Efficient and Effective Handling of Exceptions in Java Points-To Analysis

A joint points-to and exception analysis has been shown to yield benefits in both precision and performance. Treating exceptions as regular objects, however, incurs significant and rather unexpected overhead. We show that in a typical joint analysis most of the objects computed to flow in and out of a method are due to exceptional control-flow and not normal call-return control-flow. For instance, a context-insensitive analysis of the Antlr benchmark from the DaCapo suite computes 4-5 times more objects going in or out of a method due to exceptional control-flow than due to normal control-flow. As a consequence, the analysis spends a large amount of its time considering exceptions. We show that the problem can be addressed both e ectively and elegantly by coarsening the representation of exception objects. An interesting find is that, instead of recording each distinct exception object, we can collapse all exceptions of the same type, and use one representative object per type, to yield nearly identical precision (loss of less than 0.1%) but with a boost in performance of at least 50% for most analyses and benchmarks and large space savings (usually 40% or more)

Inversions of statistical parameters of an acoustic signal in range-dependent environments with applications in ocean acoustic tomography

The paper presents an application of a method for the characterization of underwater acoustic signals based on the statistics of their wavelet transform sub-band coefficients in range-dependent environments. As it was illustrated in previous works, this statistical characterization scheme is a very efficient tool for obtaining observables to be exploited in problems of ocean acoustic tomography and geoacoustic inversion, when range-independent environments are considered. Now the scheme is applied in range-dependent environments for the estimation of range-dependent features in shallow water. A simple denoising strategy, also presented in the paper, is shown to enhance the quality of the inversion results, as it helps to keep the signal characterization to the energy significant part of it. The results presented for typical test cases are encouraging and indicative of the potential of the method for the treatment of inverse problems in acoustical oceanography

Class Hierarchy Complementation: Soundly Completing a Partial Type Graph

We present the problem of class hierarchy complementa- tion: given a partially known hierarchy of classes together with subtyping constraints (“A has to be a transitive sub- type of B”) complete the hierarchy so that it satisfies all con- straints. The problem has immediate practical application to the analysis of partial programs—e.g., it arises in the process of providing a sound handling of “phantom classes” in the Soot program analysis framework. We provide algorithms to solve the hierarchy complementation problem in the single inheritance and multiple inheritance settings. We also show that the problem in a language such as Java, with single in- heritance but multiple subtyping and distinguished class vs. interface types, can be decomposed into separate single- and multiple-subtyping instances. We implement our algorithms in a tool, JPhantom, which complements partial Java byte- code programs so that the result is guaranteed to satisfy the Java verifier requirements. JPhantom is highly scalable and runs in mere seconds even for large input applications and complex constraints (with a maximum of 14s for a 19MB binary)

Inversion of acoustical data from the SW06 experiment, using a statistical method for signal characterization

his paper presents an application of an acoustic signal characterization scheme for ocean acoustic tomography and geoacoustic inversions proposed by Taroudakis et al., using real data. The work is the first attempt to validate the proposed scheme with data taken from sea experiments. The data have been collected during the SW06 experiment held in the New Jersey Continental Shelf and the inversion results (sea-bed geoacoustic parameters and source range) are compared with those reported by Bonnel and Chapman. The comparison and the signal reconstruction using estimated values of the model parameters is satisfactory being an indication that the new signal characterization method can be used in practical applications of acoustical oceanography

The State of Network Neutrality Regulation

The Network Neutrality (NN) debate refers to the battle over the design of a regulatory framework for preserving the Internet as a public network and open innovation platform. Fueled by concerns that broadband access service providers might abuse network management to discriminate against third party providers (e.g., content or application providers), policymakers have struggled with designing rules that would protect the Internet from unreasonable network management practices. In this article, we provide an overview of the history of the debate in the U.S. and the EU and highlight the challenges that will confront network engineers designing and operating networks as the debate continues to evolve.BMBF, 16DII111, Verbundprojekt: Weizenbaum-Institut für die vernetzte Gesellschaft - Das Deutsche Internet-Institut; Teilvorhaben: Wissenschaftszentrum Berlin für Sozialforschung (WZB)EC/H2020/679158/EU/Resolving the Tussle in the Internet: Mapping, Architecture, and Policy Making/ResolutioNe

Set-Based Pre-Processing for Points-To Analysis

We present set-based pre-analysis: a virtually universal op- timization technique for flow-insensitive points-to analysis. Points-to analysis computes a static abstraction of how ob- ject values flow through a program’s variables. Set-based pre-analysis relies on the observation that much of this rea- soning can take place at the set level rather than the value level. Computing constraints at the set level results in sig- nificant optimization opportunities: we can rewrite the in- put program into a simplified form with the same essential points-to properties. This rewrite results in removing both local variables and instructions, thus simplifying the sub- sequent value-based points-to computation. E ectively, set- based pre-analysis puts the program in a normal form opti- mized for points-to analysis. Compared to other techniques for o -line optimization of points-to analyses in the literature, the new elements of our approach are the ability to eliminate statements, and not just variables, as well as its modularity: set-based pre-analysis can be performed on the input just once, e.g., allowing the pre-optimization of libraries that are subsequently reused many times and for di erent analyses. In experiments with Java programs, set-based pre-analysis eliminates 30% of the program’s local variables and 30% or more of computed context-sensitive points-to facts, over a wide set of bench- marks and analyses, resulting in a 20% average speedup (max: 110%, median: 18%)