104,182 research outputs found
Programming Not Only by Example
In recent years, there has been tremendous progress in automated synthesis
techniques that are able to automatically generate code based on some intent
expressed by the programmer. A major challenge for the adoption of synthesis
remains in having the programmer communicate their intent. When the expressed
intent is coarse-grained (for example, restriction on the expected type of an
expression), the synthesizer often produces a long list of results for the
programmer to choose from, shifting the heavy-lifting to the user. An
alternative approach, successfully used in end-user synthesis is programming by
example (PBE), where the user leverages examples to interactively and
iteratively refine the intent. However, using only examples is not expressive
enough for programmers, who can observe the generated program and refine the
intent by directly relating to parts of the generated program.
We present a novel approach to interacting with a synthesizer using a
granular interaction model. Our approach employs a rich interaction model where
(i) the synthesizer decorates a candidate program with debug information that
assists in understanding the program and identifying good or bad parts, and
(ii) the user is allowed to provide feedback not only on the expected output of
a program, but also on the underlying program itself. That is, when the user
identifies a program as (partially) correct or incorrect, they can also
explicitly indicate the good or bad parts, to allow the synthesizer to accept
or discard parts of the program instead of discarding the program as a whole.
We show the value of our approach in a controlled user study. Our study shows
that participants have strong preference to using granular feedback instead of
examples, and are able to provide granular feedback much faster
Faster linearizability checking via -compositionality
Linearizability is a well-established consistency and correctness criterion
for concurrent data types. An important feature of linearizability is Herlihy
and Wing's locality principle, which says that a concurrent system is
linearizable if and only if all of its constituent parts (so-called objects)
are linearizable. This paper presents -compositionality, which generalizes
the idea behind the locality principle to operations on the same concurrent
data type. We implement -compositionality in a novel linearizability
checker. Our experiments with over nine implementations of concurrent sets,
including Intel's TBB library, show that our linearizability checker is one
order of magnitude faster and/or more space efficient than the state-of-the-art
algorithm.Comment: 15 pages, 2 figure
Analysis on the Possibility of RISC-V Adoption
As the interface between hardware and software, Instruction Set Architectures (ISAs) play a key role in the operation of computers. While both hardware and software have continued to evolve rapidly over time, ISAs have undergone minimal change. Since its release in 2010, RISC-V has begun to erode the industry aversion to ISA innovation. Established on the principals of the Reduced Instruction Set Computer (RISC), and as an open source ISA, RISC-V offers many benefits over popular ISAs like Intelâs x86 and Arm Holdingâs Advanced RISC Machine (ARM). In this literature review I evaluate the literature discussing: What makes changing Instruction Set Architectures difficultWhy might the industry choose to implement RISC-V When researching this topic I visited the IEEE (Institute of Electrical and Electronics Engineers), INSPEC (Engineering Village), and ACM (Association for Computing Machinery) Digital Library databases. I used the search terms, âRISC-Vâ, âInstruction Set Architectureâ, âRISC-Vâ AND âx86â, and âRISC-Vâ AND âInstruction Set Architectureâ. This literature review evaluates 10 papers on implementation of RISC-V. As this paper was intended to cover recent developments in the field, publication dates were limited to from 2015 to present
Meta-F*: Proof Automation with SMT, Tactics, and Metaprograms
We introduce Meta-F*, a tactics and metaprogramming framework for the F*
program verifier. The main novelty of Meta-F* is allowing the use of tactics
and metaprogramming to discharge assertions not solvable by SMT, or to just
simplify them into well-behaved SMT fragments. Plus, Meta-F* can be used to
generate verified code automatically.
Meta-F* is implemented as an F* effect, which, given the powerful effect
system of F*, heavily increases code reuse and even enables the lightweight
verification of metaprograms. Metaprograms can be either interpreted, or
compiled to efficient native code that can be dynamically loaded into the F*
type-checker and can interoperate with interpreted code. Evaluation on
realistic case studies shows that Meta-F* provides substantial gains in proof
development, efficiency, and robustness.Comment: Full version of ESOP'19 pape
Proceedings of the 3rd Workshop on Domain-Specific Language Design and Implementation (DSLDI 2015)
The goal of the DSLDI workshop is to bring together researchers and
practitioners interested in sharing ideas on how DSLs should be designed,
implemented, supported by tools, and applied in realistic application contexts.
We are both interested in discovering how already known domains such as graph
processing or machine learning can be best supported by DSLs, but also in
exploring new domains that could be targeted by DSLs. More generally, we are
interested in building a community that can drive forward the development of
modern DSLs. These informal post-proceedings contain the submitted talk
abstracts to the 3rd DSLDI workshop (DSLDI'15), and a summary of the panel
discussion on Language Composition
Symbolic Reachability Analysis of B through ProB and LTSmin
We present a symbolic reachability analysis approach for B that can provide a
significant speedup over traditional explicit state model checking. The
symbolic analysis is implemented by linking ProB to LTSmin, a high-performance
language independent model checker. The link is achieved via LTSmin's PINS
interface, allowing ProB to benefit from LTSmin's analysis algorithms, while
only writing a few hundred lines of glue-code, along with a bridge between ProB
and C using ZeroMQ. ProB supports model checking of several formal
specification languages such as B, Event-B, Z and TLA. Our experiments are
based on a wide variety of B-Method and Event-B models to demonstrate the
efficiency of the new link. Among the tested categories are state space
generation and deadlock detection; but action detection and invariant checking
are also feasible in principle. In many cases we observe speedups of several
orders of magnitude. We also compare the results with other approaches for
improving model checking, such as partial order reduction or symmetry
reduction. We thus provide a new scalable, symbolic analysis algorithm for the
B-Method and Event-B, along with a platform to integrate other model checking
improvements via LTSmin in the future
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