# Tag Info

20

What you want exists, and is an enormous area of research: it's the entire theory of programming languages. Loosely speaking, you can view computation in two ways. You can think of machines, or you can think of languages. A machine is basically some kind of finite control augmented with some (possibly unbounded) memory. This is why introductory TOC ...

19

The purpose of the proof checker is to minimise the trusted computing base. By having a proof checker, neither the compiler nor the theorem prover need to be correct. The paper makes this point on Page 3: Neither the compiler nor the prover need to be correct in order to be guaranteed to detect incorrect compiler output. This is a significant advantage ...

13

You probably want Manna, Pnueli, Axiomatic Approach to Total Correctness of Programs, 1973

12

Unfortunately, there are too many things are going on here. So, it is easy to mix things up. The use of "full" in "full completeness" and "full abstraction" refer to completely different ideas of fullness. But, there is also some vague connection between them. So, this is going to be a complicated answer. Full completeness: "Sound and complete" is a ...

12

Have you seen Arthur Charguéraud's PhD thesis, Characteristic Formulae for Mechanized Program Verification? Rather than building the type system and small-step semantics as inductive relations, he gives a technique for converting Caml programs into characteristic formulas. This are basically a generalization of predicate transformer semantics to support a ...

12

You are correct when you observe that for any particular terminating loop $L$ we may simply define the invariant "we're getting one step closer to termination". But proving that this is indeed a valid invariant may require transfinite induction! For instance, we could write a loop that computes the Goodstein sequence. This is particular sequence of numbers ...

11

The question is rather broad. To answer it in a reasonable space I will make many oversimplifications. Let us agree on terminology. A program is correct when it implies its specification. This vague statement is made precise in many ways, by pinning down what exactly is a program and what exactly is a specification. For example, in model checking the ...

10

There is a lot of work on Hoare Logic for object oriented programs, and for reasoning about memory allocation and deallocation. Some starting points: A Syntax-Directed Hoare Logic for Object-Oriented Programming Concepts Separation Logic, does not target OO-languages specifically but applies to the more fundamental problem of reasoning about heap-allocated ...

9

Amal Ahmed's very readable thesis dissertation could be a nice start.

9

I would like to add the following to Andrej's response (not enough rep for a comment). Indeed, we cannot avoid ordinals but we may hide them. One approach is to use some modal logic that takes essentially care of "we're one step closer to the end" without mentioning ordinals explicitly. This approach has been used successfully by Nakano and other people to ...

8

One approach to reducing the gap between a program and its specification is to use a language with a formal semantics. An interesting example here would be Esterel. Have a look at Gérard Berry's web page for some interesting talks about his work bringing formal methods into the real world. http://www-sop.inria.fr/members/Gerard.Berry/ p.s. Been on an ...

8

You could be interested in Jacques Garrigue's A Certified Implementation of ML with Structural Polymorphism and Recursive Types, which establishes the soundness of static and dynamic semantics and properties of type inference for a ML language with (recursion and) structural polymorphism, thus formalizing one of the more advanced corners of OCaml (...

7

Vijay D has mentioned both separation logic and jStar, which is a tool for verifying Java programs. jStar uses the logic Matthew Parkinson developed in his PhD thesis, Local Reasoning for Java, which gives a separation-based Hoare logic for verifying Java programs. It is a very well written thesis, and offers one of the most readable introductions to ...

7

The science of building reliable software in the "real world" is still being developed and is to some degree verging on an inherently cultural or anthropological study, because computers and software dont "cause" bugs— humans do! this answer will focus on general Q/A approaches of which formal software verification can be seen as one element. a remarkable ...

6

An old approach (but it is still used in some applications) is the N-version programming From Wikipedia: N-version programming (NVP), also known as multiversion programming, is a method or process in software engineering where multiple functionally equivalent programs are independently generated from the same initial specifications. The concept of N-...

6

Briefly, every theorem stated in first-order logic has a first-order proof. In his book "An Introduction to Mathematical Logic and Type Theory", Peter B. Andrews develops both first-order logic and a system of higher-order logic Q0, which is generally considered to be the theory basis of modern higher-order provers. (See the introduction to the HOL logic ...

6

The complexity is acceptable in current verifiers, and has been implemented in at least the AProVE termination analysis tool for term rewrite systems. They describe their implementation in Lazy Abstraction for Size-Change Termination, by Codish, Fuhs, Giesl & Schneider-Kamp, basing their implementation on the papers you refer to. Performance is good ...

6

Here are some results of a simple Google search: Certification of a Type Inference Tool for ML: Damas–Milner within Coq by Catherine Dubois and Valérie Ménissier-Morain Formalization of a Polymorphic Subtyping Algorithm by Jinxu Zhao, Bruno C. d. S. Oliveira, and Tom Schrijvers type-inference formalization in Coq, based on A Rewriting Semantics for Type ...

5

I don't know if it has been studied before, but after a quick look I think it should be PSPACE complete. We can build a reduction using the Nondeterministic Constraint Logic model of computation (NCL). I quick idea is the following (I assume you're familiar with the NCL model): given an NCL graph $G$, you can replace red and blue directed edges with a ...

5

Summary: full completeness means that the interpretation function is not just complete, but also surjective on programs. Full abstraction has no requirement for surjectivity. $\newcommand{\semb}[1]{[\![ #1 ]\!]}$ Details: The detailed meaning of full abstraction and full completeness depends on the nature of what/where/how you are interpreting. Here is a ...

4

There is also a three-page paper by Turing that uses ranking functions to give a correctness proof. His paper is completely readable by modern standards and extremely prescient. Checking a large routine, Alan Turing, Report of a Conference on High Speed Automatic Calculating Machines, pp.67-69, 1949.

4

The key idea here is that for any conjunction of equations $F\equiv u_1=v_1\wedge\ldots\wedge u_k=v_k$, the set $S_F$ is convex in the geometric sense, i.e. for any two points $p,q\in S_F$, all points between $p$ and $q$ are also in $S_F$. Now suppose that $F\Rightarrow G$, where $G$ is a disjunction of equations $x_1=y_1\vee\ldots\vee x_n=y_n$ (note that ...

4

As often in these matters, the encodings are important: you could have some silly encoding of Turing machines or Gallina terms or both where an input string $\langle n\rangle$ represents "the $n$-th well-typed term in Gallina". The TM that accepts this is trivial, and you'd be able to prove correctness and termination of the machine easily. See e.g. this ...

4

Levy's call by push value calculus makes a distinction between values and their thunks. For a value v of type ty the computation thunk v has type U ty. Lindley and McBride's Frank language, inspired by CBPV, also makes this distinction between computations and values explicit, though unlike Haskell, Frank is strict.

4

If I read you correctly, the intuition you have in mind goes like this: Suppose we have a program $P$, which takes a function as an argument. Further suppose that we have two functions $f$ and $g$, such that $f$ terminates on a subset of the inputs $g$ terminates on, but agrees with $g$ whenever they both terminate. Now, if $P\;g$ is partially correct, ...

4

Surely, you want $s_1 < s_2$ if there is a $t$ such that $s_1.t < s_2.t$ and $s_1.u \leq s_2.u$ for every other field $u$. That, at least, gives you a well-founded order. But there are many other well-founded orders on tuples, e.g. lexicographical order for some order of the fields (though you might need a heuristic to find the order), and various ...

3

This is a strange comparison. Your question is comparable to asking "how expressive is the ANSI C language specification compared to stdlib and compilation". The comparisons don't make sense. The Java Modelling Language can be used as a specification language to specify properties of code. The language alone does not solve the problem of verifying whether ...

3

In general, the technique used is known as "fuzzing". Not all errors are equally likely. Let's consider two hypothetical errors: System A incorrectly rejects a filename if it contains an | anywhere. System A incorrectly rejects a filename if it contains a prime number of b characters. Errors of the second type are much, much rarer, but this is not ...

3

I imagine that you can prove this straight from the operational semantics using the standard operational precongruence (assuming that you have a sequential language). Some of the relevant techniques have been collected in Operationally-based theories of program equivalence by Andy Pitts. If you have a Hoare logic of partial correctness for the language you ...

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