Inferring software behavioral models with mapreduce pdf

Characterization of Randomized Shuffle and Sort

inferring software behavioral models with mapreduce pdf

Simultaneous Inference of Places Activities and. Automatic Steering of Behavioral Model Inference produces useful information that describes the behavior of software systems. We can use traces to automatically in-fer baseline models that can help software engineers under-stand, verify and validate software systems [11]. For exam- ple, we can trace inter-component method calls, and use the recorded traces to derive models that summarize, Read the latest articles of Science of Computer Programming at ScienceDirect.com, Elsevier’s leading platform of peer-reviewed scholarly literature.

Ke Zhai

Representing and Inferring Dermatologists Perceptual Skill. Probabilistic inference in this model yields user-specific distribution over interests. As user interests change over time, our model learns interests using online learning in which the prior distribution over interests at every time step is updated using a linear function of prior and poste-rior distributions at the previous time step. Exact inference in our model is intractable and, 1 A Review of Time Critical Decision Making Models and Human Cognitive Processes Ron Azuma, Mike Daily, Chris Furmanski HRL Laboratories, LLC 3011 Malibu Canyon Rd..

Probabilistic inference in this model yields user-specific distribution over interests. As user interests change over time, our model learns interests using online learning in which the prior distribution over interests at every time step is updated using a linear function of prior and poste-rior distributions at the previous time step. Exact inference in our model is intractable and ioral, resource-aware models of software systems from logs of their executions. These finite state machine models ease understanding of system behavior and resource use. Perfume improves on the state of the art in model inference by differentiating behaviorally similar executions that differ in resource consumption. For example, Perfume separates otherwise identical requests that hit a cache

BayesSDT: Software for Bayesian inference with signal detection theory MICHAEL D. LEE University of California, Irvine, California This article describes and demonstrates the BayesSDT MATLAB-based software package for performing Bayesian analysis with equal-variance Gaussian signal detection theory (SDT). The software uses WinBUGS to draw samples from the posterior distribution of six SDT Behavior models play an crucial role in the traditional engineering of software-based systems; it is the basis for systematic approaches to design, simulation, code

Mining Precise Performance-Aware Behavioral Models from Existing Instrumentation Tony Ohmann Kevin Thai Ivan Beschastnikh Yuriy Brun University of Massachusetts Facebook Inc. University of … Software Composition Using Behavioral Models of Design Patterns OPEN ACCESS JSEA 105 niques for software composition. In Section 3, we lay out the conceptual background needed to …

mimicking the behavior of the defense mechanism can greatly limit the protection they provide. Overall, our work presents a novel methodology geared to evaluate membership inference on aggregate location data in real-world settings and can be used by providers to assess the quality of privacy protection before data release or by regulators to detect violations. I. INTRODUCTION The ability to Bayesian Capture-Recapture Analysis and Model Selection Allowing for Heterogeneity and Behavioral Effects Sujit K. Ghosh∗ James L. Norris† Institute of Statistics Mimeo Series# 2562

Read "Behavioral resource-aware model inference" on DeepDyve, the largest online rental service for scholarly research with thousands of academic publications available at your fingertips. Automatic Steering of Behavioral Model Inference produces useful information that describes the behavior of software systems. We can use traces to automatically in-fer baseline models that can help software engineers under-stand, verify and validate software systems [11]. For exam- ple, we can trace inter-component method calls, and use the recorded traces to derive models that summarize

Editorial Article Mathews Journal of Dermatology Representing and Inferring Dermatologists Perceptual Skill Based on Computational Behavioral Models Many testing and analysis techniques use finite state models to validate and verify the quality of software systems. Since the specification of such models is complex and time-consuming, researchers defined several techniques to extract finite state models from code and traces.

Bugs as Deviant Behavior: A General Approach to Inferring Errors in Systems Code Dawson Engler, David Yu Chen, Seth Hallem, Andy Chou, and Benjamin Chelf Automatic Diagnosis of Software Functional Faults by Means of Inferred Behavioral Models PhD Dissertation by: Fabrizio Pastore Advisors: Prof. Mauro Pezzè Dott. Leonardo Mariani Supervisor of the Ph.D. Program: Prof. Stefania Bandini Università degli Studi di Milano Bicocca Dipartimento di Informatica, Sistemistica e Comunicazione Dottorato di Ricerca in Informatica XXII edition. to me, …

Automatic Steering of Behavioral Model Inference produces useful information that describes the behavior of software systems. We can use traces to automatically in-fer baseline models that can help software engineers under-stand, verify and validate software systems [11]. For exam- ple, we can trace inter-component method calls, and use the recorded traces to derive models that summarize Design Software Using behavioral models to drive RF design and verify system performance T oday’s wireless communications systems are built by multidisciplinary teams. The overall system behavior is the responsibility of the system architect. Implementing each part into disparate target technologies, such as real-time software, digital hardware and RF circuits, involves several …

Characterization of Randomized Shuffle and Sort

inferring software behavioral models with mapreduce pdf

Knock Knock Who’s There? Membership Inference on. Towards inferring environment models for control functions from recorded signal data. 1st Int. Workshop on Validating Software Tests (VST 2016) at SANER 2016. [PDF] Sofia Cassel, Falk Howar, Bengt Jonsson, Bernhard Steffen., Behavioral Log Analysis with Statistical Guarantees Nimrod Busany Shahar Maoz School of Computer Science Tel Aviv University, Israel ABSTRACT Scalability is a major challenge for existing behavioral ….

STRUCTURAL BEHAVIORAL AND FUNCTIONAL MODELING OF. Software Composition Using Behavioral Models of Design Patterns OPEN ACCESS JSEA 105 niques for software composition. In Section 3, we lay out the conceptual background needed to …, Editorial Article Mathews Journal of Dermatology Representing and Inferring Dermatologists Perceptual Skill Based on Computational Behavioral Models.

Knock Knock Who’s There? Membership Inference on

inferring software behavioral models with mapreduce pdf

A Knowledge-Based Method for Inferring Semantic Concepts. Model inference is a promising approach to tackle this problem by using machine learning to infer software behavior models automatically from execution logs , , . Many model inference algorithms [4] , [5] , [6] have been proposed by recent research. > Launched in 2000 using compatibility models > Available in United States, Canada, Behavioral . 6 Model Creation Research Matches Matching Models Process Scorer Scores User Attributes . 7 Matching Research Matches Matching Models Process Scorer Scores User Attributes . 8 Predicative Model Scores Research Matches Matching Models Process Scorer Scores User Attributes . 9 ….

inferring software behavioral models with mapreduce pdf


Software Composition Using Behavioral Models of Design Patterns OPEN ACCESS JSEA 105 niques for software composition. In Section 3, we lay out the conceptual background needed to … We describe Perfume, an automated approach for inferring behavioral, resource-aware models of software systems from logs of their executions. These finite state machine models ease understanding of system behavior and resource use.

We describe Perfume, an automated approach for inferring behavioral, resource-aware models of software systems from logs of their executions. These finite state machine models ease understanding of system behavior and resource use. We describe Perfume, an automated approach for inferring behav-ioral, resource-aware models of software systems from logs of their executions. These finite state machine models ease understanding of system behavior and resource use. Perfume improves on the state of the art in model inference by differentiating behaviorally similar executions that differ in resource consumption. For example

Abstract. What a group actually accomplishes depends on the nature of its task, the relevant resources of the members, the motivations of members, and the coordination patterns developed as the group proceeds with its work. Inferring High-Level Behavior from Low-Level Sensors Donald J. Patterson, Lin Liao, Dieter Fox, and Henry Kautz University Of Washington, Department of Computer Science and Engineering,

inferring software behavioral models with mapreduce pdf

Many testing and analysis techniques use finite state models to validate and verify the quality of software systems. Since the specification of such models is complex and time-consuming, researchers defined several techniques to extract finite state models from code and traces. 17 Responses to “Known applications of MapReduce” Winning with Data: Aster Data Systems Blog » Blog Archive » Leveraging In-Database MapReduce on August 26th, 2008 1:44 am […] the sky is really the limit for anyone to build powerful analytic apps.

Describing Synthesizable RTL in SystemCв„ў Scarpaz

inferring software behavioral models with mapreduce pdf

Home falkhowar.de. software engineer, who defines the modeling language, allowing domain experts to build the necessary models in the domain, while model interpreters whose development is facilitated by the GME environment completely automate the process of generating simulation models., This book constitutes the refereed proceedings of the First International Symposium on Dependable Software Engineering: Theories, Tools, and Applications, SETTA 2015, ….

Inferring meta-models for runtime system data from the

Discovering models of software processes from event-based data. Automatic Diagnosis of Software Functional Faults by Means of Inferred Behavioral Models PhD Dissertation by: Fabrizio Pastore Advisors: Prof. Mauro Pezzè Dott. Leonardo Mariani Supervisor of the Ph.D. Program: Prof. Stefania Bandini Università degli Studi di Milano Bicocca Dipartimento di Informatica, Sistemistica e Comunicazione Dottorato di Ricerca in Informatica XXII edition. to me, …, Mining Precise Performance-Aware Behavioral Models from Existing Instrumentation Tony Ohmann Kevin Thai Ivan Beschastnikh Yuriy Brun University of Massachusetts Facebook Inc. University of ….

for Advanced Study in the Behavioral Sciences (through the National Science Foundation), and the REGRESSION MODELS WITH ORDINAL VARIABLES 513 1980). These methods, however, while elegant and well grounded in statistical theory, are dif- ficult to use in the cases where regression analysis and its extensions would otherwise apply: that is, where data are nontabular; in- clude … Automatic Steering of Behavioral Model Inference produces useful information that describes the behavior of software systems. We can use traces to automatically in-fer baseline models that can help software engineers under-stand, verify and validate software systems [11]. For exam- ple, we can trace inter-component method calls, and use the recorded traces to derive models that summarize

Inferring High-Level Behavior from Low-Level Sensors Donald J. Patterson, Lin Liao, Dieter Fox, and Henry Kautz University Of Washington, Department of Computer Science and Engineering, Concurrent systems are notoriously difficult to debug and understand. A common way of gaining insight into system behavior is to inspect execution logs and documentation. Unfortunately, manual inspection of logs is an arduous process, and documentation is often incomplete and out of sync with the

17 Responses to “Known applications of MapReduce” Winning with Data: Aster Data Systems Blog » Blog Archive » Leveraging In-Database MapReduce on August 26th, 2008 1:44 am […] the sky is really the limit for anyone to build powerful analytic apps. Bugs as Deviant Behavior: A General Approach to Inferring Errors in Systems Code Dawson Engler, David Yu Chen, Seth Hallem, Andy Chou, and Benjamin Chelf

Paper 7200-2016 . Bayesian Inference for Gaussian Semiparametric Multilevel Models . Jason Bentley, The University of Sydney, New South Wales, Australia ioral, resource-aware models of software systems from logs of their executions. These п¬Ѓnite state machine models ease understanding of system behavior and resource use. Perfume improves on the state of the art in model inference by differentiating behaviorally similar executions that differ in resource consumption. For example, Perfume separates otherwise identical requests that hit a cache

BayesSDT: Software for Bayesian inference with signal detection theory MICHAEL D. LEE University of California, Irvine, California This article describes and demonstrates the BayesSDT MATLAB-based software package for performing Bayesian analysis with equal-variance Gaussian signal detection theory (SDT). The software uses WinBUGS to draw samples from the posterior distribution of six SDT One approach to tackle this problem is automatically inferring software models from execution logs. However, real-world software systems often produce large amount of logs. In this project, I combined formal methods with modern parallel data processing techniques, and used MapReduce to tackle the problem of inferring software behavioral models from large logs.

Testability Metrics for Software Behavioral Models 1173 3. Preliminaries In this section, we give some preliminaries of software behavioral models to help establish some relevant testability indicators. RAMS and BlackSheep: Inferring white-box application behavior using black-box techniques Jiaqi Tan, Priya Narasimhan CMU-PDL-08-103 May 2008 Parallel Data Laboratory

RAMS and BlackSheep: Inferring white-box application behavior using black-box techniques Jiaqi Tan, Priya Narasimhan CMU-PDL-08-103 May 2008 Parallel Data Laboratory Abstract: An important problem for HCI researchers is to estimate the parameter values of a cognitive model from behavioral data. This is a difficult problem, because of the substantial complexity and variety in human behavioral strategies.

Using Dynamic Execution Traces and Program Invariants to Enhance Behavioral Model Inference Ivo Krkay, Yuriy Brunx, Daniel Popescuy, Joshua Garciay, and Nenad Medvidovic y Concurrent systems are notoriously difficult to debug and understand. A common way of gaining insight into system behavior is to inspect execution logs and documentation. Unfortunately, manual inspection of logs is an arduous process, and documentation is often incomplete and out of sync with the

Hadoop: A Framework for Data-Intensive Distributed Computing CS561-Spring 2012 WPI, Mohamed Y. Eltabakh 1 . What is Hadoop? • Hadoop is a software framework for distributed processing of large datasets across large clusters of computers • Hadoop is open-source implementation for Google MapReduce • Hadoop is based on a simple programming model called MapReduce • Hadoop is … With the parallel data processing capacity of MapReduce, the problem of inferring behavioral models from large logs can be efficiently solved. The technique is implemented on top of Hadoop. Experiments on Amazon clusters show efficiency and scalability of our approach.

Inferring User Interests From Microblogs microsoft.com

inferring software behavioral models with mapreduce pdf

Using Simulation Methods for Bayesian Econometric Models. Discovering Program’s Behavioral Patterns by Inferring Graph-Grammars from Execution Traces Chunying Zhao 1, Keven Ates 1, Jun Kong 2, Kang Zhang 1, The MapReduce programming model MapReduce is a framework for parallel and distributed process- ing of batch jobs [11]. Each job consists of two phases: a map and a reduce. The mapping phase partitions the input data by associating each element with a key. The reduce phase processes each parti- tion independently. All data is processed as a set of key/value pairs: the map function ….

Science of Computer Programming Vol 145 Pages 1-36 (1

inferring software behavioral models with mapreduce pdf

Describing Synthesizable RTL in SystemC™ Scarpaz. Software developers, however, often use graphs to illustrate the process of program executions, such as UML diagrams, flowcharts and call graphs. Taking advantage of graphs’ expressiveness and intuitiveness for human cognition, we present a graph-grammar induction approach to discovering program’s behavioral patterns by analyzing execution traces represented in graphs. Moreover, to … software behavior and synthesizes executable software from those models. As with any successful engineering discipline, design techniques must evolve to support development, maintenance, and evolution of designs, and these techniques must be able to handle designs of realistic size and complexity. The discipline of software engineering provides techniques, such as object-oriented ….

inferring software behavioral models with mapreduce pdf


software behavior and synthesizes executable software from those models. As with any successful engineering discipline, design techniques must evolve to support development, maintenance, and evolution of designs, and these techniques must be able to handle designs of realistic size and complexity. The discipline of software engineering provides techniques, such as object-oriented … Abstract. What a group actually accomplishes depends on the nature of its task, the relevant resources of the members, the motivations of members, and the coordination patterns developed as the group proceeds with its work.

Abstract: An important problem for HCI researchers is to estimate the parameter values of a cognitive model from behavioral data. This is a difficult problem, because of the substantial complexity and variety in human behavioral strategies. Using Dynamic Execution Traces and Program Invariants to Enhance Behavioral Model Inference Ivo Krkay, Yuriy Brunx, Daniel Popescuy, Joshua Garciay, and Nenad Medvidovic y

Design Software Using behavioral models to drive RF design and verify system performance T oday’s wireless communications systems are built by multidisciplinary teams. The overall system behavior is the responsibility of the system architect. Implementing each part into disparate target technologies, such as real-time software, digital hardware and RF circuits, involves several … ioral, resource-aware models of software systems from logs of their executions. These finite state machine models ease understanding of system behavior and resource use. Perfume improves on the state of the art in model inference by differentiating behaviorally similar executions that differ in resource consumption. For example, Perfume separates otherwise identical requests that hit a cache

software behavior and synthesizes executable software from those models. As with any successful engineering discipline, design techniques must evolve to support development, maintenance, and evolution of designs, and these techniques must be able to handle designs of realistic size and complexity. The discipline of software engineering provides techniques, such as object-oriented … Concurrent systems are notoriously difficult to debug and understand. A common way of gaining insight into system behavior is to inspect execution logs and documentation. Unfortunately, manual inspection of logs is an arduous process, and documentation is often incomplete and out of sync with the

inferring software behavioral models with mapreduce pdf

software engineer, who defines the modeling language, allowing domain experts to build the necessary models in the domain, while model interpreters whose development is facilitated by the GME environment completely automate the process of generating simulation models. > Launched in 2000 using compatibility models > Available in United States, Canada, Behavioral . 6 Model Creation Research Matches Matching Models Process Scorer Scores User Attributes . 7 Matching Research Matches Matching Models Process Scorer Scores User Attributes . 8 Predicative Model Scores Research Matches Matching Models Process Scorer Scores User Attributes . 9 …