AdaCore Blog

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by Claire Dross –

A quick glimpse at the translation of Ada integer types in GNATprove

In SPARK, as in most programming languages, there are a bunch of bounded integer types. On the other hand, Why3 only has mathematical integers and a library for bitvectors. Since bitwise operations can only be done on modular types in Ada, we currently translate arithmetic operations on signed integer types as operations on mathematical integers and arithmetic operations on modular types as operation on bitvectors. The only remaining question now is, how do we encode specific bounds of the Ada types into our Why3 translation ? In this post, I will present three different ways we tried to do this and explain which one we currently use and why.

#Formal Verification    #SPARK   

by Martyn Pike –

The latest Mixed Programming with Ada lectures at the AdaCore University

I recently joined AdaCore as a Technical Account Manager with an initial focus on the UK and Scandinavian regions, but for the last 12 months I've been busy working on the AdaCore University. The most recent addition to which is a course on Mixed Language Programming with Ada, and it includes lectures on the integration of Ada with C, C++ and Java. The course covers some advanced topics like mixed language object orientation, techniques for using Ada strong typing to combat known issue with C pointers and the pitfalls that are encountered when mixing native Ada code with Java at runtime. This course clearly demonstrates that Ada has strong support for integration with C, C++ and Java and it proves there are no technical barriers to its adoption in modern mixed language software systems.

#Mixed Language    #AdaCore University    #Java    #C++    #C    

by Clément Fumex – Guest Author

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 Yannick Moy –

GNATprove Tips and Tricks: Catching Mistakes in Contracts

Contracts may be quite complex, as complex as code in fact, so it is not surprising that they contain errors sometimes. GNATprove can help by pinpointing suspicious constructs that, although legal, do not make much sense. These constructs are likely to be caused by mistakes made by the programmer when writing the contract. In this post, I show examples of incorrect constructs that are signaled by GNATprove.

#Formal Verification    #Compilation    #SPARK   

by Tristan Gingold –

AdaCore at FOSDEM'15

I was at Bruxelles on January 31st to present the components of GNAT GPL 2015 : SPARK 2014 and GNAT GPL for ARM bare-board. This is not unrelated to a previous blog entry on Tetris in SPARK on ARM Cortex M4, in particular I presented that Tetris demo (I brought some boards with me and despite the simple package, none were broken!). The slides contain technical details on the ravenscar profile (main principles), how to build a program for the stm32f4-discovery board and how to port the runtime. There are also less technical slides such as why we choose the stm32f4 board and photos of some graphical demos. As that could be useful to anyone interested in Ravenscar or in porting the runtime to other boards or other platforms, we've made the slides available here.

#ARM    #Ravenscar    #FOSDEM    #GNATGPL   

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 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 – Guest Author

SPARK 2014 Rationale: Information Flow

In a previous blog post we described how aspect Global can be used to designate the specific global variables that a subprogram has to read and write. So, by reading the specification of a subprogram that has been annotated with aspect Global we can see exactly which variables, both local and global, are read and/or written each time the subprogram is called. Based purely on the Global aspect, this pretty much summarizes the full extent of our knowledge about the flow of information in a subprogram. To be more precise, at this point, we know NOTHING about the interplay between the inputs and outputs of the subprogram. For all we know, all outputs could be randomly generated and the inputs might not contribute in the calculation of any of the outputs. To improve this situation, SPARK 2014 uses aspect Depends to capture the dependencies between a subprogram's outputs and inputs. This blog post demonstrates through some examples how aspect Depends can be used to facilitate correct flow of information through a subprogram.

#Formal Verification    #SPARK   

by Florian Schanda – Guest Author

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 –

GNATprove Tips and Tricks: How to Write Loop Invariants

Having already presented in previous posts why loop invariants are necessary for formal verification of programs with loops, and what loop invariants are necessary for various loops, we detail here a methodology for how users can come up with the right loop invariants for their loops. This methodology in four steps allows users to progressively add the necessary information in their loop invariants, with the tool GNATprove providing the required feedback at each step on whether the information provided is sufficient or not.

#Formal Verification    #SPARK