, if the bugs were "trivial" or "impossibly hard", then either all or none of the tools would have found them; instead, there was a wide distribution between tools.
  • Some tools had issues mapping the results to the locations expected in the test oracles, either because some oracles were no longer up-to-date, or because each tool's definition of sinks and sources (the lines in the code where bugs manifest themselves, and those in which the bug is actually present) were not necessarily identical to the expected ones.
  • Several tools ended up finding more bugs than the injected ones, which is not surprising given the size of the code bases.
  • The SARIF format will be the default (and likely only) format for SATE VII. This should minimize the time necessary for NIST to process the results. All present tool developers were either already SARIF-compatible, or intended to become in the nearby future (including Frama-C).
  • Besides Frama-C, Astrée participated in the Ockham track, and also satisfied the criteria. A few other tools also participated, but some details were still being discussed. Overall, at least 4 tools participated in the Ockham track, which is a progression from the previous edition. We see this as a positive evolution of the importance of sound analyses.

Overall, the tool exposition workshop was very informative, and we thank NIST for meeting the challenges of organizing it, including very extensive and helpful feedback.

The visibility offered by SATE helps tool developers to showcase their work, and allows users to obtain important feedback about them. Incorporating a static analysis tool in a development toolchain has a cost, but may bring considerable benefits; being able to better estimate this trade-off is an important outcome of NIST team's work.

Tuesday, June 19 2018

Analyzing Chrony with Frama-C/Eva

Chrony is an implementation of NTP which is C99-compatible, with portable code, and thus a good candidate for an analysis with tools such as Frama-C.

As part of an effort sponsored by Orolia, researchers from the List, CEA Tech laboratory applied Frama-C/Eva on the Chrony source code, in an attempt to verify the absence of run-time errors. This post summarizes some of the findings and links to the full report, in PDF format.

Scope of the analysis

The analysis was performed on Chrony 3.2.

Some parts of the code were disabled via the configure scripts, namely IPV6, timestamping and readline. The idea is to minimize the amount of non-POSIX code, in hopes of improving the likelihood that external functions will have a specification in Frama-C's stdlib. Reenabling those features requires only writing additional stubs/specifications.

The entrypoint used for the analysis was the main function in test/unit/ntp_core.c, with a generalized state for argc and argv, to include possible behaviors from arbitrary command line arguments.

The Eva plug-in was iteratively parametrized to improve coverage and minimize the number of alarms, while maintaining a short execution time. Reported alarms include possible buffer overflows, uninitialized reads, and other undefined behaviors, as listed in the Eva plug-in user manual.

The analysis identified a few issues, but the overall impression was that code quality was high w.r.t. the C standard and the presence of some defensive programming patterns. However, there are still several potential alarms that need to be further investigated to ensure the absence of run-time errors.

The full report is available here:

Report: Frama-C/Eva applied to the Chrony source code: a first analysis (PDF)

Do not hesitate to contact us if you have suggestions, remarks, patches, etc. You can use the Frama-C mailing list or Github's issues page on open-source-case-studies.

Thursday, February 15 2018

Analysis scripts: helping automate case studies, part 2

In the previous post, we used analysis-scripts to prepare our analysis of Recommender. In this post, we will run EVA on the code and see how the iterative refinement of the analysis can be done. We assume the reader has performed all of the steps in the previous post, and is currently in the directory containing the GNUmakefile created previously.

Running the first EVA analysis

Running make main.eva will run the EVA plug-in in the console, and then output some metrics information. This is useful for scripts and experienced users. For now, running make main.eva.gui is more useful: it will run the analysis and then open the results in the GUI.

A *.{parse,eva}.gui target in analysis-scripts only run parsing/EVA if necessary; if it has already been run, and no source files or analysis parameters were modified, it will directly open the GUI.

In the GUI, in the Properties panel (you have to click Refresh after loading the GUI) if we inspect only Unknown/Invalid properties, we will notice 148 of them, several related to finiteness of floating-point values, as well as many related to variable initialization.

Note that the results of each analysis are stored in the main.eva directory, and also copied to a timestamped directory in the form main_YYYY-MM-DD_hh-mm-ss.eva. Thus main.eva always contains the latest analysis, while the timestamped copies are useful to retrieve past results and compare them, e.g. using meld's folder comparison view.

Iterating on EVA analyses

Let us use the Loop Analysis plug-in to obtain more precise results. Since analysis-scripts already created a Frama-C save file (extension .sav by default), we just need to load it and add -loop:

frama-c -load main.eva/framac.sav -loop > main.slevel

Open the main.slevel file with a text editor. It contains the output of the Loop Analysis plug-in: some informative text, and then a line that says:

[loop] Add this to your command line:

Followed by several command-line arguments related to the use of slevel. Let us erase everything up to and including the Add this ... line, and then include the file contents in the EVAFLAGS variable of our GNUmakefile:

EVAFLAGS    += $(shell cat main.slevel | tr '\\' ' ')

Note that we use the tr command-line utility to remove the backslashes from the output of Loop Analysis.

If we re-run make main.eva.gui, the dependencies managed by Make will re-run the analysis because its command-line changed, but not the parsing, since it was not impacted.

This time, we obtain 114 unknown/invalid properties.

Appeal to brute-force

Since this is a test case that runs very quickly, and because Loop Analysis' heuristics are not perfect, we can allow ourselves to try a somewhat aggressive -slevel. Let us remove the heuristics given by Loop Analysis, and instead use a global slevel of 500:

EVAFLAGS    += -slevel 500

The reason why we remove Loop Analysis' results is that, in some cases, it forces merging of states to avoid slowing down the analysis, and those settings take precedence over the global slevel.

The analysis will be much longer this time, but should still terminate in a few seconds. Given such a high slevel, we are lucky that it terminates at all. We will obtain 86 unknown/invalid properties this time.

Extra hypotheses for more precision

There are several options in EVA that allow a more precise analysis of less-than-ideal code that can be found in the wild. Most of them require knowing some details about the semantics of C, but others can be used more leniently, to help get a better idea of the code under analysis, before some serious analysis time is spent. One of them is -no-val-malloc-returns-null. This option is only useful when the code contains dynamic memory allocation, and what it does is to consider that memory allocation never fails.

By default, the memory allocation built-ins used by EVA suppose that memory allocation can fail, as stated in the standard (i.e. malloc can return NULL, for instance when there is not enough available memory). However, many code bases fail to test for such cases; which is admittedly a relatively rare situation, especially on a system that allows memory overcommitment. The -no-val-malloc-returns-null thus adds a new hypothesis to the underlying analysis ("... and considering that memory allocation never fails..."), in exchange for a more precise result.

In Recommender, we notice that there are some spots where malloc is tested for NULL (e.g. in src/learned_factors.c:47), but others where no such test is performed (e.g. in src/learned_factors.c:67). Thus adding this option should (hopefully) result in fewer alarms. Our EVAFLAGS line becomes:

EVAFLAGS    += -slevel 500 -no-val-malloc-returns-null

Indeed, running the analysis again results in only 56 unproved properties. However, it also reveals another issue.

Tracking red alarms

Opening in the GUI the result of the last iteration of the analysis, if we scroll through the main function, we see that the analysis has stopped (became red) before returning from the call to recommend_items. Jumping to its definition, we see a loop where j should go from 0 to 2 (the value contained in (estim_param->tset)->items_number)), but inspecting the value of j in the while condition shows {0; 1}. This means that the third iteration never took place, its trace cut short by some evaluation that resulted in a definitely invalid property.

There are several ways to proceed here:

  • One can follow the "red path" in the GUI, jumping inside reachable functions in the GUI until the limit of the red path is found;

  • Alternatively, in this case we have a warning (in the Messages tab) that says that all target addresses were invalid, which often indicates an issue with the evaluation of a state;

  • Finally, one can prioritize alarms in the Properties tab, by checking only Invalid properties at first, before including Unknown ones.

In this case, all three would end up around the same source line (src/binary_heap.c:153), though this is not always true.

Spoiler alert: the Chlorine 17 release of Frama-C will include an extra panel, Red alarms, which will provide another way to get to properties that warrant extra attention when starting an analysis.

Note that, whenever the C code contains calls to assert(), Frama-C generates a call to __FC_assert whose precondition is requires \false. This leads to an Invalid alarm in the Properties panel, however this does not indicate that the source code necessarily has undefined behavior: it may be due to an imprecision in the assertion condition, which if possibly true, leads to the call being made, which will itself definitely indicate an error. But if the call may not happen, then the assertion should be treated like an Unknown alarm.

Spoiler alert: in Frama-C Chlorine (17), the behavior of assert will be changed to more closely match the usual approach: an Invalid alarm will only be generated when the assertion is definitely violated.

Back to the Invalid alarm: if we inspect the source code in question, we will see that the only valid index for the buffer bheap->buffer is 0, due to the ACSL assertion inserted by EVA:

/*@ assert Value: index_bound: bheap->filled_elements < 1; */
bheap->buffer[bheap->filled_elements] = value;

However, filled_elements is 1 in this call, which seems like an error. But why is it there? While it is impossible to know exactly the intent of the author of the code, by inspecting the definition of the buffer, we can obtain some clues. In the Information panel, if we inspect bheap, we see that:

Variable bheap has type `binary_heap_t *'.
It is a formal parameter.
It is referenced and its address is not taken.

And then if we click binary_heap_t itself, we obtain its type information:

Type information for `binary_heap_t':
(sizeof 16, defined at src/binary_heap.h:53)
 struct binary_heap {
    size_t max_size ;
    size_t filled_elements ;
    int (*value_comparer)(void const *, void const *) ;
    void *buffer[1] ;

Finally, clicking the source line will take us to the definition in the binary_heap.h header, which contains some useful comments:

 * binary_heap:  The heap is tree based data structure
 * Members:
 *   max_size        The number of elements in the binary heap
 *   filled_elements The number of inserted elements so far
 *   buffer          The buffer is a dynamically allocated array
 *                   containing the heap's elements
typedef struct binary_heap
  size_t          max_size;
  size_t          filled_elements;
  bh_value_cmp    value_comparer;
  void*           buffer[1];
} binary_heap_t;

From the comment, it seems that the code is implementing the pattern of a flexible array member, where the last element of the binary_heap_t structure should be an incomplete array type. However, its current declaration corresponds to that of a fixed-size array, which according to the C standard cannot be accessed beyond its static bounds. We can fix this by using the proper flexible array member notation defined in the C99 standard.

Syntactic fixes

By replacing void* buffer[1]; with void* buffer[]; in src/binary_heap.h, we define a proper flexible array member. As a consequence, the code can access all elements of the dynamically-allocated array, as long as enough memory has been allocated for them.

You may notice that, after modifying the .h file and re-running make main.eva.gui, Make will not re-parse nor re-run the analysis, it will simply open the GUI again. This is because the .h file dependencies are not tracked by the Makefile rules: they were never included in the list of .c sources of main.parse (because such headers are directly included via preprocessor directives), so Make has no way to know about these implicit dependencies. You can remedy that by forcing Make to unconditionally make all targets, adding -B to the command line arguments.

After doing so, everything is recomputed, and we obtain … almost the same alarm.

This time, the alarm happens on the third iteration of the loop, instead of the second one: progress! … But not much. There is still a problem when accessing the last element of the array. To find out why, we can use the GUI again. However, this time the Invalid alarm is no longer present; the problem is more subtle. Still, the warning about all target addresses were invalid is still there. It points to this statement:

    /*@ assert
        Value: mem_access: \valid(&bheap->buffer[bheap->filled_elements]);
    bheap->buffer[bheap->filled_elements] = value;

By inspecting bheap->filled_elements, we see its possible values were {1; 2} before the statement, but {1} afterwards. This indicates that index 2 is not valid for this memory access. But why? We can check the location being accessed, to see its validity.

If we inspect the values for bheap, we see, in the Values tab:

bheap -> {{ (binary_heap_t *)&__malloc_init_binary_heap_l42 }}

Then, if we left-click on __malloc_init_binary_heap_l42, the Information panel will display some extra lines about this value in particular, with a clickable link pointing to its syntactic information. Clicking on that link will display the type of the dynamically allocated block:

Variable __malloc_init_binary_heap_l42 has type `char [23]'.

For dynamically allocated bases, EVA does not always have access to the original type intended for the allocated base, so it uses heuristics to restore that information. When such heuristics fail, it resorts to the "catch-all" char [].

"23" is a somewhat unusual size (not a multiple of the word size). Let us investigate where that number came from.

Using Studia

Right-clicking on __malloc_init_binary_heap_l42, in the Information tab, will display a context menu, the same one as if we had right-clicked some lvalue on the Cil code. We will use the Studia plug-in, in particular its Writes feature, to identify all points in the source code where this memory location was written prior to the statement indicated by the warning.

Studia will compute and highlight the statements in the code, and also add an extra column to the filetree display (upper left corner in the GUI), indicating all functions directly writing to the memory location (indicated by a 'tick' symbol in the Studia column) and the functions indirectly writing to it, that is, the callers of the former (indicated by an arrow symbol in the Studia column) as well as their own callers, recursively.

The functions writing to buffer are: balance_heap, init_binary_heap and insert_binary_heap. The first and the last write to fields in the buffer structure, but only init_binary_heap actually allocated the memory.

Well, I guess you could have directly inferred that from the variable name, which serves this exact purpose, but then I wouldn't have had an excuse to shamelessly plug Studia, one of the new features in Frama-C 16 Sulfur, would I?

Inside init_binary_heap lies our answer: the computation of the size of the bheap includes a -1, which is due to the fact that the non-flexible array member notation already had a byte allocated for the array, but our proper C99-compatible version no longer includes this byte. So the malloc'ed memory was 1 byte shorter, which led to the invalid memory access. So all we have to do is to fix the computation here (and take note of the fact that modifying other people's code without properly understanding it can lead to bugs).

At last … unable to progress

This time, we re-run the analysis (no need to use -B this time, since the .c file is tracked in the dependencies of our GNUmakefile), expecting to triumph over the syntactic distractions. However, we are greeted with a somewhat unpleasant surprise:

src/binary_heap.c:118:[value] warning: detected recursive call
    (balance_children <- balance_children :: src/binary_heap.c:135 <-
                         pop_binary_heap :: src/recommender.c:95 <-
                         recommend_items :: test/test.c:108 <-
    Use -val-ignore-recursive-calls to ignore (beware this will make the analysis
[value] user error: Degeneration occurred:
    results are not correct for lines of code that can be reached from the degeneration point.

We should have seen it coming: binary heaps are fond of recursion. Our coverage did improve from the previous analysis (from about 75% to about 85%), but we now hit a harder obstacle. To deal with this, we'll have to stub the balance_children function, possibly over-approximating its behavior, or rewrite an equivalent, iterative version of the function. In either case, such transformations are out of the scope of this tutorial.

Conclusion and bonus features

In this tutorial, we showed how to use analysis-scripts, presenting most of its features in a quick usage scenario. There are still a few tricks up its sleeve which were not mentioned:

  • flamegraph.txt: this file is computed by option -val-flamegraph, and it produces a Flamegraph of the analysis performed by EVA. This graph is useful when profiling larger case studies, to quickly visualize where the analysis is spending most of its time. This can indicate functions where less slevel or ACSL stubs might help.

  • metrics.log: its output is displayed after running a .eva target. The coverage estimation is a quick indicator of progression in the analysis during the refining stage, i.e. sometimes when an analysis is made more precise, the number of alarms may actually increase, and the reason may be that the coverage has improved, so that more code is actually being analyzed, which might explain why now there are more alarms.

  • alarms.csv: a CSV report with the same contents of the Properties panel in the GUI, obtained via the Report plug-in. Very useful for scripts.

  • stats.txt: similar to the one present in the .parse directory; however, since parsing is usually very fast when compared to an EVA analysis, this version of the file is the one that is actually useful most of the time. In particular, if you want to compare the execution time of a new parameterization of the analysis, you just need to look at the user_time line. Very useful when you realize you forgot to type time make instead of make.

We hope this tutorial was useful to you and that the next Frama-C release will make things even easier! Don't forget to check some usage examples in open-source-case-studies, and please consider proposing your own case studies via Github issues.

Thursday, January 25 2018

Analysis scripts: helping automate case studies, part 1

(kindly reviewed by T. Antignac, D. Bühler and F. Kirchner)

Among Frama-C 16 Sulfur's new features, one of them is dedicated to help setting up and iterating case studies. In this series of posts, we will explain how to use such scripts to save time when starting a new case study with EVA.

This series supposes some familiarity with EVA, as in, its basic usage is not detailed. Reading A simple EVA tutorial or the tutorial in the EVA user manual should be sufficient.

In this first part, we will explore the basics of the analysis-scripts framework and its use on an open source project. We will see how to get the preprocessor flags needed to prepare an analysis template. This template is in fact a Makefile which will be used to set up the analysis. It will enable us to define the sources to parse by editing its targets.

In the next post, we will see that, once the set-up is done, the analysis steps are similar to the ones presented in previous EVA tutorials: run a simple analysis, then refine, improve the precision, iterate. Once an analysis has been run, we will see how to track red alarms to improve the coverage. This will lead to some syntactic fixes that will allow the analysis to go further.

Analysis scripts

The release 16 (Sulfur) of Frama-C includes a small set of files, called analysis scripts, whose purpose is to help starting new analyses with Frama-C. It is currently focused on analyses with EVA, but other plug-ins such as WP and E-ACSL may incorporate it as well.

The new files are available in the analysis-scripts of Frama-C's share directory. Use frama-c -print-share-path to obtain its exact location. This directory currently contains a README, two small Bash scripts and a Makefile (frama-c.mk) which contains the bulk of it.

Note: the README.md mentions fcscripts, the old name of this set of files (it was already being used by the open-source-case-studies Git repository, under that name, but now it is part of the Frama-C release). The upcoming Frama-C release will update that.

analysis-scripts relies on some GNU-specific, Make 4.0+ features. This version of Make (or a more recent one) is already available on most Linux distributions and on Homebrew for MacOS, but in the worst case, downloading and compiling GNU Make from source should be an option.

Basically, what these files provide is a set of semi-generated Makefile targets and rules that automate most of the steps typically used by Frama-C/EVA developers to set up a new case study. The scripts themselves are extensively used in the open-source-case-studies repository, which serves as use example.

Using analysis scripts

To illustrate the use of analysis-scripts, we picked one project from ffaraz's awesome-cpp repository: GHamrouni's Recommender, a library from the Machine Learning section.

We start by cloning the repository1:

git clone git@github.com:GHamrouni/Recommender.git

1 Note: at the time of this posting, the latest commit is 649fbfc. The results presented later in this tutorial may differ in the future. You can select this commit via git checkout 649fbfc in case this happens.

Then, inside the newly-created Recommender directory, we look for its build instructions. Many C open-source libraries and tools are based on autoconf/configure/make, which may require running some commands before all headers are available (e.g., ./configure often produces a config.h file from a config.h.in template). Frama-C does not require compiling the sources, so in most cases you can stop before running make. However, since Frama-C does require preprocessor flags, you can use existing Makefiles to cheaply obtain that information.

Obtaining preprocessor flags from a compile_commands.json

In order to find out which preprocessor flags are needed for a given program, you can use tools such as CMake or Build EAR to produce a JSON compilation database, commonly called compile_commands.json. This is a JSON file which contains the list of commands (including all of their arguments) to be given to the compiler. It contains many options which are irrelevant to Frama-C (such as warning and optimization flags, typically -W and -O), but it also contains preprocessor flags, mostly -I and -D, which we are interested in.

The compile_commands.json file can be produced as follows:

  1. If the project is based on CMake, add -DCMAKE_EXPORT_COMPILE_COMMANDS=ON to the cmake command-line, e.g. instead of cmake <source dir>, use cmake <source dir> -DCMAKE_EXPORT_COMPILE_COMMANDS=ON.

  2. If the project is based on Makefile, use Build EAR. After Build EAR is installed, you just have to prefix make with bear: typing bear make is usually enough to obtain the JSON database.

Note: Frama-C 17 (Chlorine) includes option -json-compilation-database, which allows using compile_commands.json directly, rendering the next step unnecessary.

Once you have the file, simply grep it for -I and -D flags, e.g:

grep '\-I\|\-D' compile_commands.json

Those flags should be added to the preprocessor flags in Frama-C's Makefile (described in the next section), CPPFLAGS.

Note that these recommendations may not work in complex setups. Manual inspection of the commands used during compilation might be necessary to obtain all necessary flags.

Preparing an analysis template

We will create a Makefile for Frama-C, to manage dependencies and help re-run analyses. In order to avoid having to type make -f <name> each time, we will name it GNUmakefile, for the following reasons:

  1. GNU Make gives preference to GNUmakefile over Makefile if both exist, so the default file used when typing make will be ours, even if the project already has its own Makefile;

  2. This avoids having to rename/overwrite existing makefiles (or, worse, having Frama-C's Makefile erased when re-running ./configure);

  3. The analysis-scripts Makefile already relies on some features specific to GNU Make, so there is no compatibility downside here.

If you want to name your Makefile otherwise, just remember to always add -f <your makefile name> to the make commands presented in this tutorial.

Our GNUmakefile will be created with content based on the template available on Frama-C's Github repository.

In this tutorial, we consider that Frama-C is installed and in the PATH to keep the template concise.

include $(shell frama-c-config -print-share-path)/analysis-scripts/frama-c.mk

# Global parameters
FCFLAGS     +=


# Default targets
all: main.eva

# Input files
main.parse: <TO BE COMPLETED>

The essential element to complete this template is the list of files to be parsed. Other arguments, such as flags for the C preprocessor (CPPFLAGS), for the Frama-C kernel (FCFLAGS) and for the EVA plug-in (EVAFLAGS) are also to be filled by the user, when necessary.

Finally, note that the target name (main) is completely arbitrary. You can have multiple targets if your code contains multiple main functions. The important part is the use of the suffixes .parse and .eva, which are hard-coded in the analysis-scripts' Makefile to generate targets with the appropriate dependencies and rules.

The .parse suffix is used by analysis-scripts to set the list of source files to be parsed. It is associated to an .eva target which runs the EVA analysis. This target is generated by analysis-scripts itself; we just need to tell the Makefile that it should be run when we run make all, or simply make, since all is the first rule in our Makefile.

Setting sources and testing parsing

The list of source files to be given to Frama-C can be obtained from the compile_commands.json file. However, it is often the case that the software under analysis contains several binaries, each requiring a different set of sources. The JSON compilation database does not map the sources used to produce each binary, so it is not always possible to entirely automate the process. You may have to manually adjust the sets of files to be given to Frama-C. For a whole-program analysis with EVA, in particular, you might want to ensure that there is exactly one file defining a main function.

In the case of Recommender, since it is a library, the src directory does not contain a main function. However, the test directory contains two files, each of them defining a main function. In this tutorial, we will use the test.c file as the main entry point of the analysis. We could also have used the -lib-entry option on one or more functions in the library. More advanced users of Frama-C may prefer this option though we will keep it simple and use the main function in test.c as unique entry point in this tutorial.

Therefore, the list of sources to be filled in the main.parse target is the following:

main.parse: src/*.c test/test.c

We can test that Frama-C is able to parse the sources:

make main.parse

If you are strictly following this tutorial, you should have the following error:

[kernel] Parsing test/test.c (with preprocessing)
test/test.c:1:25: fatal error: recommender.h: No such file or directory
 #include "recommender.h"
compilation terminated.

This is because we never included the actual -I lines that we found in the compile_commands.json file. Note that they include flag -I../../src/, which is relative to one of the subdirectories in tools/*. Since our Makefile (and thus Frama-C) will run relative to the base directory in Recommender, the actual include directive needs to be -Isrc, which we add to CPPFLAGS:


Running make main.parse now should succeed. Run it again. You will notice that nothing is done: thanks to the dependencies managed by analysis-scripts, unless you modify one of the source files, or the flags given to Frama-C (CPPFLAGS or FCFLAGS), Frama-C will not waste time reparsing the results: they have already been saved inside the main.parse directory.

Contents of the .parse directory

For each .parse target, analysis-scripts will create a corresponding directory with several files:

  • command: the command-line arguments used by Frama-C;

  • framac.ast: the pretty-printed normalized AST produced by Frama-C;

  • stats.txt: performance information (user time and memory consumption);

  • warnings.log: warnings emitted during parsing;

  • framac.sav: a Frama-C save file (a binary) with the result of parsing;

  • parse.log: the entire log of the parsing (includes the warnings in warnings.log).

All of these files are used internally by the analysis scripts or some other tools (notably for regression testing and profiling purposes), however only the last 2 files are occasionally relevant for the end user:

  • framac.sav can be used with frama-c -load, for instance when trying different plug-ins;

  • parse.log contains a copy of all messages emitted during parsing.

If we want to load the parsed files in the Frama-C GUI, we can use either frama-c -load framac.sav, or more conveniently, make main.parse.gui. The advantage of the latter is that it will generate the .parse directory if it has not been done already.

This concludes the first part of this tutorial. In the next post, we will run EVA using our Makefile, then iterate to improve the analysis.

Tuesday, June 13 2017

Frama-C 15 (Phosphorus) released, and open source case studies

Frama-C 15 (Phosphorus) has been released, and the OPAM package is already available! A MinGW-based OPAM package, distributed by fdopen's MinGW OPAM repository, is also available.

In this post, we briefly highlight two new features in this release. We also announce the release of a new Github repository, open-source-case-studies, which contains some snapshots of code bases ready to be analyzed with Frama-C/EVA.

Highlighted new features

E-ACSL in the default release

One notable change in this release is the direct integration of E-ACSL: instead of having to install OPAM packages frama-c and frama-c-e-acsl, you only need to install frama-c.

E-ACSL enables runtime verification in Frama-C, serving as an efficient tool for detecting undefined behavior and for debugging ACSL specifications. It can be used in a "stand-alone" mode (e.g. with assertions generated by the RTEgen plug-in), or in combination with EVA, in which case its instrumentation is more efficient: EVA only generates ACSL assertions for the properties that it cannot prove, thus greatly reducing E-ACSL's instrumentation.

Note that, due to the usage of jemalloc and some technical details, E-ACSL is disabled by default in Mac and Windows.

Better pretty-printing of #include directives

One of the drawbacks of the -print option of Frama-C was the fact that the code was entirely preprocessed, expanding a Hello world example to several hundreds of lines, due to the expansion of #include <stdio.h> and derived files.

There are now two options, -print-libc and -no-print-libc (the latter is enabled by default) which control the folding/unfolding of #include directives in pretty-printed code. More specifically, if your original code is:

#include <stdio.h>

int main() {
    printf("hello world!\n");
    return 0;

Then the result of -print will be:

/* Generated by Frama-C */
#include "errno.h"
#include "stdarg.h"
#include "stddef.h"
#include "stdio.h"
/*@ requires valid_read_string(format);
    assigns \result, __fc_stdout->__fc_FILE_data;
    assigns \result
      \from (indirect: __fc_stdout->__fc_FILE_id),
            __fc_stdout->__fc_FILE_data, (indirect: *(format + (0 ..)));
    assigns __fc_stdout->__fc_FILE_data
      \from (indirect: __fc_stdout->__fc_FILE_id),
            __fc_stdout->__fc_FILE_data, (indirect: *(format + (0 ..)));
int printf_va_1(char const *format);

int main(void)
  int __retres;
  printf_va_1("hello world!\n");
  __retres = 0;
  return __retres;

There are two interesting things to notice here:

  1. Some #include directives are present at the beginning of the file. These directives correspond to all files from the Frama-C standard library whose identifiers were present in the (expanded) original code. For instance, errno.h is present because Frama-C's stdio.h includes it. As you can see, the mechanism does not guarantee a minimal number of includes, but it is much cleaner than having all files expanded;

  2. The specification of printf_va_1 is visible. This is due to the fact that the Variadic plug-in (which is enabled by default on Frama-C 15 (Phosphorus)) generated this specification - it is not part of the standard Frama-C library. In fact, printf_va_1 is a specific instantiation of the variadic printf function. You can disable the automatic variadic translation with -variadic-no-translation, in which case -print will result in:

/* Generated by Frama-C */
#include "errno.h"
#include "stdarg.h"
#include "stddef.h"
#include "stdio.h"
int main(void)
  int __retres;
  printf("hello world!\n");
  __retres = 0;
  return __retres;

The Phosphorus release also includes, as usual, a series of bug fixes and minor improvements. Consult the Changelog for more details.

Open source case studies

A new Github repository on the Frama-C organization, open-source-case-studies, has been created to help users quickly run Frama-C (and EVA in particular) in more realistic code bases, which includes different sorts of open-source code; some of them are very small (a single file) while others contain significantly larger bases. Their usage is very simple: once you have installed Frama-C and put it in the PATH, enter one of the case study directories and run:

  • make to parse and run EVA;

  • make <target>.eva.gui to open the Frama-C GUI and view the results.

The target names vary on each case study, and can be obtained via make help. Note that this will show only the base target name, from which other targets are derived (e.g. <target>.parse, <target>.eva, <target>.eva.gui).

All case studies include a Makefile, which uses the files in fcscripts to generate targets and Makefile rules to allow running EVA quickly. Among the facilities provided by these scripts, we highlight:

  • templates for Frama-C parametrization (i.e. variables CPPFLAGS, FCFLAGS and EVAFLAGS to delineate which options are related to preprocessing, parsing and running EVA), including helpful default parameters;

  • automatic target dependencies on command line arguments: Frama-C reparses files only when they are modified, and re-runs EVA only when command line arguments change;

  • saving of intermediate results in directories (for easy comparison via Meld), to run other plug-ins without having to re-run EVA (e.g. frama-c -load <target>.eva/framac.sav ...).

Note, however, that there are some caveats concerning this repository:

  1. It is not representative of the scale of programs that Frama-C/EVA can handle; indeed, all large code bases where Frama-C/EVA is applied consist in industrial code that cannot be shared;

  2. One of the main purposes of the repository (internally) is to serve for non-regression testing, which means that some analyses are not fully parametrized;

  3. Some case studies include code that is not ideally dealt with by EVA, but may be useful for other plug-ins.

Those caveats aside, we hope this repository will give practical examples and help you to parametrize your own analyses. If you also have some interesting open source code bases on which to run EVA, you can submit them to us as a Github pull requests. This will make it easier to compare the behavior of future versions of Frama-C on such code, and to benefit from improvements in the analyzer.

Tuesday, April 11 2017

A simple Eva tutorial, part 3

On the previous post we've seen how to run Eva, but at the end we had a NON TERMINATING FUNCTION for a function that is supposed to always terminate, a likely indication that a definitive undefined behavior has been found in the analysis. In this post, we will see how to diagnose such cases, using derived plug-ins and the GUI.

We will reuse the save file produced at the end of the analysis, value2.sav.

When the GUI is not enough

Usually, after running the value analysis in the command-line, we launch the GUI to visualize the results:

frama-c-gui -load value2.sav

In this case, because of the NON TERMINATING FUNCTION message, we know that at some point in the program we will have red statements in the GUI, which indicate unreachable code.

By scrolling down from the main function, we reach the non-terminating statement, which is a call to test_x25519:

Unreachable code in the Frama-C GUI

Note the red semicolon at the end of the statement, and the fact that the following statements are also red. If we click on the statement, the Information panel says that This call never terminates.

You can right-click on the function and Go to the definition of test_x25519, and you will find the same thing inside, this time a call to crypto_x25519_public_key, and so on, until you reach fe_tobytes, which is slightly different: it contains a for loop (defined via a macro FOR), after which all statements are red, but the loop itself is not an infinite loop: it simply iterates i from 0 to 5. How can this be non-terminating?

The answer, albeit non-intuitive, is simple: there is one statement inside the loop which is non-terminating, but not during the first iteration of the loop. Because the GUI colors are related to the consolidated result of all callstacks (i.e., if there is at least one path which reaches a statement, it is marked as reachable), it cannot show precisely which callstack led to the non-termination. To better understand what happens here, we will use the Nonterm plug-in.

Nonterm to the rescue

Nonterm is a small plug-in that uses the result of the value analysis to display callstack-wise information about non-terminating statements, by emitting warnings when such statements are found. It requires Eva to have been executed previously, but it runs very quickly itself, so you do not need to save its results. Close the GUI and re-run it again, this time with Nonterm:

frama-c-gui -load value2.sav -then -nonterm -nonterm-ignore exit

The -nonterm-ignore exit argument serves to minimize the number of warnings related to calls to the libc exit() function, which is always non-terminating.

The warnings generated by Nonterm are displayed in the Messages panel, after those emitted by Eva.

Examples of Nonterm warnings

The warnings display the non-terminating callstacks. The order of the warnings themselves is not relevant. However, some kinds of warnings are more useful than others. Here is a rough indication of their relevance, from most to least precise:

  1. Non-terminating statements;
  2. Non-terminating loops;
  3. Non-terminating function calls;
  4. Unreachable returns.

In our analysis, the first (and only) warning about a non-terminating statement is the following:

Non-terminating statement

Note a few important details about the Frama-C GUI:

  • When you click on the warning in the Messages panel, the GUI focuses on the related statement.
  • When a statement has associated annotations (here, two warnings), the focus is placed on the first annotation, instead of the statement itself. This does not imply that the annotation itself is related to this specific warning.
  • The property status indicators (colored circles, or bullets on the left of each property) display the consolidated status of all callstacks; in particular, if the property is definitively valid in one callstack, but possibly/definitively invalid in another, the GUI displays a yellow bullet.

Nonterm restores some of the information lost due to callstack consolidation. The highlighted warning in particular gives us the following information:

  1. There exists a stack trace in which statement h5 -= c5 << 25 does not terminate;
  2. There is exactly one stack trace in which the statement never terminates; all other stack traces (which are not shown in the warning) terminate.

Currently, it is not possible to select a stack trace from the Messages panel, but we can do so using the Values panel. If we switch to it (keeping the statement highlighted in the source code), we can see that there are 40 different stack traces reaching this point.

Values Panel

The Values panel is arguably the most powerful inspection tool for the Eva plug-in in the Frama-C GUI. Some of its features were presented in earlier posts, but for the sake of completeness, here are some commented screenshots:

Values panel

The values displayed in this panel are related to the green highlighted zone in the Cil source.

The Ctrl+E shortcut is equivalent to highlighting a statement, then right-clicking Evaluate ACSL term. The Ctrl+Shift+E shortcut is slightly more powerful: it also evaluates terms, such as \valid(p). This command is not available from any menus.

The Multiple selections checkbox allows adding several expressions to be compared side-by-side. When checked, highlighting an expression in the same statement adds a column with its value. Note that highlighting a different statement results in resetting all columns.

The three checkboxes to the right are seldom used: Expand rows simply expands all callstacks (but generates visual clutter); Consolidated value displays the row all (union of all callstacks); and Per callstack displays a row for each separate callstack.

The callstacks display has several contextual menus that can be accessed via right-clicks.

Callstacks display

Let us start from the bottom: right-clicking on a callstack shows a popup menu that allows you to focus on a given callstack. This focus modifies the display in the Cil code viewer: reachability will only be displayed for the focused callstack(s). We will come back to that later.

Right-clicking on a cell containing a value allows filtering on all callstacks for which the expression has the same value. This is often used, for instance, to focus on all callstacks in which a predicate evaluates to invalid or unknown.

Finally, clicking on the column headers allows filtering columns.

Note that the Callstacks column header displays a pipette icon when a filter is being applied, to remind you that other callstacks exist.

Filtering non-terminating callstacks

In our code, despite the existence of 40 callstacks, only one of them is non-terminating. If you highlight the 0 ≤ c5 expression before statement h5 -= c5 << 25, you will see that only a single callstack displays invalid in the column 0 ≤ c5. Focus on this callstack using the popup menu, then highlight expression c5 in the Cil code. You will obtain the following:

Focused on a non-terminating callstack

As you can see, the GUI now displays the statements following h5 -= c5 << 25 in red, indicating thay they are unreachable in the currently focused callstacks. The exact value that caused this is shown in column c5: -1. The C standard considers the left-shift of a negative number as undefined behavior. Because -1 is the only possible value in this callstack, the reduction caused by the alarm leads to a post-state that is <BOTTOM>.

Proceeding with the analysis

To allow Eva to continue the analysis of the code, we need to modify it in some way. Since we are not experts in cryptography, we are unable to provide a definitive explanation why the code was written this way. In any case, it is not specific to Monocypher, but also present in TweetNaCl and ref10, two cryptographic libraries.

It is likely that replacing the signed carry variables in function fe_mul with unsigned ones would get rid of the undefined behavior, without changing the expected behavior of the code. However, without a more formal analysis performed by a cryptographer, this is just guesswork. Still, we need to do something to be able to continue the analysis (and possibly spot more undefined behaviors), such as changing the declarations of variables c0 to c9 to u64 instead of i64. Then, re-parse the sources, re-run the analysis, and keep iterating.

Ideas for complex situations

In the beta version of this post, we were using version 0.1 of Monocypher, which had a different version of functions related to fe_mul. In particular, some of the functions were taken from TweetNaCl, and the code was not unrolled the same way as in Monocypher 0.3. One of the consequences was that Nonterm was unable to show as clear a picture as in this case; it was necessary to perform syntactic loop unrolling (e.g., using loop pragma UNROLL) just to be able to clearly see in the GUI which statement was non-terminating.

Future developments in Frama-C and in the Eva plug-in will help identifying and visualizing such situations more easily.


We would like to thank loup-vaillant (Monocypher's author) for the discussions concerning Monocypher and Eva's analysis. New versions of Monocypher have been released since the analysis performed for this series of posts, which do not present the undefined behavior described in this post.

Friday, March 17 2017

A simple Eva tutorial, part 2

On the previous post we've seen some recommendations about using Frama-C/Eva, and some tips about parsing. In this post, we will see how to run Eva, and how to quickly setup it for a more precise result.

We will reuse the save file produced at the end of the parsing, parsed.sav.

First run of Eva

The default parameters of Eva are intended for a fast analysis. In Frama-C 14 (Silicon), option -val-builtins-auto is recommended to enable the usage of built-in functions that improve the precision and sometimes the speed of the analysis1.

1 This option will be enabled by default in Frama-C 15 (Phosphorus).

The following command-line should result in a relatively quick first analysis:

frama-c -load parsed.sav -val-builtins-auto -val -save value.sav

Note that we save the result in another file. It can be reused as input for another analysis, or visualization in the GUI.

The analysis will likely output many alarms, some due to loss of precision, others due to an incorrect setup. Here are a few important alarms concerning an incorrect setup:

  1. Missing code or specification

    file.c:42:[kernel] warning: Neither code nor specification for function foo, generating default assigns from the prototype

    There are two major causes for this warning: (1) the file containing the function definition was not given to Frama-C during parsing; or (2) the function has no source code and no ACSL specification was given.

    In the first case, the solution is to include the missing source file. Parsing will succeed even if only a declaration (function prototype) is present, but Eva requires more than that. It may be necessary to return to the parsing stage when this arrives.

    In the second case, you must supply an ACSL specification for the function, otherwise Eva will assume it has no effect, which may be unsound. To do it with minimal modifications to the original code, you can do the following:

    1. create a file, say stubs.h;
    2. copy the function prototype to be stubbed in stubs.h (adding the necessary #includes for the types used in the prototype);
    3. add an ACSL specification to this prototype;
    4. include stubs.h in the original source, either by adding #include "stubs.h", or using GCC's -include option (e.g. -cpp-extra-args="-includestubs.h", without spaces between -include and the file name).
  2. Missing assigns clause, or missing \from

    When analyzing functions without source code, Eva imposes some constraints on the ACSL specification: they must contain assigns clauses, and these clauses must have \from dependencies. Otherwise, warnings such as the following may be generated:

    foo.c:1:[value] warning: no 'assigns \result \from ...' clause specified for function foo
    foo.c:3:[value] warning: no \from part for clause 'assigns *out;' of function foo
    foo.c:6:[kernel] warning: No code nor implicit assigns clause for function foo, generating default assigns from the prototype

    The following is an example of an incomplete specification:

    /*@ assigns *out; */
    void foo(int in, int *out);

    Even if it contains an \assigns clause for pointer out, it does not say where the result comes from. Adding \from in, for instance, makes the specification complete from the point of view of Eva.

    Note: Eva cannot verify the correctness of the specification in the absence of code, especially that of ensures clauses. If you provide an incorrect specification, the result may be unsound. For that reason, it is often useful to write a simplified (or abstract) implementation of the function and then run the analysis. If Eva has both the code and the specification, it is able to check ensures clauses and detect some kinds of errors.

Running Eva on monocypher

Running Eva on parsed.sav will start the value analysis on the main function defined in test.c. Due to the large number of small functions in Monocypher, Eva will output a huge amount of lines, whenever a new function is entered. Adding option -no-val-show-progress will omit messages emitted whenever entering a new function.

Also, the fact that this code contains lots of small functions with few or no side-effects is a very strong indicator that -memexec-all will be very helpful in the analysis.

Memexec, which is part of Eva, acts as a cache that allows reusing the result of function calls when their memory footprint is unchanged. It dramatically improves performance.

Combining both options, we obtain the following command-line:

frama-c -load parsed.sav -val -val-builtins-auto \
        -no-val-show-progress -memexec-all -save value.sav

The analysis will then start and emit several warnings (mainly due to imprecisions). It should finish in a few seconds, depending on your processor speed.

Improving Eva results

After running the value analysis, it is a good time to check what the result looks like, using the GUI:

frama-c-gui -load value.sav

In the screenshot below, we indicate some parts of the GUI that are useful when inspecting Eva results (besides the source view). We also indicate some parts that are never (or rarely) used with Eva.

Frama-C GUI for Eva

Note that the Properties tab (between Console and Values) is not updated automatically: you need to click on the Refresh button before it outputs anything, and after changing filters.

Several tips concerning this panel were presented in a previous post about the GUI. If you follow them, you will be able to make the Properties panel show the total of Unknown (unproven) properties for the entire program, and only those. This number is often similar to the number of messages in the Messages panel.

In Monocypher, after setting the filters to show every Unknown property in the entire program, and clicking Refresh, we obtain over 900 unproven properties. Since the analysis was not tuned at all for precision (other than with -val-builtins-auto), this number is not particularly surprising.

A quick way to improve on results is to use the Loop analysis plug-in.

The Loop analysis plug-in performs a mostly syntactic analysis to estimate loop bounds in the program (using heuristics, without any soundness guarantees) and outputs a list of options to be added to the value analysis. Running Eva again with these options should improve the precision, although it may increase analysis time. Loop analysis' main objective is to speed up the repetitive task of finding loop bounds and providing them as semantic unrolling (-slevel) counters. The analysis may miss some loops, and the estimated bounds may be larger or smaller, but overall it minimizes the amount of manual work required.

Loop analysis does not depend on Eva, but if it has been run, the results may be more precise. In Monocypher, both commands below give an equivalent result (the difference is not significative in this context):

frama-c -load parsed.sav -loop
frama-c -load value.sav -loop

In both cases, Loop analysis' effect is simply to produce a text output that should be fed into Eva for a new analysis:

[loop] Add this to your command line:
       -val-slevel-merge-after-loop crypto_argon2i \
       -val-slevel-merge-after-loop crypto_blake2b_final \

You should, by now, use a shell script or a Makefile to run the Frama-C command line, adding all the -val-slevel-merge-after-loop and -slevel-function lines to your command.

Let us consider that the environment variable LOOPFLAGS contains the result of Loop analysis, and EVAFLAGS contains the flags mentioned previously (-no-val-show-progress, -val-builtins-auto and -memexec-all). Then the following command will re-run Eva with a more detailed (and, hopefully, precise) set of parameters:

frama-c -load parsed.sav $LOOPFLAGS -val $EVAFLAGS -save value2.sav

Opening this file on the GUI will indicate approximately 500 warnings, which is still substantial, but much better than before. Improvements to Loop analysis in the next release of Frama-C will allow this number to be reduced slightly.

The basic tutorial is over, but there are several paths to choose

From here on, there are several possibilities to reduce the imprecisions in the analysis:

  • Inspect alarms and see if their functions contain loops that were not inferred by Loop analysis; if so, adding their bounds to -slevel-function can improve the precision of the analysis;

  • Increase the precision using other parameters, such as -plevel;

  • Stub libc functions to emulate/constrain inputs when relevant;

  • Use Eva's abstract domains (e.g. -eva-equality-domain) to improve precision;

  • Stop at the first few alarms (-val-stop-at-nth-alarm), to track more closely the sources of imprecision. However, when there are hundreds of alarms, this is more useful as a learning experience than as a practical solution.

Each solution is more appropriate in a specific situation. Here are a few tips for an intermediate-level user of Eva:

  1. Functions that perform array initialization are often simple (a loop with a few assignments per iteration), so unrolling them completely should not slow down the analysis excessively. The Loop analysis plug-in usually works with them, but some pattern variations may throw it off. You may want to check the proposed values in such loops. Because initialization happens early in program execution, checking such loops may yield good results.

  2. The plevel parameter is often used in response to messages such as:

    monocypher.c:491:[kernel] more than 200(255) elements to enumerate. Approximating.

    where the first number is the current plevel (by default, 200), and the second number is the amount that would be required to avoid the approximation. In this case, -plevel 255 would be reasonable, but if you had more than 200(67108864) elements, for instance, it would not be helpful to set the plevel to such a high value.

  3. Stubbing is a good approach when dealing with functions that are closely system-dependent, specifically input functions that read from files, sockets, or from the command-line. Check the Frama-C builtins in __fc_builtin.h, they provide some useful primitives for abstracting away code with non-deterministic functions.

  4. Eva's domains have specific trade-offs between precision and efficiency, and some have broader applicability than others. Future posts in this blog will describe some of these domains, but as a rule of thumb, two domains that are fairly low-cost and generally useful are -eva-equality-domain (for syntactic equalities) and -eva-gauges-domain (for some kinds of loops).

  5. The Messages panel in the GUI is chronologically sorted, so it can help the user follow what the analysis did, to try and identify sources of imprecision. However, even in this case, there is still an advantage to using -val-stop-at-nth-alarm: because the execution stops abruptly, there are possibly less callstacks displayed in the GUI, and therefore it may be easier to see at a glance which parts of the code were actually executed, and the dependencies between values that lead to the alarm.

Non-terminating function?

The "beginner" tutorial ends here, but one thing that you may have noticed after running Eva, is the dreaded "non terminating function" message at the end of the analysis:

[value:final-states] Values at end of function main:

This indicates that, somewhere during the analysis, a completely invalid state was found, and Eva could not proceed. This usually indicates one of the following:

  1. Eva's setup is incorrect: most likely, some function has missing or incorrect specifications, or some case that cannot be currently handled by Eva (e.g. recursive calls) was encountered.
  2. A definitively undefined behavior is present in the code, which may or may not lead to an actual bug during execution. In either case, it should be taken care of.

We will see how to handle such situations in the next post, using the GUI and the Nonterm plug-in (-nonterm), in a tutorial destined for beginners and experienced users alike.

Tuesday, March 7 2017

A simple Eva tutorial, part 1

(with the collaboration of T. Antignac, Q. Bouillaguet, F. Kirchner and B. Yakobowski)

This is the first of a series of posts on a new Eva tutorial primarily aimed at beginners (some of the later posts contain more advanced content).

Reminder: Eva is the new name of the Value analysis plug-in.

There is a Value tutorial on Skein-256 that is part of the Value Analysis user manual. The present tutorial is complementary and presents some new techniques available in Frama-C. If you intend to use Eva, we recommend you read the Skein-256 tutorial as well because it details several things that will not be repeated here. (However, it is not required to have read the Skein-256 before this one.)

The source code used in this tutorial is the version 0.3 of Monocypher, a C99-conformant cryptographic library that also includes a nice test suite.

Note: newer versions of Monocypher are available! For this tutorial, please ensure you download version 0.3, otherwise you will not obtain the same behavior as described in this tutorial.

Future posts will include more advanced details, useful for non-beginners as well, so stay tuned!

Starting with Frama-C/Eva

This tutorial will use Monocypher's code, but it should help you to figure out how to analyze your code as well. First and foremost, it should help you answer these questions:

  1. Is my code suitable for a first analysis with Frama-C/Eva?
  2. How should I proceed?

(Un)Suitable code

There are lots of C code in the wild; for instance, searching Github for language:C results in more than 250k projects. However, many of them are not suitable candidates for a beginner, for reasons that will be detailed in the following.

Note that you can analyze several kinds of codes with Frama-C/Eva. However, without previous experience, some of them will raise many issues at the same time, which can be frustrating and inefficient.

Here is a list of kinds of code that a Frama-C/Eva beginner should avoid:

  1. Libraries without tests

    Eva is based on a whole-program analysis. It considers executions starting from a given entry point. Libraries without tests contain a multitude of entry points and no initial context for the analysis. Therefore, before analyzing them, you will have to write your own contexts1 or test cases.

  2. Command-line tools that rely heavily on the command-line (e.g. using getopt), without test cases.

    Similar to the previous situation: a program that receives all of its input from the command-line behaves like a library. Command-line parsers and tools with complex string manipulation are not the best use cases for the Eva's current implementation. A fuzzer might be a better tool in this case (though a fuzzer will only find bugs, not ensure their absence). Again, you will have to provide contexts1 or test cases.

  3. Code with lots of non-C99 code (e.g. assembly, compiler extensions)

    Frama-C is based on the C standard, and while it includes numerous extensions to handle GCC and MSVC-specific code, it is a primarily semantic-based tool. Inline assembly is supported syntactically, but its semantics needs to be given via ACSL annotations. Exotic compiler extensions are not always supported. For instance, trying to handle the Linux kernel without previous Frama-C experience is a daunting task.

  4. Code relying heavily on libraries (including the C standard library)

    Frama-C ships with an annotated standard library, which has ACSL specifications for many commonly-used functions (e.g. string.h and stdlib.h). This library is however incomplete and in some cases imprecise2. You will end up having to specify and refine several functions.

1 A context, here, is similar to a test case, but more general. It can contain, for instance, generalized variables (e.g. by using Frama_C_interval or ACSL specifications).

2 A balance is needed between conciseness (high-level view), expressivity, and precision (implementation-level details). The standard library shipped with Frama-C tries to be as generic as possible, but for specific case studies, specialized specifications can provide better results.

Each new version of Frama-C brings improvements concerning these aspects, but we currently recommend you try a more suitable code base at first. If your objective is to tackle such a challenging code base, contact us! Together we can handle such challenges more efficiently.

This explains why Monocypher is a good choice: it has test cases, it is self-contained (little usage of libc functions), and it is C99-conforming.

The 3-step method

In a nutshell, the tutorial consists in performing three steps:

  1. Parsing the code (adding stubs if necessary);
  2. Running Eva with mostly default parameters (for a first, approximated result);
  3. Tuning Eva and running it again.

The initial parsing is explained in this post, while the other steps will be detailed in future posts.

General recommendations

Before starting the use of Frama-C, we have some important general recommendations concerning the Eva plug-in:

  1. DO NOT start with the GUI. Use the command-line. You should consider Frama-C/Eva as a command-line tool with a viewer (the GUI). The Frama-C GUI is not an IDE (e.g. you cannot edit code with it), and Eva does not use the GUI for anything else other than rendering its results.

  2. Use scripts. Even a simple shell script, just to save the command-line options, is already enough for a start. For larger code bases, you will want Makefiles or other build tools to save time.

  3. Use frama-c -kernel-help (roughly equivalent to the Frama-C manpage) and frama-c -value-help to obtain information about the command-line options. Each option contains a brief description of what it does, so grepping the output for keywords (frama-c -kernel-help | grep debug for instance) is often useful. Otherwise, consider Stack Overflow - there is a growing base of questions and answers available there.

  4. Advance one step at a time. As you will see, the very first step is to parse the code, and nothing else. One does not simply run Eva, unless he or she is very lucky (or the program is very simple). Such precautions may seem excessive at first, but being methodical will save you time in the long run.

Parsing the code

Often overlooked, this step is erroneously considered as "too simple" ("just give all files to the command-line!"). In a few cases, it is indeed possible to run frama-c *.c -val and succeed in parsing everything and running Eva.

When this does not work, however, it is useful to isolate the steps to identify the error. Here are some general recommendations:

  1. Start with few files, and include more when needed

    Note that parsing may succeed even if some functions are only declared, but not defined. This will of course prevent Eva from analyzing them. If so, you may have to return to this step later, adding more files to be parsed.

  2. Ensure that preprocessor definitions and inclusions are correct

    Several code bases require the use of preprocessor definitions (-D in GCC) or directory inclusions (-I in GCC) in order for the code to be correctly preprocessed. Such information is often available in Makefiles, and can be given to Frama-C using e.g. -cpp-extra-args="-DFOO=bar -Iheaders".

    -cpp-extra-args is the most useful option concerning this step. It is used in almost every case study, and often the only required option for parsing. Note: old releases of Frama-C did not have this option, and -cpp-command was recommended instead. Nowadays, -cpp-command is rarely needed and should be avoided, because it is slightly more complex to use.

  3. Make stubs for missing standard library definitions

    Frama-C's standard library is incomplete, especially for system-dependent definitions that are not in C99 or in POSIX. Missing constants, for instance, may require the inclusion of stub files (e.g. stubs.h) with the definitions and/or the ACSL specifications. A common way to include such files is to use GCC's -include option, documented here.

  4. Save the result

    Use Frama-C's -save/-load options to avoid having to reparse the files each time. There is no default extension associated with Frama-C save files, although .sav is a common choice. For instance, running:

    frama-c <parse options> -save parsed.sav

    will try to parse the program and, if it succeeds, will save the Frama-C session to parsed.sav. You can then open it in the GUI (frama-c-gui -load parse.sav), to see what the normalized source code looks like, or use it as an input for the next step.

Reminder: for the Eva plug-in, the GUI is not recommended for parametrizing/tuning an analysis. It is best used as a viewer for the results.

The default output of Eva is rather verbose but very useful for studying small programs. For realistic case studies, however, you may want to consider the following options:

  • -no-val-show-progress: does not print when entering a new function. This will be the default in Frama-C 15 (Phosphorus);

  • -value-msg-key=-initial-state: does not print the initial state;

  • -value-msg-key=-final-states: does not print the final states of the analysis.

Note the minus symbols (-) before initial-state and final-states. They indicate we want to hide the messages conditioned by these categories.

Parsing monocypher

As indicated above, the naive approach (frama-c *.c) does not work with monocypher:

$ frama-c *.c

[kernel] Parsing FRAMAC_SHARE/libc/__fc_builtin_for_normalization.i (no preprocessing)
[kernel] Parsing monocypher.c (with preprocessing)
[kernel] Parsing more_speed.c (with preprocessing)
[kernel] syntax error at more_speed.c:15:
         14    // Specialised squaring function, faster than general multiplication.
         15    sv fe_sq(fe h, const fe f)
         16    {
         17        i32 f0 = f[0]; i32 f1 = f[1]; i32 f2 = f[2]; i32 f3 = f[3]; i32 f4 = f[4];

The first line is always printed when Frama-C parses a source file, and can be ignored.

The second line indicates that monocypher.c is being parsed.

The third line indicates that more_speed.c is now being parsed, implying that the parsing of monocypher.c ended without issues.

Finally, we have a parsing error in more_speed.c, line 15. That line, plus the lines above and below it, are printed in the console.

Indeed, the file more_speed.c is not a valid C source (sv is not a type defined in that file, and it does not include any other files). But this is not an actual issue, since more_speed.c is not part of the library itself, simply an extra file (this can be confirmed by looking into the makefile). Thus we are going to restrict the set of files Frama-C is asked to analyze.

Note: Frama-C requires the entire program to be parsed at once. It may be necessary to adapt compilation scripts to take that into account.

We also see that the rule for building monocypher.o includes a preprocessor definition, -DED25519_SHA512. We will add that to our parsing command, which will then become:

frama-c test.c sha512.c monocypher.c -cpp-extra-args="-DED25519_SHA512" -save parsed.sav

The lack of error messages is, in itself, a resounding success.

The first part of this tutorial ends here. See you next week!

For now, you can start reading the Skein-256 tutorial available at the beginning of the Eva manual. Otherwise, if you already know Eva (and still decided to read this), you may try to find some undefined behavior (UB) in Monocypher 0.3!

Hint: There is indeed some UB, although it does not impact the code in any meaningful way. At least not with today's compilers, maybe in the future... and anyway, it has been fixed in the newer releases of Monocypher.

Tuesday, December 13 2016

Frama-C Silicon has been released!

Frama-C 14 (Silicon) has just been released. In this post, we present a few additions that should help everyday usage of Value EVA.

Value is now EVA

The Value analysis plug-in has been renamed EVA, for Evolved Value Analysis. It has a new architecture that allows plugging abstract domains, among other features. It is a truly remarkable evolution which this post is too small to contain1, however, so it will presented in more detail later.

1 Facetious reference to Fermat's Last Theorem

Automatic built-in matching for libc functions

One of the new user-friendly features is the -val-builtins-auto option, which avoids having to memorize which built-in to use for each libc function that has one, namely malloc, free, and some floating-point and string-related functions (e.g. pow and strlen).

For instance, consider the following toy program, which simply allocates a buffer, copies a string into it, then allocates a buffer of the right size for the string, and stores it there.

// file.c
#include <stdio.h>
#include <stdlib.h>
#include "string.c" // include Frama-C's implementation of string.h

int main() {
  char *buf = malloc(256); // allocate a large buffer
  if (!buf) exit(1);
  char *msg = "silicon";
  strcpy(buf, msg);
  size_t n = strlen(buf);
  char *str = malloc(n + 1); // allocate a buffer with the exact size (plus '\0')
  if (!str) exit(1);
  strncpy(str, buf, n);
  str[n] = 0;
  size_t n2 = strlen(str);
  //@ assert n == n2;
  return 0;

This program uses dynamic allocation and calls functions from string.h.

The following command-line is enough to obtain an interesting result:

frama-c file.c -val -val-builtins-auto -slevel 7

Without -val-builtins-auto one would need to use this overly long argument:

-val-builtin malloc:Frama_C_alloc_by_stack,free:Frama_C_free,strlen:Frama_C_strlen

For more details about Frama_C_alloc_by_stack, check the EVA manual, section 8.1.

The builtins for free and strlen were automatically chosen by EVA. Note however that strcpy and strncpy do not have builtins. In this case, we include "string.c" (which is actually in share/libc/string.c) to use the implementations available with Frama-C.

Analyzing a program using the implementations in share/libc/string.c is less efficient than using a built-in, but more precise than using only a specification. These implementations are designed to minimize the number of alarms when their inputs are imprecise. Also, because they are not optimized for execution, they are conceptually simpler than the actual libc implementations.

Using these functions. -slevel 7 ensures that their loops are fully unrolled in the example. Can you guess why 7 is the right value here?

Inspecting values in the GUI

Another improvement to usability comes in the form of a popup menu in the GUI. To see it, run the following command using the same file as previously:

frama-c-gui file.c -val -val-builtins-auto -slevel 7

On the Frama-C GUI, click on the str expression in the statement str = (char *)malloc(n + (size_t)1); (corresponding to line 11 in the original source code). Then open the Values tab, and you will see something similar to this:

Show pointed values in the GUI

In the Values tab on the bottom, right-clicking on the cell containing the NULL; &__malloc_main_l11[0] value will show a popup menu "Display values for ...". Clicking on it will add a new column displaying its contents.

Before Silicon, this information was already available, but as the result of a long and painful process. The new popup menu shows one entry per pointed variable in the chosen cell, so if there are several different values, there will be several popup menu entries.

malloc may fail

In the previous example, the values of str are those returned by the malloc builtin: NULL and a newly allocated base (__malloc_main_l11). This models the fact that there may not be enough memory, and malloc may fail. The code should definitely handle this case! But for the hurried evaluator, the use of option -no-val-malloc-returns-null can help focus on the other potential run-time errors (before coming back to the malloc-related ones).

Still ways to go

In this example, there are still some warnings, due to the specification of functions strcpy and strncpy, which use logical constructs not yet evaluated by EVA (but very useful for WP). They are not an issue in this example, since we used the actual implementation of these functions, and therefore do not need their specifications, but future work on EVA will help deal with these details and provide a more streamlined experience.

Wednesday, October 12 2016

A mini ACSL tutorial for Value, part 3: indirect assigns

To conclude our 3-part series on ACSL specifications for Value, we present a feature introduced in Frama-C Aluminium that allows more precise specifications: the indirect label in ACSL assigns clauses. The expressivity gains when writing \froms are especially useful for plugins such as Value.

Indirect assigns

Starting in Frama-C Aluminium (20150601), assigns clauses (e.g. assigns x \from src) accept the keyword indirect (e.g. assigns x \from indirect:src), stating that the dependency from src to x is indirect, that is, it does not include data dependencies between src and x. In other words, src itself will never be directly assigned to x.

Indirect dependencies are, most commonly, control dependencies, in which src affects x by controlling whether some instruction will modify the value of x. Another kind of indirect dependency are address dependencies, related to the computation of addresses for pointer variables.

Let us once again refer to our running example, the specification and mock implementation of safe_get_random_char. As a reminder, here's its specification, without the ensures \subset(*out,...) postcondition, as suggested in the previous post:

#include <stdlib.h>
typedef enum {OK, NULL_PTR, INVALID_LEN} status;

  assigns \result \from out, buf, n;
  assigns *out \from out, buf, buf[0 .. n-1], n;
  behavior null_ptr:
    assumes out == \null || buf == \null;
    assigns \result \from out, buf, n;
    ensures \result == NULL_PTR;
  behavior invalid_len:
    assumes out != \null && buf != \null;
    assumes n == 0;
    assigns \result \from out, buf, n;
    ensures \result == INVALID_LEN;
  behavior ok:
    assumes out != \null && buf != \null;
    assumes n > 0;
    requires \valid(out);
    requires \valid_read(&buf[0 .. n-1]);
    ensures \result == OK;
    ensures \initialized(out);
  complete behaviors;
  disjoint behaviors;
status safe_get_random_char(char *out, char const *buf, unsigned n);

Here's the mock implementation of the original function, in which ensures \subset(*out,...) holds:

#include "__fc_builtin.h"
#include <stdlib.h>
typedef enum { OK, NULL_PTR, INVALID_LEN } status;

status safe_get_random_char(char *out, char const *buf, unsigned n) {
  if (out == NULL || buf == NULL) return NULL_PTR;
  if (n == 0) return INVALID_LEN;
  *out = buf[Frama_C_interval(0,n-1)];
  return OK;

And here's the main function used in our tests:

void main() {
  char *msg = "abc";
  int len_arr = 4;
  status res;
  char c;
  res = safe_get_random_char(&c, msg, len_arr);
  //@ assert res == OK;
  res = safe_get_random_char(&c, NULL, len_arr);
  //@ assert res == NULL_PTR;
  res = safe_get_random_char(NULL, msg, len_arr);
  //@ assert res == NULL_PTR;
  res = safe_get_random_char(&c, msg, 0);
  //@ assert res == INVALID_LEN;

In the mock implementation, we see that out and buf are tested to see if they are equal to NULL, but their value itself (i.e., the address they point to) is never actually assigned to *out; only the characters inside buf may be assigned to it. Therefore, out and buf are both control dependencies (in that, they control whether *out = buf[Frama_C_interval(0,n-1)] is executed), and thus indirect as per our definition.

n is also a control dependency of the assignment to *out, due to the check if (n == 0). n also appears in buf[Frama_C_interval(0,n-1)], leading this time to an address dependency: in lval = *(buf + Frama_C_interval(0,n-1)), lval depends indirectly on every variable used to compute the address that will be dereferenced (buf, n, and every variable used by Frama_C_interval in this case).

If we run Value using our specification, this is the result:

[value] ====== VALUES COMPUTED ======
[value] Values at end of function main:
  msg ∈ {{ "abc" }}
  len_arr ∈ {4}
  res ∈ {2}
  c ∈
   {{ garbled mix of &{c; "abc"}
    (origin: Arithmetic {file.c:33}) }}

Note that c has a garbled mix which includes c itself, plus the string literal "abc". The culprit is this assigns clause:

assigns *out \from out, buf, buf[0 .. n-1], n;

out is c and buf is "abc". n, despite also being a dependency, does not contribute to the garbled mix because it is a scalar. The garbled mix appears because, in some functions, it is the address of the pointer itself that is assigned to the lvalue in the assigns clause. Without a means of distinguishing between direct and indirect dependencies, one (dangerous) workaround is to omit some dependencies from the clauses. This may lead to incorrect results.

Thanks to indirect \from clauses, now we can avoid the garbled mix by specifying that out and buf are only indirect dependencies. Applying the same principle to all assigns clauses, we obtain the final version of our (fixed) specification:

  assigns \result \from indirect:out, indirect:buf, indirect:n;
  assigns *out \from indirect:out, indirect:buf, buf[0 .. n-1], indirect:n;
  behavior null_ptr:
    assumes out == \null || buf == \null;
    assigns \result \from indirect:out, indirect:buf, indirect:n;
    ensures \result == NULL_PTR;
  behavior invalid_len:
    assumes out != \null && buf != \null;
    assumes n == 0;
    assigns \result \from indirect:out, indirect:buf, indirect:n;
    ensures \result == INVALID_LEN;
  behavior ok:
    assumes out != \null && buf != \null;
    assumes n > 0;
    requires \valid(out);
    requires \valid_read(&buf[0 .. n-1]);
    ensures \result == OK;
    ensures \initialized(out);
  complete behaviors;
  disjoint behaviors;
status safe_get_random_char(char *out, char const *buf, unsigned n);

Note that indirect dependencies are implied by direct ones, so they never need to be added twice.

With this specification, Value will return c ∈ [--..--], without garbled mix. The result is still imprecise due to the lack of ensures, but better than before. Especially when trying Value on a new code base (where most functions have no stubs, or only simple ones), the difference between garbled mix and [--..--] (often called top int, that is, the top value of the lattice of integer ranges) is significant.

In the new specification, it is arguably easier to read the dependencies and to reason about them: users can skip the indirect dependencies when reasoning about the propagation of imprecise pointer values.

The new specification is more verbose because indirect is not the default. And this is so in order to avoid changing the semantics of existing specifications, which might become unsound.

The From plugin has a new (experimental) option, --show-indirect-deps, which displays the computed dependencies using the new syntax. It is considered experimental simply because it has not yet been extensively used in industrial applications, but it should work fine. Do not hesitate to tell us if you have issues with it.

Ambiguously direct dependencies

It is not always entirely obvious whether a given dependency can be safely considered as indirect, or if it should be defined as direct. This is often the case when a function has an output argument that is related to the length (or size, cardinality, etc.) of one of its inputs. strnlen(s, n) is an example of a libc function with that property: it returns n itself when s is longer than n characters.

Let us consider the following function, which searches for a character in an array and returns its offset, or the given length if not found:

// returns the index of c in buf[0 .. n-1], or n if not found
/*@ assigns \result \from indirect:c, indirect:buf,
                          indirect:buf[0 .. n-1], indirect:n; */
int indexOf(char c, char const *buf, unsigned n);

Our specification seems fine: the result value is usually the number of loop iterations, and therefore it depends indirectly on the related arguments.

However, the following implementation contradicts it:

int indexOf(char c, char const *buf, unsigned n) {
  unsigned i;
  for (i = 0; i < n; i++) {
    if (buf[i] == c) return i;
  return n;

void main() {
  int i1 = indexOf('a', "abc", 3);
  int i2 = indexOf('z', "abc", 3);

If we run frama-c -calldeps -show-indirect-deps (that is, run the From plugin with callwise dependencies, showing indirect dependencies) in this example, we will obtain this output:

[from] call to indexOf at ambiguous.c:10 (by main):
  \result FROM indirect: c; buf; n; "abc"[bits 0 to 7]
[from] call to indexOf at ambiguous.c:11 (by main):
  \result FROM indirect: c; buf; n; "abc"[bits 0 to 23]; direct: n
[from] entry point:

Note that, in the second call, n is computed as a direct dependency. Indeed, it is directly assigned to the return value in the code. This means that our specification is possibly unsound, since it states that n is at most an indirect dependency of \result.

However, if we modify our implementation of indexOf to return i instead of n, then From will compute n as an indirect dependency, and thus our specification could be considered correct. The conclusion is that, in some situations, both versions can be considered correct, and this not will affect the end result.

One specific case where such discussions may be relevant is the case of the memcmp function of the C standard library (specified in string.h): one common implementation consists in comparing each byte of both arrays, say s1[i] and s2[i], and returning s1[i] - s2[i] if they are different. One could argue that such an implementation would imply that assigns \result \from s1[0 ..], s2[0 ..], with direct dependencies. However, this can create undesirable garbled mix, so a better approach would be to consider them as indirect dependencies. In such situations, the best specification is not a clear-cut decision.

Frama-C libc being updated

The Frama-C stdlib has lots of specifications that still need to be updated to take indirect into account. This is being done over time, which means that unfortunately they do not yet constitute a good example of best practices. This is improving with each release, and soon they should offer good examples for several C standard library functions. Until then, you may refer to this tutorial or ask the Frama-C community for recommendations to your specifications.

Also note that some of these recommendations may not be the most relevant ones when considering other plugins, such as WP. Still, most tips here are sufficiently general that they should help you improve your ACSL for all purposes.

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