1,590 research outputs found
Isabelle/PIDE as Platform for Educational Tools
The Isabelle/PIDE platform addresses the question whether proof assistants of
the LCF family are suitable as technological basis for educational tools. The
traditionally strong logical foundations of systems like HOL, Coq, or Isabelle
have so far been counter-balanced by somewhat inaccessible interaction via the
TTY (or minor variations like the well-known Proof General / Emacs interface).
Thus the fundamental question of math education tools with fully-formal
background theories has often been answered negatively due to accidental
weaknesses of existing proof engines.
The idea of "PIDE" (which means "Prover IDE") is to integrate existing
provers like Isabelle into a larger environment, that facilitates access by
end-users and other tools. We use Scala to expose the proof engine in ML to the
JVM world, where many user-interfaces, editor frameworks, and educational tools
already exist. This shall ultimately lead to combined mathematical assistants,
where the logical engine is in the background, without obstructing the view on
applications of formal methods, formalized mathematics, and math education in
particular.Comment: In Proceedings THedu'11, arXiv:1202.453
Calculational Proofs in ACL2s
Teaching college students how to write rigorous proofs is a critical
objective in courses that introduce formal reasoning. Over the course of
several years, we have developed a mechanically-checkable style of
calculational reasoning that we used to teach over a thousand freshman-level
undergraduate students how to reason about computation in our "Logic and
Computation" class at Northeastern University. We were inspired by Dijkstra,
who advocated the use of calculational proofs, writing "calculational proofs
are almost always more effective than all informal alternatives, ..., the
design of calculational proofs seems much more teachable than the elusive art
of discovering an informal proof." Our calculational proof checker is
integrated into ACL2s and is available as an Eclipse IDE plugin, via a Web
interface, and as a stand-alone tool. It automatically checks proofs for
correctness and provides useful feedback. We describe the architecture of the
checker, its proof format, its underlying algorithms, its correctness and
provide examples using proofs from our undergraduate class and from Dijkstra.
We also describe our experiences using the proof checker to teach
undergraduates how to formally reason about computation
Variability Abstractions: Trading Precision for Speed in Family-Based Analyses (Extended Version)
Family-based (lifted) data-flow analysis for Software Product Lines (SPLs) is
capable of analyzing all valid products (variants) without generating any of
them explicitly. It takes as input only the common code base, which encodes all
variants of a SPL, and produces analysis results corresponding to all variants.
However, the computational cost of the lifted analysis still depends inherently
on the number of variants (which is exponential in the number of features, in
the worst case). For a large number of features, the lifted analysis may be too
costly or even infeasible. In this paper, we introduce variability abstractions
defined as Galois connections and use abstract interpretation as a formal
method for the calculational-based derivation of approximate (abstracted)
lifted analyses of SPL programs, which are sound by construction. Moreover,
given an abstraction we define a syntactic transformation that translates any
SPL program into an abstracted version of it, such that the analysis of the
abstracted SPL coincides with the corresponding abstracted analysis of the
original SPL. We implement the transformation in a tool, reconfigurator that
works on Object-Oriented Java program families, and evaluate the practicality
of this approach on three Java SPL benchmarks.Comment: 50 pages, 10 figure
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