AdaCore Blog

101 entries tagged with #Proof

by Claire Dross

Handling Aliasing through Pointers in SPARK

As I explained in a blog post a couple of years ago, pointers are subjected to a strict ownership policy in SPARK. It prevents aliasing and allows for an efficient formal verification model. Of course, it comes at the cost of restrictions which might not be applicable to all usage. In particular, while ownership makes it possible to represent certain recursive data-structures, those involving cycles or sharing are de-facto forbidden. This is a choice, and not every proof tool did the same. For example, the WP plug-in of Frama-C supports pointers with arbitrary aliasing. If some information about the separation of memory cells is necessary to verify a program, then the user shall give the annotation explicitly. I have investigated modeling pointers with aliasing in SPARK as indices in a big memory array. I will present the results of my experiments in this blog post. We will see that, while such a representation is indeed possible modulo some hiding in SPARK, it can quickly become rather heavy in practice.

#SPARK    #Data Structures    #Formal Verification   

by Yannick Moy , Claire Dross

Proving the Correctness of GNAT Light Runtime Library

The GNAT light runtime library is a version of the runtime library targeted at embedded platforms and certification, which has been certified for use at the highest levels of criticality in several industrial domains. It contains around 180 units focused mostly on I/O, numerics, text manipulation, memory operations. We have used SPARK to prove the correctness of 40 of them: that the code is free of runtime errors, and that it satisfies its functional specifications.

#SPARK    #Runtime    #Proof   

by Yannick Moy

SPARKNaCl - Two Years of Optimizing Crypto Code in SPARK (and counting)

SPARKNaCl is a SPARK ver­sion of the Tweet­Na­Cl cryp­to­graph­ic library, developed by formal methods and security expert Rod Chapman. For two years now, Rod has been developing and optimizing this open-source cryptographic library while preserving the automatic type-safety proof across code changes and tool updates. He has recently given a talk about this experience that I highly recommend.

#SPARK    #Cryptography    #Formal Verification   

by Paul Butcher

Fuzz Testing in International Aerospace Guidelines

Through the HICLASS UK research group, AdaCore has been developing security-focused software development tools that are aligned with the objectives stated within the avionics security standards. In addition, they have been developing further guidelines that describe how vulnerability identification and security assurance activities can be described within a Plan for Security Aspects of Certification.

#Fuzzing    #Cyber Security    #Civil Avionics    #DO-356A    #ED-203A   

by Kyriakos Georgiou

Security-Hardening Software Libraries with Ada and SPARK

Part of AdaCore's ongoing efforts under the HICLASS project is to demonstrate how the SPARK technology can play an integral part in the security-hardening of existing software libraries written in other non-security-oriented programming languages such as C. This blog post presents the first white paper under this work-stream, “Security-Hardening Software Libraries with Ada and SPARK”.

#SPARK    #STM32    #Embedded   

by Roderick Chapman

SPARKNaCl with GNAT and SPARK Community 2021: Port, Proof and Performance

This post continues our adventures with SPARKNaCl - our verified SPARK version of the TweetNaCl cryptographic library. This time, we'll be looking at yet more performance improvement via proof-driven "operator narrowing", porting the library to GNAT Community 2021, and the effect that has on proof and performance of the code.

#SPARK     #Cryptography    #Formal Verification    #Code generation    #RISC-V    #Security   

by Claire Dross

Relaxing the Data Initialization Policy of SPARK

SPARK always being under development, new language features make it in every release of the tool, be they previously unsupported Ada features (like access types) or SPARK specific developments. However, new features generally take a while to make it into actual user code. The feature I am going to present here is in my experience an exception, as it was used both internally and by external users before it made it into any actual release. It was designed to enhance the verification of data initialization, whose limitations have been a long standing issue in SPARK.

#Formal Verification    #SPARK   

by Jon Andrew

CuBit: A General-Purpose Operating System in SPARK/Ada

Last year, I started evaluating programming languages for a formally-verified operating system. I've been developing software for a while, but only recently began work in high integrity software development and formal methods. There are several operating system projects, like the SeL4 microkernel and the Muen separation kernel, that make use of formal verification. But I was interested in using a formally-verified language to write a general-purpose OS - an environment for abstracting the underlying hardware while acting as an arbiter for running the normal applications we're used to.

by Pat Rogers

From Ada to Platinum SPARK: A Case Study for Reusable Bounded Stacks

This blog entry describes the transformation of an Ada stack ADT into a completely proven SPARK implementation that relies on static verification instead of run-time enforcement of the abstraction’s semantics. We will prove that there are no reads of unassigned variables, no array indexing errors, no range errors, no numeric overflow errors, no attempts to push onto a full stack, no attempts to pop from an empty stack, that subprogram bodies implement their functional requirements, and so on. As a result, we get a maximally robust implementation of a reusable stack abstraction providing all the facilities required for production use.

#SPARK    #Ada    #Transitioning to SPARK   

by Pat Rogers

Making an RC Car with Ada and SPARK

As a demonstration for the use of Ada and SPARK in very small embedded targets, I created a remote-controlled (RC) car using Lego NXT Mindstorms motors and sensors but without using the Lego computer or Lego software. I used an ARM Cortex System-on-Chip board for the computer, and all the code -- the control program, the device drivers, everything -- is written in Ada. Over time, I’ve upgraded some of the code to be in SPARK. This blog post describes the hardware, the software, the SPARK upgrades, and the repositories that are used and created for this purpose.

#Ada    #SPARK    #Robotics   

by Quentin Ochem

Witnessing the Emergence of a New Ada Era

For nearly four decades the Ada language (in all versions of the standard) has been helping developers meet the most stringent reliability, safety and security requirements in the embedded market. As such, Ada has become an entrenched player in its historic A&D niche, where its technical advantages are recognized and well understood. Ada has also seen usage in other domains (such as medical and transportation) but its penetration has progressed at a somewhat slower pace. In these other markets Ada stands in particular contrast with the C language, which, although suffering from extremely well known and documented flaws, remains a strong and seldom questioned default choice. Or at least, when it’s not the choice, C is still the starting point (a gateway drug?) for alternatives such as C++ or Java, which in the end still lack the software engineering benefits that Ada embodies..

by Joffrey Huguet , Johannes Kanig

Proving a simple program doing I/O ... with SPARK

The functionality of many security-critical programs is directly related to Input/Output (I/O). This includes command-line utilities such as gzip, which might process untrusted data downloaded from the internet, but also any servers that are directly connected to the internet, such as webservers, DNS servers and so on. In this blog post we show an approach that deals with error handling and reasoning about content, and demonstrate the approach using the cat command line utility.

#Formal Verification    #SPARK   

by Joffrey Huguet

Using SPARK to prove 255-bit Integer Arithmetic from Curve25519

In 2014, Adam Langley, a well-known cryptographer from Google, wrote a post on his personal blog, in which he tried to prove functions from curve25519-donna, one of his projects, using various verification tools: SPARK, Frama-C, Isabelle... He describes this attempt as "disappointing", because he could not manage to prove "simple" things, like absence of runtime errors. I will show in this blogpost that today, it is possible to prove what he wanted to prove, and even more.

#SPARK    #Formal Verification    #Cryptography   

by Quentin Ochem

Proving Memory Operations - A SPARK Journey

The promise behind the SPARK language is the ability to formally demonstrate properties in your code regardless of the input values that are supplied - as long as those values satisfy specified constraints. As such, this is quite different from static analysis tools such as our CodePeer or the typical offering available for e.g. the C language, which trade completeness for efficiency in the name of pragmatism. Indeed, the problem they’re trying to solve - finding bugs in existing applications - makes it impossible to be complete. Or, if completeness is achieved, then it is at the cost of massive amount of uncertainties (“false alarms”). SPARK takes a different approach. It requires the programmer to stay within the boundaries of a (relatively large) Ada language subset and to annotate the source code with additional information - at the benefit of being able to be complete (or sound) in the verification of certain properties, and without inundating the programmer with false alarms.

by Yannick Moy

​Amazon Relies on Formal Methods for the Security of AWS

Byron Cook, who founded and leads the Automated Reasoning Group at Amazon Web Services (AWS) Security, gave a powerful talk at the Federated Logic Conference in July about how Amazon uses formal methods for ensuring the security of parts of AWS infrastructure. In the past four years, this group of 20+ has progressively hired well-known formal methods experts to face the growing demand inside AWS to develop tools based on formal verification for reasoning about cloud security. What is unique so far is the level of investment at AWS in formal verification as a means to radically eliminate some security problems, both for them and for their customers. This is certainly an approach we're eager to support with our own investment in the SPARK technology​.

#Formal Verification    #Cloud    #Security   

by Yannick Moy

Two Days Dedicated to Sound Static Analysis for Security

​AdaCore has been working with CEA, Inria and NIST to organize a two-days event dedicated to sound static analysis techniques and tools, and how they are used to increase the security of software-based systems. The program gathers top-notch experts in the field, from industry, government agencies and research institutes, around the three themes of analysis of legacy code, use in new developments and accountable software quality. Here is why it is worth attending.

#SPARK    #Frama-C    #Security    #Formal Methods    #Static Analysis   

by Yannick Moy

Tokeneer Fully Verified with SPARK 2014

Tokeneer is a software for controlling physical access to a secure enclave by means of a fingerprint sensor. This software was created by Altran (Praxis at the time) in 2003 using the previous generation of SPARK language and tools, as part of a project commissioned by the NSA to investigate the rigorous development of critical software using formal methods. The project artefacts, including the source code, were released as open source in 2008. Tokeneer was widely recognized as a milestone in industrial formal verification. We recently transitioned this software to SPARK 2014, and it allowed us to go beyond what was possible with the previous SPARK technology. We have also shown how security vulnerabilities introduced in the code can be detected by formal verification.

#SPARK    #Formal Methods   

by Yannick Moy

For All Properties, There Exists a Proof

With the recent addition of a Manual Proof capability in SPARK 18, it is worth looking at an example which cannot be proved by automatic provers, to see the options that are available for proving it with SPARK. We present three ways to complete a proof beyond what automatic provers can do: using an alternative automatic prover, proving interactively inside our GPS IDE, and using an alternative interactive prover.

#SPARK    #Formal Methods   

by Lionel Matias

Leveraging Ada Run-Time Checks with Fuzz Testing in AFL

Fuzzing is a very popular bug finding method. The concept, very simple, is to continuously inject random (garbage) data as input of a software component, and wait for it to crash. If, like me, you find writing robustness test tedious and not very efficient in finding bugs, you might want to try fuzzing your Ada code.Here's a recipe to fuzz-test your Ada code, using American Fuzzy Lop and all the runtime checks your favorite Ada compiler can provide.Let's see (quickly) how AFL works, then jump right into fuzzing 3 open-source Ada libraries: ZipAda, AdaYaml, and GNATCOLL.JSON.

#Testing    #Ada    #VerificationTools   

by Yannick Moy

Proving Loops Without Loop Invariants

For all the power that comes with proof technology, one sometimes has to pay the price of writing a loop invariant. Along the years, we've strived to facilitate writing loop invariants by improving the documentation and the technology in different ways, but writing loops invariants remains difficult sometimes, in particular for beginners. To completely remove the need for loop invariants in simple cases, we have implemented loop unrolling in GNATprove. It turns out it is quite powerful when applicable.

#Formal Verification    #SPARK   

by Yannick Moy

Research Corner - Focused Certification of SPARK in Coq

The SPARK toolset aims at giving guarantees to its users about the properties of the software analyzed, be it absence of runtime errors or more complex properties. But the SPARK toolset being itself a complex tool, it is not free of errors. To get confidence in its results, we have worked with academic partners to establish mathematical evidence of the correctness of a critical part of the SPARK toolset. The part on which we focused is the tagging of nodes requiring run-time checks by the frontend of the SPARK technology. This work has been accepted at SEFM 2017 conference.

#SPARK   

by Yannick Moy

Applied Formal Logic: Searching in Strings

A friend pointed me to recent posts by Tommy M. McGuire, in which he describes how Frama-C can be used to functionally prove a brute force version of string search, and to find a previously unknown bug in a faster version of string search called quick search. Frama-C and SPARK share similar history, techniques and goals. So it was tempting to redo the same proofs on equivalent code in SPARK, and completing them with a functional proof of the fixed version of quick search. This is what I'll present in this post.

#Dev Projects    #Formal Verification    #SPARK   

by Yannick Moy

Research Corner - FLOSS Glider Software in SPARK

Two years ago, we redeveloped the code of a small quadcopter called Crazyflie in SPARK, as a proof-of-concept to show it was possible to prove absence of run-time errors (no buffer overflows, not division by zero, etc.) on such code. The researchers Martin Becker and Emanuel Regnath have raised the bar by developing the code for the autopilot of a small glider in SPARK in three months only. Their paper and slides are available, and they have released their code as FLOSS for others to use/modify/enhance!

#Formal Verification    #Dev Projects    #SPARK   

by Yannick Moy

Research Corner - Floating-Point Computations in SPARK

It is notoriously hard to prove properties of floating-point computations, including the simpler bounding properties that state safe bounds on the values taken by entities in the program. Thanks to the recent changes in SPARK 17, users can now benefit from much better provability for these programs, by combining the capabilities of different provers. For the harder cases, this requires using ghost code to state intermediate assertions proved by one of the provers, to be used by others. This work is described in an article which was accepted at VSTTE 2017 conference.

#Formal Verification    #SPARK   

by Yannick Moy

New Guidance for Adoption of SPARK

While SPARK has been used for years in companies like Altran UK, companies without the same know-how may find it intimidating to get started on formal program verification. To help with that process, AdaCore has collaborated with Thales throughout the year 2016 to produce a 70-pages detailed guidance document for the adoption of SPARK. These guidelines are based on five levels of assurance that can be achieved on software, in increasing order of costs and benefits: Stone level (valid SPARK), Bronze level (initialization and correct data flow), Silver level (absence of run-time errors), Gold level (proof of key properties) and Platinum level (full functional correctness). These levels, and their mapping to the Development Assurance Levels (DAL) and Safety Integrity Levels (SIL) used in certification standards, were presented at the recent High Confidence Software and Systems conference.

#Formal Verification    #SPARK   

by Yannick Moy

VerifyThis Challenge in SPARK

This year again, the VerifyThis competition took place as part of ETAPS conferences. This is the occasion for builders and users of formal program verification platforms to use their favorite tools on common challenges. The first challenge this year was a good fit for SPARK, as it revolves around proving properties of an imperative sorting procedure. In this post, I am using this challenge to show how one can reach different levels of software assurance with SPARK.

#Formal Verification    #SPARK   

by Yannick Moy

GNATprove Tips and Tricks: Proving the Ghost Common Divisor (GCD)

Euclid's algorithm for computing the greatest common divisor of two numbers is one of the first ones we learn in school, and also one of the first algorithms that humans devised. So it's quite appealing to try to prove it with an automatic proving toolset like SPARK. It turns out that proving it automatically is not so easy, just like understanding why it works is not so easy. In this post, I am using ghost code to prove correct implementations of the GCD, starting from a naive linear search algorithm and ending with Euclid's algorithm.

#Formal Verification    #SPARK   

by Claire Dross

Research Corner - Auto-active Verification in SPARK

GNATprove performs auto-active verification, that is, verification is done automatically, but usually requires annotations by the user to succeed. In SPARK, annotations are most often given in the form of contracts (pre and postconditions). But some language features, in particular ghost code, allow proof guidance to be much more involved. In a paper we are presenting at NASA Formal Methods symposium 2017, we describe how an imperative red black tree implementation in SPARK was verified using intensive auto-active verification.

#Formal Verification    #SPARK   

by Yannick Moy

New Year's Resolution for 2017: Use SPARK, Say Goodbye to Bugs

​NIST has recently published a report called "Dramatically Reducing Software Vulnerabilities"​ in which they single out five approaches which have the potential for creating software with 100 times fewer vulnerabilities than we do today. One of these approaches is formal methods. Among formal methods, the report highlights strong suits of SPARK, and cites SPARK projects as example of mature uses of formal methods. NIST is not the only ones to support the use of SPARK. Editor Bill Wong from Electronic Design has included SPARK in his "2016 Gifts for the Techie". So if your new year's resolutions include software without bugs, have a look at SPARK in 2017.

#VerificationTools    #Formal Methods    #SPARK   

by Claire Dross

Automatic Generation of Frame Conditions for Array Components

One of the most important challenges for SPARK users is to come up with adequate contracts and annotations, allowing GNATprove to verify the expected properties in a modular way. Among the annotations mandated by the SPARK toolset, the hardest to come up with are probably loop invariants. A previous post explains how GNATprove can automatically infer loop invariants for preservation of unmodified record components, and so, even if the record is itself nested inside a record or an array. Recently, this generation was improved to also support the simplest cases of partial array updates. We describe in this post in which cases GNATprove can, or cannot, infer loop invariants for preservation of unmodified array components.

#Formal Verification    #SPARK   

by Yannick Moy

GNATprove Tips and Tricks: What’s Provable for Real Now?

One year ago, we presented on this blog what was provable about fixed-point and floating-point computations (the two forms of real types in SPARK). Since then, we have integrated static analysis in SPARK, and modified completely the way floating-point numbers are seen by SMT provers. Both of these features lead to dramatic changes in provability for code doing fixed-point and floating-point computations.

#Formal Verification    #SPARK   

by Yannick Moy

Verified, Trustworthy Code with SPARK and Frama-C

Last week, a few of us at AdaCore have attended a one-day workshop organized at Thales Research and Technologies, around the topic of "Verified, trustworthy code - formal verification of software". Attendees from many different branches of Thales (avionics, railway, security, networks) were given an overview of the state-of-practice in formal verification of software, focused on two technologies: the SPARK technology that we develop at AdaCore for programs in Ada, and the Frama-C technology developed at CEA research labs for programs in C. The most interesting part of the day was the feedback given by three operational teams who have experimented during a few months with either SPARK (two teams) or Frama-C (one team). The lessons learned by first-time adopters of such technologies are quite valuable.

#SPARK    #Formal Methods   

by Yannick Moy

GNATprove Tips and Tricks: Using the Lemma Library

A well-know result of computing theory is that the theory of arithmetic is undecidable. This has practical consequences in automatic proof of programs which manipulate numbers. The provers that we use in SPARK have a good support for addition and subtraction, but much weaker support for multiplication and division. This means that as soon as the program has multiplications and divisions, it is likely that some checks won't be proved automatically. Until recently, the only way forward was either to complete the proof using an interactive prover (like Coq or Isabelle/HOL) or to justify manually the message about an unproved check. There is now a better way to prove automatically such checks, using the recent SPARK lemma library.

#Formal Verification    #SPARK   

by Florian Schanda

SPARKSMT - An SMTLIB Processing Tool Written in SPARK - Part I

Today I will write the first article in a short series about the development of an SMTLIB processing tool in SPARK. Instead of focusing on features, I intend to focus on the how I have proved absence of run-time errors in the name table and lexer. I had two objectives: show absence of run-time errors, and do not write useless defensive code. Today's blog will be about the name table, a data structure found in many compilers that can map strings to a unique integer and back. The next blog post will talk about the lexical analyzer.

#Dev Projects    #Formal Verification    #SPARK   

by Yannick Moy

Did SPARK 2014 Rethink Formal Methods?

David Parnas is a well-known researcher in formal methods, who famously contributed to the analysis of the shut-down software for the Darlington nuclear power plant and designed the specification method known as Parnas tables and the development method called Software Cost Reduction. In 2010, the magazine CACM asked him to identify what was preventing more widespread adoption of formal methods in industry, and in this article on Really Rethinking Formal Methods he listed 17 areas that needed rethinking. The same year, we started a project to recreate SPARK with new ideas and new technology, which lead to SPARK 2014 as it is today. Parnas's article influenced some critical design decisions. Six years later, it's interesting to see how the choices we made in SPARK 2014 address (or not) Parnas's concerns.

#Formal Verification    #SPARK   

by Yannick Moy

Formal Verification of Legacy Code

Just a few weeks ago, one of our partners reported a strange behavior of the well-known function Ada.Text_IO.Get_Line, which reads a line of text from an input file. When the last line of the file was of a specific length like 499 or 500 or 1000, and not terminated with a newline character, then Get_Line raised an exception End_Error instead of returning the expected string. That was puzzling for a central piece of code known to have worked for the past 10 years! But fair enough, there was indeed a bug in the interaction between subprograms in this code, in boundary cases having to do with the size of an intermediate buffer. My colleague Ed Schonberg who fixed the code of Get_Line had nonetheless the intuition that this particular event, finding such a bug in an otherwise trusted legacy piece of code, deserved a more in depth investigation to ensure no other bugs were hiding. So he challenged the SPARK team at AdaCore in checking the correctness of the patched version. He did well, as in the process we uncovered 3 more bugs.

#SPARK    #Legacy    #Formal Methods   

by David Hauzar

SPARK 16: Generating Counterexamples for Failed Proofs

While the analysis of failed proofs is one of the most challenging aspects of formal verification, it would be much easier if a tool would automatically find values of variables showing why a proof fails. SPARK Pro 16, to be released in 2016, is going to introduce such a feature. If a proof fails, it attempts to generate a counterexample exhibiting the problem. This post introduces this new feature, developed in the scope of the ProofInUse laboratory.

#Formal Verification    #SPARK   

by Yannick Moy

GNATprove Tips and Tricks: User Profiles

One of the most difficult tasks when using proof techniques is to interact with provers, in particular to progressively increase proof power until everything that should be proved is proved. Until the last release, increasing the proof power meant operating on three separate switches. There is now a simpler solution based on a new switch --level, together with a simpler proof panel in GPS for new users.

#Formal Verification    #SPARK   

by Yannick Moy

SPARKSkein: From tour-de-force to run-of-the-mill Formal Verification

In 2010, Rod Chapman released an implementation in SPARK of the Skein cryptographic hash algorithm, and he proved that this implementation was free of run-time errors. That was a substantial effort with the previous version of the SPARK technology. We have recently translated the code of SPARKSkein from SPARK 2005 to SPARK 2014, and used GNATprove to prove absence of run-time errors in the translated program. The difference between the two technologies is striking. The heroic effort that Rod put in the formal verification of the initial version of SPARKSkein could now be duplicated with modest effort and modest knowledge of the technology, thanks to the much greater proof automation that the SPARK 2014 technology provides, as well as various features that lower the need to provide supporting specifications, most notably contracts on internal subprograms and loop invariants.

#Dev Projects    #Formal Verification    #SPARK   

by Anthony Leonardo Gracio

How to prevent drone crashes using SPARK

The Crazyflie is a very small quadcopter sold as an open source development platform: both electronic schematics and source code are directly available on their GitHub and its architecture is very flexible. Even if the Crazyflie flies out of the box, it has not been developed with safety in mind: in case of crash, its size, its weight and its plastic propellers won’t hurt anyone! But what if the propellers were made of carbon fiber, and shaped like razor blades to increase the drone’s performance? In theses circumstances, a bug in the flight control system could lead to dramatic events. In this post, I present the work I did to rewrite the stabilization system of the Crazyflie in SPARK 2014, and to prove that it is free of runtime errors. SPARK also helped me to discover little bugs in the original firmware, one of which directly related with overflows. Besides the Crazyflie, this work could be an inspiration for others to do the same work on larger and more safety-critical drones.

#UAVs    #crazyflie    #SPARK    #Drones   

by Clément Fumex

GNATprove Tips and Tricks: Bitwise Operations

The ProofInUse joint laboratory is currently improving the way SPARK deals with modular types and bitwise operators. Until now the SPARK tool was trying its best to translate those into equivalent operations on integers. It is now using native theory of smt-solvers when available resulting in much better support, and guaranteeing state of the art handling of bitwise operations. We present some examples in this post.

#Formal Verification    #SPARK   

by Olivier Ramonat

AdaCore Releases GNAT Pro 7.3, QGen 1.0 and GNATdashboard 1.0

February saw the annual customer release of a number of important products. This is no mean task when you consider the fact that GNAT Pro is available on over 50 platforms and supports over 150 runtime profiles (ranging from Full Ada Support to the very restricted Zero Footprint Profile suitable for safety-critical development). All in all, from the branching of the preview version to the customer release it takes us nearly 4 months to package everything up! Quality is assured through the internally developed AdaCore Factory.

#GNAT Pro    #SPARK Pro    #GPS    #GNATbench    #GNATdashboard    #Ada    #AdaCore Factory    #CodePeer    #QGen   

by Yannick Moy

SPARK 2014 Rationale: Object Oriented Programming

Object Oriented Programming is known for making it particularly difficult to analyze programs, because the subprograms called are not always known statically. The standard for civil avionics certification has recognized this specific problem, and defines a specific verification objective called Local Type Consistency that should be met with one of three strategies. SPARK allows using one of these strategies, by defining the behavior of an overridden subprogram using a special class-wide contract and checking that the behavior of the overriding subprogram is a suitable substitution, following the Liskov Substitution Principle.

#Language    #Formal Verification    #SPARK   

by Yannick Moy

SPARK 2014 Rationale: Ghost Code

A common situation when proving properties about a program is that you end up writing additional code whose only purpose is to help proving the original program. If you're careful or lucky enough, the additional code you write will not impact the program being verified, and it will be removed during compilation, so that it does not inflate binary size or waste execution cycles. SPARK provides a way to get these benefits automatically, by marking the corresponding code as ghost code, using the new Ghost aspect.

#Formal Verification    #SPARK   

by Yannick Moy

Using Coq to Verify SPARK 2014 Code

In the first release of SPARK 2014, GNATprove only provided support for automatic provers, in particular Alt-Ergo. Automatic provers are very handy when it comes to perform a big numberof simple proof. But they can fail to prove valid formulas when the proof involves some advanced reasoning. As mentioned in a previous post, one check left unproved might invalidate assumptions on which are based the proofs of multiple other checks. This is a case where manual proof may be useful for SPARK 2014 users. The development version of GNATprove now supports Coq to perform manual proof.

#Formal Verification    #SPARK   

by Yannick Moy

Using SPARK to Prove AoRTE in Robot Navigation Software

Correctness of robot software is a challenge. Just proving the absence of run-time errors (AoRTE) in robot software is a challenge big enough that even NASA has not solved it. Researchers have used SPARK to do precisely that for 3 well-known robot navigation algorithms. Their results will be presented at the major robotics conference IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014) this coming September.

#Formal Verification    #SPARK    #Robotics   

by Claire Dross

External Axiomatizations: a Trip Into SPARK’s Internals

There are cases expressing all the specification of a package in SPARK is either impossible (for example if you need to link them to elements of the mathematical world, like trigonometry functions), cumbersome (especially if they require concepts that cannot easily be described using contracts, like transitivity, counting, summation...), or simply inefficient, for big and complex data structures like containers for example. In these cases, a user can provide directly a manually written Why3 translation for an Ada package using a feature named external axiomatizations. Coming up with this manual translation requires both a knowledge of the WhyML language and a minimal understanding of GNATprove's mechanisms and is therefore reserved to advanced users.

#Formal Verification    #SPARK   

by Claire Dross

Manual Proof with Ghost Code in SPARK 2014

Guiding automatic solvers by adding intermediate assertions is a commonly used technique. We can go further in this direction, by adding complete pieces of code doing nothing, generally called ghost code, to guide the automated reasoning. This is an advanced feature, for people willing to manually guide proofs. Still, it is all in SPARK 2014 and thus does not require the user to learn a new language. We explain here how we can achieve inductive proofs on a permutation function.

#Formal Verification    #SPARK   

by Florian Schanda

SPARK 2014 Rationale: Data Dependencies

Programs often use a few global variables. Global variables make passing common information between different parts of a program easier. By reading the specification of a subprogram we are able to see all of the parameters that the subprogram uses and, in Ada, we also get to know whether they are read, written or both. However, no information regarding the use of global variables is revealed by reading the specifications. In order to monitor and enforce which global variables a subprogram is allowed to use, SPARK 2014 has introduced the Global aspect, which I describe in this post.

#Language    #Formal Verification    #SPARK   

by Yannick Moy

Muen Separation Kernel Written in SPARK

The University of Applied Sciences Rapperswil in Switzerland has released last week an open-source separation kernel written in SPARK, which has been proved free from run-time errors. This project is part of the secure multilevel workstation project by Secunet, a German security company, which is using SPARK and Isabelle to create the next generation of secure workstations providing different levels of security to government employees and military personnel. I present why I think this project is worth following closely.

#Language    #Formal Verification    #SPARK   

by Yannick Moy

SPARK 2014 Rationale: Loop Invariants

Formal verification tools like GNATprove rely on two main inputs from programmers: subprogram contracts (preconditions and postconditions) and loop invariants. While the first ones are easy to understand (based on the "contract" analogy, in which a subprogram and its caller have mutual obligations), the second ones are not so simple to grasp. This post presents loop invariants and the choices we made in SPARK 2014.

#Language    #Formal Verification    #SPARK