Towards an Adaptive Skeleton Framework for Performance Portability

The proliferation of widely available, but very different, parallel architectures makes the ability to deliver good parallel performance on a range of architectures, or performance portability, highly desirable. Irregularly-parallel problems, where the number and size of tasks is unpredictable, are particularly challenging and require dynamic coordination. The paper outlines a novel approach to delivering portable parallel performance for irregularly parallel programs. The approach combines declarative parallelism with JIT technology, dynamic scheduling, and dynamic transformation. We present the design of an adaptive skeleton library, with a task graph implementation, JIT trace costing, and adaptive transformations. We outline the architecture of the protoype adaptive skeleton execution framework in Pycket, describing tasks, serialisation, and the current scheduler.We report a preliminary evaluation of the prototype framework using 4 micro-benchmarks and a small case study on two NUMA servers (24 and 96 cores) and a small cluster (17 hosts, 272 cores). Key results include Pycket delivering good sequential performance e.g. almost as fast as C for some benchmarks; good absolute speedups on all architectures (up to 120 on 128 cores for sumEuler); and that the adaptive transformations do improve performance

Canonical Abstract Syntax Trees

This paper presents Gom, a language for describing abstract syntax trees and generating a Java implementation for those trees. Gom includes features allowing the user to specify and modify the interface of the data structure. These features provide in particular the capability to maintain the internal representation of data in canonical form with respect to a rewrite system. This explicitly guarantees that the client program only manipulates normal forms for this rewrite system, a feature which is only implicitly used in many implementations

EVMPatch: Timely and Automated Patching of Ethereum Smart Contracts

Recent attacks exploiting errors in smart contract code had devastating consequences thereby questioning the benefits of this technology. It is currently highly challenging to fix errors and deploy a patched contract in time. Instant patching is especially important since smart contracts are always online due to the distributed nature of blockchain systems. They also manage considerable amounts of assets, which are at risk and often beyond recovery after an attack. Existing solutions to upgrade smart contracts depend on manual and error-prone processes. This paper presents a framework, called EVMPatch, to instantly and automatically patch faulty smart contracts. EVMPatch features a bytecode rewriting engine for the popular Ethereum blockchain, and transparently/automatically rewrites common off-the-shelf contracts to upgradable contracts. The proof-of-concept implementation of EVMPatch automatically hardens smart contracts that are vulnerable to integer over/underflows and access control errors, but can be easily extended to cover more bug classes. Our extensive evaluation on 14,000 real-world (vulnerable) contracts demonstrate that our approach successfully blocks attack transactions launched on these contracts, while keeping the intended functionality of the contract intact. We perform a study with experienced software developers, showing that EVMPatch is practical, and reduces the time for converting a given Solidity smart contract to an upgradable contract by 97.6 %, while ensuring functional equivalence to the original contract.Comment: A slightly shorter version of this paper will be published at USENIX Security Symposium 202

The program is the model: Enabling [email protected]

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-36089-3_7Revised Selected Papers of 5th International Conference, SLE 2012, Dresden, Germany, September 26-28, 2012The increasing application of Model-Driven Engineering in a wide range of domains, in addition to pure code generation, raises the need to manipulate models at runtime, as part of regular programs. Moreover, certain kinds of programming tasks can be seen as model transformation tasks, and thus we could take advantage of model transformation technology in order to facilitate them. In this paper we report on our works to bridge the gap between regular programming and model transformation by enabling the manipulation of Java APIs as models. Our approach is based on the specification of a mapping between a Java API (e.g., Swing) and a meta-model describing it. A model transformation definition is written against the API meta-model and we have built a compiler that generates the corresponding Java bytecode according to the mapping. We present several application scenarios and discuss the mapping between object-oriented meta-modelling and the Java object system. Our proposal has been validated by a prototype implementation which is also contributed.Work funded by the Spanish Ministry of Economy and Competitivity (TIN2011-24139), and the R&D programme of Madrid Region (S2009/TIC-1650)

Jalapa: Securing Java with Local Policies Tool Demonstration

AbstractWe present Jalapa, a tool for securing Java bytecode programs with history-based usage policies. Policies are defined by usage automata, that recognize the forbidden execution histories. Usage automata are expressive enough to allow programmers specify of many real-world usage policies; yet, they are simple enough to permit formal reasoning. Programmers can sandbox untrusted pieces of code with usage policies. The Jalapa tool rewrites the Java bytecode by adding the hooks for the mechanism that enforces the given policies at run-time

Populating the Peephole Optimizer of a Smart Contract Compiler

Developing compiler optimizations, especially for new, rapidly evolving smart contract languages, can be onerous and error-prone, but is especially important for smart contracts, where deployment and execution directly translate to monetary cost and which cannot change once deployed. One common optimization technique is the use of peephole optimizations, replacement rules that are applied using pattern-matching. These rules are normally constructed using human expertise, which is both time-consuming and far from systematic in exploring opportunities for optimization. In this work we propose a pipeline to automatically populate the peephole optimizer of a smart contract compiler. We apply superoptimization to an existing code base to obtain sequences of instructions, which can be replaced by cheaper, observationally equivalent instructions. We then generate peephole optimization rules by extracting the underlying patterns of these optimizations. We provide a case study of our approach and a prototype implementation for bytecode of the Ethereum Virtual Machine, the tool ppltr, which combines the superoptimizer ebso and the rule generator sorg. Then we evaluate our approach by generating and applying nearly 1k peephole optimization rules extracted from 2k optimizations obtained from deployed bytecode

Proving termination of programs automatically with AProVE

AProVE is a system for automatic termination and complexity proofs of Java, C, Haskell, Prolog, and term rewrite systems (TRSs). To analyze programs in high-level languages, AProVE automatically converts them to TRSs. Then, a wide range of techniques is employed to prove termination and to infer complexity bounds for the resulting TRSs. The generated proofs can be exported to check their correctness using automatic certifiers. For use in software construction, we present an AProVE plug-in for the popular Eclipse software development environment

Rewriting Strategies in Java

International audienceIn any language designed to express transformations, the notion of rewrite rule is a key feature. Its conciseness as well as its strong theoretical foundations are essential. The notion of strategy is complementary: this describes how rules are applied. In this paper, we show how a high-level strategy language can be implemented in a Java setting. We present the integration of the visitor combinator design pattern into Tom. This corresponds to an interpreter for strategy expressions. To be more efficient, we present a compilation method based on bytecode specialization. This low-level transformation is expressed in Tom itself, using rules and strategies