Safe Pointers in SPARK 2014

dynamic - SPARK: dynamic / static Run-time errors: - Ada: dynamic - SPARK: dynamic / static Data flow errors: - Ada: - - SPARK: static Strong typing: - Ada: static - SPARK: static Safer language subset: - Ada: - - SPARK: static Strict clear syntax: - Ada: static - SPARK: static --- Additionally, safe pointers in SPARK: https://blog.adacore.com/using-pointers-in-spark and https://arxiv.org/abs/1710.07047. --- Cryptographic library in SPARK 2014: https://github.com/Componolit/libsparkcrypto. > libsparkcrypto is a formally verified implementation of several widely used cryptographic algorithms using the SPARK 2014 programming language and toolset. For the complete library proofs of the absence of run-time errors like type range violations, division by zero and numerical overflows are available. Some of its subprograms include proofs of partial correctness. --- Ada/SPARK is excellent for real-time and safety-critical software: https://www.rcs.ei.tum.de/fileadmin/tueircs/www/becker/spark... to give you some ideas. It may be a bit outdated in some regards, though, for example: "Next version of SPARK 2014 under development (pointers!).". It is already done! :)

this work is hard even when doing simple things if you want end result to be widely usable. So, you better have a good justification for trying to redo decades worth of hard work on your own with some VC funding. Anyone wanting a shortcut should build your language on top of capabilities of the SPARK Ada language [1] with this book [2]. Your smart contracts get all the benefits it currently offers plus whatever extra you build plus whatever they build with the influx of money for Pro edition. Recent projects already add some pointer [3] and floating-point [4] safety to what they already mostly automate with that tooling. This is also a mature tool whose development and commercial use goes back decades [5]. [1] https://en.wikipedia.org/wiki/SPARK_(programming_language) [2] https://www.amazon.com/Building-High-Integrity-Applications-... [3] https://arxiv.org/abs/1710.07047 [4] http://lists.forge.open-do.org/pipermail/spark2014-discuss/2... [5] http://www.spark-2014.org/uploads/itp_2014_r610.pdf

runtime. Specifically, GNATprove logically interprets the meaning of every instruction in the program. Using this interpretation, GNATprove generates a logical formula called a verification condition for each check that would otherwise be required by the Ada (and hence SPARK) language. Additionally, in Ada/SPARK, you can formally verify tasks (concurrency), too: https://docs.adacore.com/spark2014-docs/html/ug/en/source/co.... Moreover: > SPARK builds on the strengths of Ada to provide even more guarantees statically rather than dynamically. As summarized in the following table, Ada provides strict syntax and strong typing at compile time plus dynamic checking of run-time errors and program contracts. SPARK allows such checking to be performed statically. In addition, it enforces the use of a safer language subset and detects data flow errors statically. Contract programming: - Ada: dynamic - SPARK: dynamic / static Run-time errors: - Ada: dynamic - SPARK: dynamic / static Data flow errors: - Ada: - - SPARK: static Strong typing: - Ada: static - SPARK: static Safer language subset: - Ada: - - SPARK: static Strict clear syntax: - Ada: static - SPARK: static Additionally, safe pointers in SPARK: https://blog.adacore.com/using-pointers-in-spark and https://arxiv.org/abs/1710.07047. More information about Get_Line (i.e. even where you would think you cannot go static): https://blog.adacore.com/formal-verification-of-legacy-code. [1] overflow check, index check, range check, divide by zero