A Concurrent Language with a Uniform Treatment of Regions and Locks

A challenge for programming language research is to design and implement multi-threaded low-level languages providing static guarantees for memory safety and freedom from data races. Towards this goal, we present a concurrent language employing safe region-based memory management and hierarchical locking of regions. Both regions and locks are treated uniformly, and the language supports ownership transfer, early deallocation of regions and early release of locks in a safe manner

A Polyvariant Binding-Time Analysis for Off-line Partial Deduction

We study the notion of binding-time analysis for logic programs. We formalise the unfolding aspect of an on-line partial deduction system as a Prolog program. Using abstract interpretation, we collect information about the run-time behaviour of the program. We use this information to make the control decisions about the unfolding at analysis time and to turn the on-line system into an off-line system. We report on some initial experiments.Comment: 19 pages (including appendix) Paper (without appendix) appeared in Programming Languages and Systems, Proceedings of the European Symposium on Programming (ESOP'98), Part of ETAPS'98 (Chris Hankin, eds.), LNCS, vol. 1381, 1998, pp. 27-4

Termination Proofs for Logic Programs with Tabling

Tabled logic programming is receiving increasing attention in the Logic Programming community. It avoids many of the shortcomings of SLD execution and provides a more flexible and often extremely efficient execution mechanism for logic programs. In particular, tabled execution of logic programs terminates more often than execution based on SLD-resolution. In this article, we introduce two notions of universal termination of logic programming with Tabling: quasi-termination and (the stronger notion of) LG-termination. We present sufficient conditions for these two notions of termination, namely quasi-acceptability and LG-acceptability, and we show that these conditions are also necessary in case the tabling is well-chosen. Starting from these conditions, we give modular termination proofs, i.e., proofs capable of combining termination proofs of separate programs to obtain termination proofs of combined programs. Finally, in the presence of mode information, we state sufficient conditions which form the basis for automatically proving termination in a constraint-based way.Comment: 48 pages, 6 figures, submitted to ACM Transactions on Computational Logic (TOCL

Static Detection of Race Conditions in Erlang

We address the problem of detecting some commonly occurring kinds of race conditions in Erlang programs using static analysis. Our analysis is completely automatic, fast and scalable, and avoids false alarms by taking language characteristics into account. We have integrated our analysis in dialyzer, a commonly used tool for detecting software defects in Erlang programs which is part of Erlang/OTP, and evaluate its effectiveness and performance on a suite of widely used industrial and open source programs of considerable size. The analysis has detected a significant number of previously unknown race conditions

Test-Driven Development of Concurrent Programs using Concuerror

This paper advocates the test-driven development of concurrent Erlang programs in order to detect early and eliminate the vast majority of concurrency-related errors that may occur in their execution. To facilitate this task we have developed a tool, called Concuerror, that exhaustively explores process interleaving (possibly up to some preemption bound) and presents detailed interleaving information of any errors that occur. We describe in detail the use of Concuerror on a non-trivial concurrent Erlang program that we develop step by step in a test-driven fashion

Recovering joint and individual components in facial data

A set of images depicting faces with different expressions or in various ages consists of components that are shared across all images (i.e., joint components) and imparts to the depicted object the properties of human faces and individual components that are related to different expressions or age groups. Discovering the common (joint) and individual components in facial images is crucial for applications such as facial expression transfer. The problem is rather challenging when dealing with images captured in unconstrained conditions and thus are possibly contaminated by sparse non-Gaussian errors of large magnitude (i.e., sparse gross errors) and contain missing data. In this paper, we investigate the use of a method recently introduced in statistics, the so-called Joint and Individual Variance Explained (JIVE) method, for the robust recovery of joint and individual components in visual facial data consisting of an arbitrary number of views. Since, the JIVE is not robust to sparse gross errors, we propose alternatives, which are 1) robust to sparse gross, non-Gaussian noise, 2) able to automatically find the individual components rank, and 3) can handle missing data. We demonstrate the effectiveness of the proposed methods to several computer vision applications, namely facial expression synthesis and 2D and 3D face age progression in-the-wild

Recovering joint and individual components in facial data

A set of images depicting faces with different expressions or in various ages consists of components that are shared across all images (i.e., joint components) imparting to the depicted object the properties of human faces as well as individual components that are related to different expressions or age groups. Discovering the common (joint) and individual components in facial images is crucial for applications such as facial expression transfer and age progression. The problem is rather challenging when dealing with images captured in unconstrained conditions in the presence of sparse non-Gaussian errors of large magnitude (i.e., sparse gross errors or outliers) and contain missing data. In this paper, we investigate the use of a method recently introduced in statistics, the so-called Joint and Individual Variance Explained (JIVE) method, for the robust recovery of joint and individual components in visual facial data consisting of an arbitrary number of views. Since the JIVE is not robust to sparse gross errors, we propose alternatives, which are (1) robust to sparse gross, non-Gaussian noise, (2) able to automatically find the individual components rank, and (3) can handle missing data. We demonstrate the effectiveness of the proposed methods to several computer vision applications, namely facial expression synthesis and 2D and 3D face age progression ‘in-the-wild’

Robust statistical frontalization of human and animal faces

The unconstrained acquisition of facial data in real-world conditions may result in face images with significant pose variations, illumination changes, and occlusions, affecting the performance of facial landmark localization and recognition methods. In this paper, a novel method, robust to pose, illumination variations, and occlusions is proposed for joint face frontalization and landmark localization. Unlike the state-of-the-art methods for landmark localization and pose correction, where large amount of manually annotated images or 3D facial models are required, the proposed method relies on a small set of frontal images only. By observing that the frontal facial image of both humans and animals, is the one having the minimum rank of all different poses, a model which is able to jointly recover the frontalized version of the face as well as the facial landmarks is devised. To this end, a suitable optimization problem is solved, concerning minimization of the nuclear norm (convex surrogate of the rank function) and the matrix ℓ1 norm accounting for occlusions. The proposed method is assessed in frontal view reconstruction of human and animal faces, landmark localization, pose-invariant face recognition, face verification in unconstrained conditions, and video inpainting by conducting experiment on 9 databases. The experimental results demonstrate the effectiveness of the proposed method in comparison to the state-of-the-art methods for the target problems