Deductive Software Verification: From Pen-and-Paper Proofs to Industrial Tools

Abstract

Deductive software verification aims at formally verifying that all possible behaviors of a given program satisfy formally defined, possibly complex properties, where the verification process is based on logical inference. We follow the trajectory of the field from its inception in the late 1960s via its current state to its promises for the future, from pen-and-paper proofs for programs written in small, idealized languages to highly automated proofs of complex library or system code written in mainstream languages. We take stock of the state-of-art and give a list of the most important challenges for the further development of the field of deductive software verification.

Methods, Languages and Tools for Future System Development

“…Deductive Verification: From Pen-and-Paper Proofs to Industrial Tools [15] provides a retrospective view on the development of deductive software verification, the discipline aiming at formally verifying that all possible behaviors of a given program satisfy formally defined, possibly complex properties, where the verification process is based on logical inference. Following the trajectory of the field from its inception in the late 1960s via its current state to its promises for the future, from pen-and-paper proofs for programs written in small, idealized languages to highly automated proofs of complex library or system code written in mainstream languages, the chapter establishes the stateof-the-art and provides a list of the most important challenges for the further development of the field.…”

The 10,000 Facets of MDP Model Checking

“…The often excessive size of the state space spanned by a concrete verification problem is a major impediment to practicality across the entire spectrum of verification methods, see e.g. [2,92]. This problem of state-space explosion also affects negatively the basic probabilistic model checking procedures we discussed thus far.…”

Language-Driven Engineering: From General-Purpose to Purpose-Specific Languages

“…Also the approaches presented in the remaining papers could profit from DSLs, e.g., as follows: [41] for specifying certain assertions or contracts, [43] for specifying data flow analyses 20 , [25] for specifying test models, [42] for defining learning alphabets or representing the learning result, [40] for modularly specifying the required code instrumentation, e.g. in an aspect-oriented fashion, and [15,19,66] for conveniently specifying their enriched system structures.…”