SimSight: A Virtual Machine Based Dynamic Call Graph Generator

One problem with using component-based software development approach is that once software modules are reused over generations of products, they form legacy structures that can be challenging to understand, making validating these systems difficult. Therefore, tools and methodologies that enable engineers to see interactions of these software modules will enhance their ability to make these software systems more dependable. To address this need, we propose SimSight, a framework to capture dynamic call graphs in Simics, a widely adopted commercial full-system simulator. Simics is a software system that simulates complete computer systems. Thus, it performs nearly identical tasks to a real system but at a much lower speed while providing greater execution observability. We have implemented SimSight to generate dynamic call graphs of statically and dynamically linked functions in x86/Linux environment. A case study illustrates how we can use SimSight to identify sources of software errors. We then evaluate its performance using 12 integer programs from SPEC CPU2006 benchmark suite.

Génération efficace de graphes d’appels dynamiques complets

Analyser le code permet de vérifier ses fonctionnalités, détecter des bogues ou améliorer sa performance. L’analyse du code peut être statique ou dynamique. Des approches combinants les deux analyses sont plus appropriées pour les applications de taille industrielle où l’utilisation individuelle de chaque approche ne peut fournir les résultats souhaités. Les approches combinées appliquent l’analyse dynamique pour déterminer les portions à problèmes dans le code et effectuent par la suite une analyse statique concentrée sur les parties identifiées. Toutefois les outils d’analyse dynamique existants génèrent des données imprécises ou incomplètes, ou aboutissent en un ralentissement inacceptable du temps d’exécution. Lors de ce travail, nous nous intéressons à la génération de graphes d’appels dynamiques complets ainsi que d’autres informations nécessaires à la détection des portions à problèmes dans le code. Pour ceci, nous faisons usage de la technique d’instrumentation dynamique du bytecode Java pour extraire l’information sur les sites d’appels, les sites de création d’objets et construire le graphe d’appel dynamique du programme. Nous démontrons qu’il est possible de profiler dynamiquement une exécution complète d’une application à temps d’exécution non triviale, et d’extraire la totalité de l’information à un coup raisonnable. Des mesures de performance de notre profileur sur trois séries de benchmarks à charges de travail diverses nous ont permis de constater que la moyenne du coût de profilage se situe entre 2.01 et 6.42. Notre outil de génération de graphes dynamiques complets, nommé dyko, constitue également une plateforme extensible pour l’ajout de nouvelles approches d’instrumentation. Nous avons testé une nouvelle technique d’instrumentation des sites de création d’objets qui consiste à adapter les modifications apportées par l’instrumentation au bytecode de chaque méthode. Nous avons aussi testé l’impact de la résolution des sites d’appels sur la performance générale du profileur.

An approach to profiling for run-time checking of computational properties and performance debugging in logic programs.

Although several profiling techniques for identifying performance bottlenecks in logic programs have been developed, they are generally not automatic and in most cases they do not provide enough information for identifying the root causes of such bottlenecks. This complicates using their results for guiding performance improvement. We present a profiling method and tool that provides such explanations. Our profiler associates cost centers to certain program elements and can measure different types of resource-related properties that affect performance, preserving the precedence of cost centers in the call graph. It includes an automatic method for detecting procedures that are performance bottlenecks. The profiling tool has been integrated in a previously developed run-time checking framework to allow verification of certain properties when they cannot be verified statically. The approach allows checking global computational properties which require complex instrumentation tracking information about previous execution states, such as, e.g., that the execution time accumulated by a given procedure is not greater than a given bound. We have built a prototype implementation, integrated it in the Ciao/CiaoPP system and successfully applied it to performance improvement, automatic optimization (e.g., resource-aware specialization of programs), run-time checking, and debugging of global computational properties (e.g., resource usage) in Prolog programs.

Graph coloring applied to secure computation in non-Abelian groups

We study the natural problem of secure n-party computation (in the computationally unbounded attack model) of circuits over an arbitrary finite non-Abelian group (G,⋅), which we call G-circuits. Besides its intrinsic interest, this problem is also motivating by a completeness result of Barrington, stating that such protocols can be applied for general secure computation of arbitrary functions. For flexibility, we are interested in protocols which only require black-box access to the group G (i.e. the only computations performed by players in the protocol are a group operation, a group inverse, or sampling a uniformly random group element). Our investigations focus on the passive adversarial model, where up to t of the n participating parties are corrupted.

Graph Wavelets for Spatial Traffic Analysis

A number of problems in network operations and engineering call for new methods of traffic analysis. While most existing traffic analysis methods are fundamentally temporal, there is a clear need for the analysis of traffic across multiple network links — that is, for spatial traffic analysis. In this paper we give examples of problems that can be addressed via spatial traffic analysis. We then propose a formal approach to spatial traffic analysis based on the wavelet transform. Our approach (graph wavelets) generalizes the traditional wavelet transform so that it can be applied to data elements connected via an arbitrary graph topology. We explore the necessary and desirable properties of this approach and consider some of its possible realizations. We then apply graph wavelets to measurements from an operating network. Our results show that graph wavelets are very useful for our motivating problems; for example, they can be used to form highly summarized views of an entire network's traffic load, to gain insight into a network's global traffic response to a link failure, and to localize the extent of a failure event within the network.

The Forgiving Graph: a distributed data structure for low stretch under adversarial attack

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick “repairs,” which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions, without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been l in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most l log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degree would have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from Hayes et al. (2008) in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it requires only a very simple and minimal initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network.

The Forgiving Graph:A distributed data structure for low stretch under adversarial attack

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that, over a sequence of rounds, an adversary either inserts a node with arbitrary connections or deletes an arbitrary node from the network. The network responds to each such change by quick "repairs," which consist of adding or deleting a small number of edges. These repairs essentially preserve closeness of nodes after adversarial deletions,without increasing node degrees by too much, in the following sense. At any point in the algorithm, nodes v and w whose distance would have been - in the graph formed by considering only the adversarial insertions (not the adversarial deletions), will be at distance at most - log n in the actual graph, where n is the total number of vertices seen so far. Similarly, at any point, a node v whose degreewould have been d in the graph with adversarial insertions only, will have degree at most 3d in the actual graph. Our distributed data structure, which we call the Forgiving Graph, has low latency and bandwidth requirements. The Forgiving Graph improves on the Forgiving Tree distributed data structure from Hayes et al. (2008) in the following ways: 1) it ensures low stretch over all pairs of nodes, while the Forgiving Tree only ensures low diameter increase; 2) it handles both node insertions and deletions, while the Forgiving Tree only handles deletions; 3) it requires only a very simple and minimal initialization phase, while the Forgiving Tree initially requires construction of a spanning tree of the network. © Springer-Verlag 2012.

Exact computation of the adjacency graph of an arrangement of quadrics

Präsentiert wird ein vollständiger, exakter und effizienter Algorithmus zur Berechnung des Nachbarschaftsgraphen eines Arrangements von Quadriken (Algebraische Flächen vom Grad 2). Dies ist ein wichtiger Schritt auf dem Weg zur Berechnung des vollen 3D Arrangements. Dabei greifen wir auf eine bereits existierende Implementierung zur Berechnung der exakten Parametrisierung der Schnittkurve von zwei Quadriken zurück. Somit ist es möglich, die exakten Parameterwerte der Schnittpunkte zu bestimmen, diese entlang der Kurven zu sortieren und den Nachbarschaftsgraphen zu berechnen. Wir bezeichnen unsere Implementierung als vollständig, da sie auch die Behandlung aller Sonderfälle wie singulärer oder tangentialer Schnittpunkte einschließt. Sie ist exakt, da immer das mathematisch korrekte Ergebnis berechnet wird. Und schließlich bezeichnen wir unsere Implementierung als effizient, da sie im Vergleich mit dem einzigen bisher implementierten Ansatz gut abschneidet. Implementiert wurde unser Ansatz im Rahmen des Projektes EXACUS. Das zentrale Ziel von EXACUS ist es, einen Prototypen eines zuverlässigen und leistungsfähigen CAD Geometriekerns zu entwickeln. Obwohl wir das Design unserer Bibliothek als prototypisch bezeichnen, legen wir dennoch größten Wert auf Vollständigkeit, Exaktheit, Effizienz, Dokumentation und Wiederverwendbarkeit. Über den eigentlich Beitrag zu EXACUS hinaus, hatte der hier vorgestellte Ansatz durch seine besonderen Anforderungen auch wesentlichen Einfluss auf grundlegende Teile von EXACUS. Im Besonderen hat diese Arbeit zur generischen Unterstützung der Zahlentypen und der Verwendung modularer Methoden innerhalb von EXACUS beigetragen. Im Rahmen der derzeitigen Integration von EXACUS in CGAL wurden diese Teile bereits erfolgreich in ausgereifte CGAL Pakete weiterentwickelt.

Beyond the tree of texts: Building an empirical model of scribal variation through graph analysis of texts and stemmata

Stemmatology, or the reconstruction of the transmission history of texts, is a field that stands particularly to gain from digital methods. Many scholars already take stemmatic approaches that rely heavily on computational analysis of the collated text (e.g. Robinson and O’Hara 1996; Salemans 2000; Heikkilä 2005; Windram et al. 2008 among many others). Although there is great value in computationally assisted stemmatology, providing as it does a reproducible result and allowing access to the relevant methodological process in related fields such as evolutionary biology, computational stemmatics is not without its critics. The current state-of-the-art effectively forces scholars to choose between a preconceived judgment of the significance of textual differences (the Lachmannian or neo-Lachmannian approach, and the weighted phylogenetic approach) or to make no judgment at all (the unweighted phylogenetic approach). Some basis for judgment of the significance of variation is sorely needed for medieval text criticism in particular. By this, we mean that there is a need for a statistical empirical profile of the text-genealogical significance of the different sorts of variation in different sorts of medieval texts. The rules that apply to copies of Greek and Latin classics may not apply to copies of medieval Dutch story collections; the practices of copying authoritative texts such as the Bible will most likely have been different from the practices of copying the Lives of local saints and other commonly adapted texts. It is nevertheless imperative that we have a consistent, flexible, and analytically tractable model for capturing these phenomena of transmission. In this article, we present a computational model that captures most of the phenomena of text variation, and a method for analysis of one or more stemma hypotheses against the variation model. We apply this method to three ‘artificial traditions’ (i.e. texts copied under laboratory conditions by scholars to study the properties of text variation) and four genuine medieval traditions whose transmission history is known or deduced in varying degrees. Although our findings are necessarily limited by the small number of texts at our disposal, we demonstrate here some of the wide variety of calculations that can be made using our model. Certain of our results call sharply into question the utility of excluding ‘trivial’ variation such as orthographic and spelling changes from stemmatic analysis.

A note on adding objects to an existing twoway graph

In Stata, graphs are usually generated by one call to the graph command. Sometimes, however, it would be convenient to be able to add objects to a graph after the graph has been created. In this article, I provide a command called addplot that offers such functionality for twoway graphs, capitalizing on an undocumented feature of Stata's graphics system.

Building the View Graph of a Category by Exploiting Image Realism

We propose a weakly supervised method to arrange images of a given category based on the relative pose between the camera and the object in the scene. Relative poses are points on a sphere centered at the object in a given canonical pose, which we call object viewpoints. Our method builds a graph on this sphere by assigning images with similar viewpoint to the same node and by connecting nodes if they are related by a small rotation. The key idea is to exploit a large unlabeled dataset to validate the likelihood of dominant 3D planes of the object geometry. A number of 3D plane hypotheses are evaluated by applying small 3D rotations to each hypothesis and by measuring how well the deformed images match other images in the dataset. Correct hypotheses will result in deformed images that correspond to plausible views of the object, and thus will likely match well other images in the same category. The identified 3D planes are then used to compute affinities between images related by a change of viewpoint. We then use the affinities to build a view graph via a greedy method and the maximum spanning tree.

Semantic Mining based on graph theory and ontologies. Case Study: Cell Signaling Pathways

In this paper we use concepts from graph theory and cellular biology represented as ontologies, to carry out semantic mining tasks on signaling pathway networks. Specifically, the paper describes the semantic enrichment of signaling pathway networks. A cell signaling network describes the basic cellular activities and their interactions. The main contribution of this paper is in the signaling pathway research area, it proposes a new technique to analyze and understand how changes in these networks may affect the transmission and flow of information, which produce diseases such as cancer and diabetes. Our approach is based on three concepts from graph theory (modularity, clustering and centrality) frequently used on social networks analysis. Our approach consists into two phases: the first uses the graph theory concepts to determine the cellular groups in the network, which we will call them communities; the second uses ontologies for the semantic enrichment of the cellular communities. The measures used from the graph theory allow us to determine the set of cells that are close (for example, in a disease), and the main cells in each community. We analyze our approach in two cases: TGF-β and the Alzheimer Disease.