23 entries tagged with #Fixed Point
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.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.
by Pierre-Marie de Rodat
A Further Expedition into Libadalang: Save Time with Libadalang.Helpers.App
Martyn’s recent blog post showed small programs based on Libadalang to find uses of access types in Ada sources. Albeit short, these programs need to take care of all the tedious logistics around processing Ada sources: find the files to work on, create a Libadalang analysis context, use it to read the source files, etc. Besides, they are not very convenient to run:
by Martyn Pike
An Expedition into Libadalang
I’ve been telling Ada developers for a while now that Libadalang will open up the possibility of more-easily writing Ada source code analysis tools. (You can read more about Libadalang here and here and can also access the project on Github.)
by Alexander Senier
RecordFlux: From Message Specifications to SPARK Code
Handling binary data is hard. Errors in parsers routinely lead to critical security vulnerabilities. In this post we show how the RecordFlux toolset eases the creation of formally verified binary parsers in SPARK.by Allan Ascanius , Per Dalgas Jakobsen
Winning DTU RoboCup with Ada and SPARK
The Danish Technical University has a yearly RoboCup where autonomous vehicles solve a number of challenges. We participated with RoadRunner, a 3D printed robot with wheel suspension, based on the BeagleBone Blue ARM-based board and the Pixy 1 camera with custom firmware enabling real-time line detection. Code is written in Ada and formally proved correct with SPARK at Silver level.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.
by Arnaud Charlet
How Do We Use CodePeer at AdaCore
A question that our users sometimes ask us is "do you use CodePeer at AdaCore and if so, how?". The answer is yes! and this blog post will hopefully give you some insights into how we are doing it for our own needs.
by Rob Tice
AdaFractal Part 2: Fixed Point and Floating Point Math Performance and Parallelization
In Part 1 of this blog post I discussed why I chose to implement this application using the Ada Web Server to serve the computed fractal to a web browser. In this part I will discuss a bit more about the backend of the application, the Ada part.
by Rob Tice
AdaFractal Part1: Ada with a Portable GUI
The is the first part of a multiple part post that covers the development of the AdaFractal project. The idea was to create fractals in Ada. Here we will cover how to use AWS to create a flexible and portable way to display the generated fractals without using bulky graphics libraries.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.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.by Yannick Moy
(Many) More Low Hanging Bugs
We reported in a previous post our initial experiments to create lightweight checkers for Ada source code, based on the new Libadalang technology. The two checkers we described discovered 12 issues in the codebase of the tools we develop at AdaCore. In this post, we are reporting on 6 more lightweight checkers, which have discovered 114 new issues in our codebase. This is definitely showing that these kind of checkers are worth integrating in static analysis tools, and we look forward to integrating these and more in our static analyzer CodePeer for Ada programs.by Yannick Moy , Nicolas Roche
A Usable Copy-Paste Detector in A Few Lines of Python
After we created lightweight checkers based on the recent Libadalang technology developed at AdaCore, a colleague gave us the challenge of creating a copy-paste detector based on Libadalang. It turned out to be both easier than anticipated, and much more efficient and effective than we could have hoped for. In the end, we hope to use this new detector to refactor the codebase of some of our tools, and we expect to integrate it in our IDEs.by Jorge Real

Writing on Air
While searching for motivating projects for students of the Real-Time Systems course here at Universitat Politècnica de València, we found a curious device that produces a fascinating effect. It holds a 12 cm bar from its bottom and makes it swing, like an upside-down pendulum, at a frequency of nearly 9 Hz. The free end of the bar holds a row of eight LEDs. With careful and timely switching of those LEDs, and due to visual persistence, it creates the illusion of text... floating in the air!
by Fabien Chouteau , Arnaud Charlet , Yannick Moy
SPARK Tetris on the Arduboy
One of us got hooked on the promise of a credit-card-size programmable pocket game under the name of Arduboy and participated in its kickstarter in 2015. The kickstarter was successful (but late) and delivered the expected working board in mid 2016. Of course, the idea from the start was to program it in Ada , but this is an 8-bits AVR microcontroller (the ATmega32u4 by Atmel) not supported anymore by GNAT Pro. One solution would have been to rebuild our own GNAT compiler for 8-bit AVR from the GNAT FSF repository and use the AVR-Ada project. Another solution, which we explore in this blog post, is to use the SPARK-to-C compiler that we developed at AdaCore to turn our Ada code into C and then use the Arduino toolchain to compile for the Arduboy board.
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.by Yannick Moy
The Most Obscure Arithmetic Run-Time Error Contest
Something that many developers do not realize is the number of run-time checks that occur in innocent looking arithmetic expressions. Of course, everyone knows about overflow checks and range checks (although many people confuse them) and division by zero. After all, these are typical errors that do show up in programs, so programmers are aware that they should keep an eye on these. Or do they?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.
by Yannick Moy
GNATprove Tips and Tricks: What’s Provable for Real?
SPARK supports two ways of encoding reals in a program: the usual floating-point reals, following the standard IEEE 754, and the lesser known fixed-point reals, called this way because their precision is fixed (contrary to floating-points whose precision varies with the magnitude of the encoded number). This support is limited in some ways when it comes to proving properties of computations on real numbers, and these limitations depend strongly in the encoding chosen. In this post, I show the results of applying GNATprove on simple programs using either floating-point or fixed-point reals, to explain these differences.by Emmanuel Briot
Traits-Based Containers
This post describes the design of a new containers library. It highlights some of the limitations of the standard Ada containers, and proposes a new approach using generic packages as formal parameters to make these new containers highly configurable at compile time.by Tristan Gingold , Yannick Moy

Tetris in SPARK on ARM Cortex M4
Tetris is a well-known game from the 80's, which has been ported in many versions to all game platforms since then. There are even versions of Tetris written in Ada. But there was no version of Tetris written in SPARK, so we've repaired that injustice. Also, there was no version of Tetris for the Atmel SAM4S ARM processor, another injustice we've repaired.