1,478 research outputs found
Building an IDE for the Calculational Derivation of Imperative Programs
In this paper, we describe an IDE called CAPS (Calculational Assistant for
Programming from Specifications) for the interactive, calculational derivation
of imperative programs. In building CAPS, our aim has been to make the IDE
accessible to non-experts while retaining the overall flavor of the
pen-and-paper calculational style. We discuss the overall architecture of the
CAPS system, the main features of the IDE, the GUI design, and the trade-offs
involved.Comment: In Proceedings F-IDE 2015, arXiv:1508.0338
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
Automated Generation of User Guidance by Combining Computation and Deduction
Herewith, a fairly old concept is published for the first time and named
"Lucas Interpretation". This has been implemented in a prototype, which has
been proved useful in educational practice and has gained academic relevance
with an emerging generation of educational mathematics assistants (EMA) based
on Computer Theorem Proving (CTP).
Automated Theorem Proving (ATP), i.e. deduction, is the most reliable
technology used to check user input. However ATP is inherently weak in
automatically generating solutions for arbitrary problems in applied
mathematics. This weakness is crucial for EMAs: when ATP checks user input as
incorrect and the learner gets stuck then the system should be able to suggest
possible next steps.
The key idea of Lucas Interpretation is to compute the steps of a calculation
following a program written in a novel CTP-based programming language, i.e.
computation provides the next steps. User guidance is generated by combining
deduction and computation: the latter is performed by a specific language
interpreter, which works like a debugger and hands over control to the learner
at breakpoints, i.e. tactics generating the steps of calculation. The
interpreter also builds up logical contexts providing ATP with the data
required for checking user input, thus combining computation and deduction.
The paper describes the concepts underlying Lucas Interpretation so that open
questions can adequately be addressed, and prerequisites for further work are
provided.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
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