We show how to determine statically whether it is safe for untrusted machine code to be loaded into a trusted host system. Our safety-checking technique operates directly on the untrusted machine-code program, requiring only that the initial inputs to the untrusted program be annotated

sophisticated machine-coding system based on our research. We then discuss a number of problems we have encountered in machine coding, focusing on the Reuters data source and the KEDS program itself. The paper concludes with a discussion of future approaches to machine coding in event data research and other

Formally establishing safety properties of software presents a grand challenge to the computer science community. Producing proof-carrying code, i.e., machine code with machine-checkable specifications and proofs, is particularly difficult for system softwares written in low-level languages. One

Ensemble methods are learning algorithms that construct a set of classifiers and then classify new data points by taking a (weighted) vote of their predictions. The original ensemble method is Bayesian averaging, but more recent algorithms include error-correcting output coding, Bagging

The New Jersey Machine-Code Toolkit helps programmers write applications that process machine code. Applications that use the toolkit are written at an assembly-language level of abstraction, but they recognize and emit binary. Guided by a short instructionset specification, the toolkit generates

Abstract. We present the algorithms used in MCVETO (Machine-Code VErification TOol), a tool to check whether a stripped machinecode program satisfies a safety property. The verification problem that MCVETO addresses is challenging because it cannot assume that it has access to (i) certain

-late. Often there is no feasible method to recharge motes, so energy is a precious resource. Once deployed, a network must be reprogrammable although physically unreachable, and this reprogramming can be a significant energy cost. We present Maté, a tiny communication-centric virtual machine designed

Performance-critical components of virtual machines are often implemented in assembly language. Traditionally, this code is compiled with an assembler and linked statically with the rest of the system. Generating this code at startup time has significant engineering advantages over the conventional

pipelining is that optimal performance can be achieved with compact object code. This paper extends previous results of software pipelining in two ways: First, this paper shows that by using an im-proved algorithm, near-optimal performance can be obtained without specialized hardware. Second, we propose a

Abstract. This paper shows how a machine-code Hoare logic is used to lift reasoning from the tedious operational model of a machine language to a manageable level of abstraction without making simplifying assumptions. A Hoare logic is placed on top of a high-fidelity model of the ARM instruction