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Towards Autonomic Business Process Models Karolyne Oliveira, Jaelson Castro Centro de Informática Universidade Federal de Pernambuco Recife, Brazil {kmao, jbc}@cin.ufpe.br Abstract - In many organizations business process models (BPM) play a central role by capturing the way activities are performed. However, in the dynamic circumstances often encountered in today's business world, the processes are becoming increasingly complex and heterogeneous. Unfortunately, most of the current approaches to BPM are too inflexible and unresponsive to change. This calls for Autonomic Business Process (ABP) aimed at self-management and selfadaptation in dynamic environments. However, a key challenge is to keep the models understandable and scalable in increasingly complex scenarios. In our work we rely on the principle of separation of concerns and modularization in order to properly represent autonomic features in Business Process Models. We argue that Communication Analysis can help to indicate mission-critical activities that must be treated in autonomic manner. We outline a process that helps to define the granularity of the Business Process Models, indicating where the system needs to be instrumented. This novel approach provides four well-defined levels of abstraction: Communicational Level, Technological Level, Operational Level and Service Level. A real example is used to illustrate our proposal. Keywords - Business Process Modeling; Autonomic Computing; Self-Adaptation; Communication Analysis I. INTRODUCTION Analysts and researchers in Information Technology and Communication (ITC) management have forecasted an unavoidable collapse, imposed by the sheer scale and complexity of the new systems. Hence, complexity and size have driven ITC management to consider less human-dependent solutions, such as Autonomic Computing (AC), aimed at developing computer systems capable of self-management [1]. An autonomic system must know itself, be able to selfconfigure and recon figure when faced with unforeseen circumstances. Moreover, it s hould look for optimizations, to be able to self-heal as well as to self-recover from critical failures and protect itself. Hence, it must understand the environment and the context around the activities. In our work, we are co ncerned about the use of principles of autonomic computing in the management of business processes. Our goal is to help organizations to survive in d ynamics environments. More specifically we want to face an open challenge which is to promote Sergio España, Oscar Pastor Centro de Investigación en Métodos de Producción de Software Universitat Politècnica de València Valencia, Spain {sergio.espana, opastor}@pros.upv.es modularization and separation of concerns (SoC) in Autonomic Business Process Models [2]. The paper proposes a proce ss that exploits the high variability in service-oriented system environment by the use of contexts and autonomic adaptations by operationalizations of Non-Functional Requirements (NFR). In order to im prove modularity and promote the use of different levels of abstractions in Autonomic Business Process we investigate the use of Communication Analysis Principles. The benefits are manifold and include addressing scalability problems and improving the understandability of ABP in complex scenarios [3]. A MAPE cycle (Monitor-Analyze-Plan-Execute), was utilized considering both as pects: system (self) and t he instrumented BPM (context). In order t o illustrate our proposal we describe a real example which presents mission-critical activities often managed through BPM. In the next sections, we present concepts related to this work, our approach and conclusions respectively. II. BACKGROUND AND RELATED WORKS In this section, we introduce self-adaptation and the use of business process modeling as well some relevant work on using these models to provide autonomic computing characteristics to software. A. Autonomic Computing / Self-Adaptation Self-adaptive software is expected to fulfill its requirements at run-time in response to changes. This objective can be achieved through monitoring the software system (self) and its environment (context) to detect changes, make appropriate decisions, and act accordingly. Certain characteristics, known as self-* properties are expected: (i) Self-configuration; (ii) Self-healing; (iii) Self-optimizing; and, (iv) Self-Protecting [4], [5]. Figure 1 shows the hierarchy of the self-* properties according [6]. Figure 1. Hierarchy of the Self-* Properties, adapted from [6] 531
Adaptive software should basically determine when and where a change is required, how it can be changed, and what the impacts of a change are on system attributes. These dimensions (when, where, what, and how) are highlighted in the taxonomy of evolution [7]. When corresponds to temporal properties; Where refers to the object of change and describe which artifact needs to be chang ed; What relates to system properties (qualities attributes); How refers to change support (change models and the formality). We advocate the use of feedback control (or closed loop control)[8], as the mechanism to su pport autonomic characteristics into a busin ess process. We argue that selfadaptive software is a clo sed-loop system with feedback from the self and th e context. The Autonomic Computer System’s building block, n amed autonomic manager, constantly interacts with managed element in order t o maintain its equilibrium in face of incoming perturbations. The MAPE cycle (Monitor-Analyze-Plan-Execute), represented in Figure 2, is an implementation of the classical feedback control technique [4]. Figure 2. Monitor Analyzer Instrumented System Actuator Planner Closed Loop Control Mechanism In a service-based mission-critical system, adaptation is an activity with the objective of delivering an acceptable/guaranteed service based on SLA (Service Level Agreement). Basically, SLA is a service contract between a customer and a service provider that specifies t he forwarding service a custo mer should receive. One of the key components in SLA is SLO (Service Level Objective) which specifies QoS (Quality of Service) metrics governing service delivery. Each SLA may include several SLOs, each corresponding to a sin gle QoS parameter related to quality factors. An example SLO is keeping the end-to-end response time in a specific ran ge. For example, how a s ubstituted method, replaced using an aspect weaving/unweaving operation, will violate or sati sfy a co ndition on the system throughput [8]. In this paper, we claim that self-adaptive features must be aligned with Business Processes. B. Business Process Modeling and Autonomic Computing <strong>Systems</strong> Business Processes and Business Process Management (BPM) are essential in many modern enterprises. They constitute organizational and operational knowledge and often perpetuate independently of personnel and infrastructure change [9]. Autonomic Computing principles can be adapted to hel p organizations survive in dynamic business scenarios. Process that can be able to answer to AC principles are designated Autonomic Business Process (ABP) [10]. Autonomic Business Process (or autonomic workflow) must have the capability to adjust to environment variations (context). If one component service node (self) becomes unavailable, a m echanism is needed to ens ure a business process exec ution is not interrupted [11]. ABP differs from traditional workflow as it relie s on autonomic techniques to manage adjustments during its execution. Therefore, it enab les dynamic and auto matic configuration of its definition, activities and resources. It also allows selfoptimization and self-healing. Furthermore, autonomic workflow must have intelligence to anal yze situations and deduce adaptations at run-time. There is a b elief that self-* properties are related to software quality factors. For example, Salehie and Tahvildari discuss the potential links between these properties and quality factors [12]. We argue that in logical level of business process model the adaptations must result in qu ality attributes defined according NFR Framework [13]. In order to demonstrate such relationships, it is better to analyze how a well-known set of quality factors defined in the ISO 9126 -1 quality model [14] are lin ked to m ajor and prim itive self-* properties. Considering aspects discussed in [15], TABLE I presents a consolidation of NFR and Autonomic Computing Principles. TABLE I. NFR NFR AND AUTONOMIC COMPUTING PRINCIPLES Self- Configuring Maintainability X X Autonomic Computing Principles Self- Self- Healing Optimize Self- Protect Functionality X X X Portability Usability X X Realiability X X X Efficiency The benefits related to th e use of NFR joined with BPM have been acknowledged in the last years. NFRs have been applied to help in th e design of bu siness process models through extensions of business process modeling languages, allowing for richer analysis and operation alizations of the process model. However, many works do n ot consider the variability in their solutions [16]. On the other hand, the context of a b usiness process is the set o f environmental properties that affect business process execution. Therefore, these properties s hould be taken into account when designing a bu siness process. If context is analyzed when modeling a bu siness process, then identification of all its variants (relevant states of the world in which the business X 532
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SEKE San Francisco Bay July 1-3 201
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Copyright © 2012 by Knowledge Syst
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The 24 th International Conference
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Zhenyu Chen, Nanjing University, Ch
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Riccardo Martoglia, University of M
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Poster/Demo Sessions Co-Chairs Fars
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Evaluating the Cost-Effectiveness o
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Program Understanding Evaluating Op
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An Empirical Study of Execution-Dat
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Computer Forensics: Toward the Cons
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Modeling Bridging KDM and ASTM for
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A Mapping Study on Software Product
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A proposal for the improvement of t
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Panel on Future Trends of Software
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een available for analysis. Social
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The rest of this paper is orga nize
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Now we assume is given, we first pr
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“iphone” and “blackberry” a
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nique estimate the impact set based
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Figure 1. An example to illustrate
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trategy, the results should support
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Figure 1. System Architecture would
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Figure 2. Sequence Diagram of Train
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deployed on Android phone and runs
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the ontology information is only us
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Both kinds of axioms lead to an inh
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engineer and achieving requirements
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elicitation and the act ivities con
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Step 2. Step 3. 1.2. Use of Procedu
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Figure 6.b. Task: Cognitive Analysi
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original User’s Discourse / Speec
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II. RELATED WORK Business processes
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test, we did not find any significa
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For the indicator “requirements a
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the model checkers SPIN [8] and NuS
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allow for the presentation of syste
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the requirement or design phases sh
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using the CR estimates against the
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Data Set TABLE II. DATA SETS Artifa
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Figure 4. Relative Error in the Est
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Take basic requirements from user a
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sent Semantic Web Ontologies. It co
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The rest of the paper is organized
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and the risk level. Existing assess
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diagram could give developers an in
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Figure 2. Co
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• Sensor(Lexical): at the top and
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An Overview of the RSLingo Approach
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Figure 2. Overview of the RSLingo a
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DETECTING EMERGENT BEHAVIOR IN DIST
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Definition 2: For a set of MSCs M,
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Stability of Filter-Based Feature S
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Algorithm 1: Threshold-Based Featur
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MI KS GM AUC PRC S2N RUS35 RUS50 RO
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80
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Cloud Application Resource Mapping
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Fig. 1. UML Collaboration Diagram m
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Fig. 2. UML Activity Diagram modeli
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An Empirical Study of Software Metr
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TABLE I SOFTWARE DATASETS CHARACTER
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1) Classifiers: In this study, soft
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Progressive Clustering with Learned
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IV. DATA SOURCES We have been worki
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meta-data we assign to indicate sig
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Multi-Objective Optimization of Fuz
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uilding FNNs that satisfy different
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VI. EXPERIMENTAL RESULTS The presen
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Generating Performance Test Scripts
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test duration(s) for the scenario(s
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which are composed by the name and
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A Catalog of Patterns for Concept L
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assisted solution for lattice analy
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The complete lattice of the class s
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Client-Side Rendering Mechanism: A
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JavaScript code directly within the
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Fig. 6. CPU usage percentage of pre
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may introduce the extra learning cu
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[9] but no validation is provided i
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One of the st udents from Group B t
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scribed by the equation: where η i
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4 Model Checking DPN We use HyTech
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Recommender systems are usually cla
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such as one week and gradually dete
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•
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146
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Enforcing Contracts for Aspect-orie
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Table 1. Behavioral Rules in LSD [9
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1 public privileged aspect Update {
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Towards More Generic Aspect-Oriente
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vals must be denoted by some notion
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Aspect-Orientation in the Developme
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Table II SELECTED PRIMARY STUDIES #
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Evaluating Open Source Reverse Engi
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Table 1. Candidate reverse engineer
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Some tools may perform the needed f
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Coordination Model to Support Visua
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this CMV approach we employee three
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colored according to the Gradient T
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Improving Program Comprehension in
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The method used to support and eval
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
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An Approach for Software Component
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properties. In particular, the foll
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Conference Dataset Anatomy Dataset
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equipment maintenance node may cont
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Online Anomaly Detection for Compon
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B. Monitoring Static Method Invocat
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undle which is responsible for pars
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An Exploratory Study of One-Use and
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Figure 1. Mindmap of Reuse Design P
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subject also caused outliers for re
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Choosing licenses in free open sour
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The important aspect is to provide
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that holds a model of each software
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Online Probability Application Char
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TABLE II THE PARAMETERS FOR THE HAR
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[10] N. Gunther, “Hit-and-run tac
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Section 5 d iscusses some related w
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model and the analysis results. The
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tree view of UML model, as show in
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II. BACKGROUND In this section, we
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Algorithm 2 MarkStatements function
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(a) printtok (b) printtok2 (c) sche
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Gupta extended HGS and proposed the
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manage intellectual knowledge with
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D. Manage Training When any trainin
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TABLE II. COMPARISON BETWEEN THE EX
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B. Trace Semantics of DAP Fig. 1. A
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∀ [DR ′ ] []gen [; ] [D]□ [;
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transformation idea in MDA [13] . T
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MappingRule MappingTGtoHP { [Rule I
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executing a continuous transition,
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protocol of DATS we used is properl
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in Boolean search and reasoning has
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to be broken by expelling one of it
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where, among other things: 1. The t
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A never-ending language learner cal
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4. i 2 Learning(DEC, mex) via Bias
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4.4. An Illustrative Example Now le
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Evolutionary Learning and Fuzzy Log
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In addition to the rules, the knowl
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As described in the previous sectio
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the ontology hierarchy; learning a
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three different learning techniques
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TABLE IX. USING SVM FOR LEARNING tr
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Siemens set contains seven C progra
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The program tcas is not included be
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esults. To be more specific, they w
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According to IEEE [10], regression
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(a) Volatility (b) Complexity (c) R
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It mimics the test engineer knowled
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integrate the test results. • Aut
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No tify the cloud controller to get
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of execution-data classification. T
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Figure 1. Boxplots of average AUC r
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anches is more applicable than the
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To validate the proposed approach,
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contains broadcast of Subject to Ob
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S 1a=1; S 2b=5; cobegin { S 3read
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.
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298
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A functionality is the ability of a
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level); in UML/J2EE technology [11]
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• to provide a unified catalogue
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flexibility they provide to model s
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complete in zero-time, and thus hav
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figure assumes the experiment with
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could be a practical way of dealing
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and (iv) the reduced amount of line
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III.BUSINESS RULES FRAMEWORK FOR KN
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explanation for why the program wan
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A model introducing SOAs quality at
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there exist a hierarchical ranking
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Software as a Service: Undo Hernán
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operations consist in reinjection i
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stored. If event failure, external
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ensure users the trustworthiness of
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Patient Doctor Doctor Patient Direc
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going down at a time. This is a rea
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Decidability of Minimal Supports of
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A S 1 1 1 0 0 0 1 1 0 0 0 1 1
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satisfies R( D) R( C) S 1. Compa
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Automated Generation of Concurrent
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target of testing. A blackbox test
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sequence. Each t i θ i in the firi
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SAMAT -AToolforSoftware Architectur
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Figure 4. The SAM Hierarchical Mode
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High-level Petri net Place Place Ty
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verification and thus is often limi
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(r 1 r 2 ...r k ) 1 denotes Path [r
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Fig. 3. Example a 3-compound weakly
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necessary before verification. In t
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CTL formula as: AG (( jp EX( jp ad
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equirements level, like EA-Miner [1
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II. RESOURCE-ORIENTED WORKFLOW MODE
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eventually triggers a co mmon task.
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Input: A resource oriented workflow
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access control exists, the action i
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(ACCDA), is customized to address a
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ICrudSchema and shown in Figure 3.
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Connectors for Secure Software Arch
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Non-repudiation security service pr
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anAsynchronousCustomer InterfaceCon
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How Social Network APIs Have Ended
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OSN Social Feed Unique Features Con
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users can control the reach of thei
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Computer Forensics: Toward the Cons
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In 2009, Cohen et al. in [4] have o
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dcterms:contributor, dcterms:creato
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A Holistic Approach to Software Tra
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Figure 1. Figure 1 shows an overvie
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B. Case study in a proprietary proj
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Pointcut Design with AODL Saqib iqb
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system attributes, methods and exec
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Feature modeling and Verification b
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hasOptionalPart hasPart hasMandato
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A Context Ontology Model for Pervas
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Figure 1. UML view of the model. Th
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Figure 3. Architecture for deliveri
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Ontology-based Representation of Si
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Figure 2. Upper Ontology fragment f
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I2Sim simulation model was transfor
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An ontology-based approach for stor
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fying the equivalences between conc
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• Homonymy conflicts: occur when
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Automatic Generation of Architectur
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we dealt w ith the verticals rules.
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Towards Architectural Evolution thr
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different from replacing it, we dec
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Using FCA-based Change Impact Analy
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Table 2. Impact set of C1,C2,C5 cha
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Figure 3. The PF and PTS results fo
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Forecasting Fault Events in Power D
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which the airport data did not cont
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classified. Recall is the probabili
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Testing Interoperability Security P
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Figure 2. Overview of the Test Gene
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Objective Figure 4. Testing
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A New Approach to Evaluate Path Fea
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k v ( df i ) 0 , it means that the
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Model & Method Feasibility Evaluati
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Structural Testing for Multithreade
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adequate to another criterion. This
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Using the Results from a Systematic
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obtained from the categorization of
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that automatically presents the usa
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Improving a Web Usability Inspectio
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Following the experimental methodol
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About the category “Improvements
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Identification Guidelines for the D
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created according to the preview re
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In our analysis, the “Government
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In the following, we present the re
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USE SCENARIO The application Vuelos
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[8] Mayhew, D., “The Usability En
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Interaction State Set Structure Dat
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B. Component Model Fig. 2 show s th
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As a continuation of our research w
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PROMETHEE methods [3] belong to a f
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comparison rule, a value of 1/9 is
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TABLE V: Supermatrix for the exampl
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for knowledge sharing. Based on str
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y applying hash functions to its su
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Empirical Validation of Variability
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III. EXPERIMENTAL STUDY In this sec
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Table III SPEARMAN’S CORRELATION
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A Mapping Study on Software Product
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most relevant sources in software e
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TABLE IV TOOL’S CLASSIFICATION AC
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[2] P. Clements and L. Northrop, So
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and future works. II. BACKGROUND ON
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System Advanced Standard Module A M
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Algorithm 1: Backtracking for MIN-A
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outcomes from such research fields,
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TABLE IV. CONTINUED FROM PREVIOUS P
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contribution of each study was made
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assets, the plugin approach can be
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Figure 3: PlugSPL Feature Model Edi
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contributions from the several acto
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o Guideline 6.4: Softgoal dependenc
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descriptions must also b e configur
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It means that throughout the develo
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B. Instrumentation The experiment w
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• External Validity: W e have con
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II. THE PROPOSED TAXONOMY The taxon
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sub-dimension is categorized as, co
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A Proposal of Reference Architectur
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Figure. 1. Reference Architecture M
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A Variability Management Method for
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C. Correctness of configuration fil
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means patterns which are shown in s
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Tool Support for Anomaly Detection
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Figure 1. System overview of the SD
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Once the datasets were evaluated us
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Reconfiguration of Robot Applicatio
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data dependencies required for keep
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Spacemaker: Practical Formal Synthe
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Fig. 1. The ecommerce object model.
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Fig. 3. Mapping diagram for Figure
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A formal support for incremental be
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machine may be empty which should l
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software, based on revised requirem
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A Process-Based Approach to Improvi
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Appropriate processes m ust support
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Figure 2. Reordered layers of the k
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Automatic Acquisition of isA Relati
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III. VALIDATING THE DIMENSION HEADE
Page 739 and 740:
The table title and the dimension s
Page 741 and 742:
A light weight alternative for OLAP
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i.d. subsets of cubes focused on se
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Match production rules Enterprise S
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A Tool for Visualization of a Knowl
Page 749 and 750:
other ontology visualization tools
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shown at Figure 5. Objectives are s
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Rendering UML Activity Diagrams as
Page 755 and 756:
a = O1 → a → O2 b = O2 → b
Page 757 and 758:
ecordProblem → A → reproducePro
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umlTUowl - A Both Generic and Vendo
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The tool’s ability to deal with S
Page 763 and 764:
Elem. UML Example D 12 Harmonizing
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4) Associations: In the first test
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III. GRAPH REPRESENTATION OF CLASS
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as an add-in to popular UML m odeli
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742
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744
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746
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her necessities. However, the progr
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Figure 3. Global Log. of terms. The
Page 781 and 782:
two stages. The first stage is focu
Page 783 and 784:
754
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756
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758
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With the GDUC approach, we can mode
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Figure 6. Three proposals containin
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764
Page 795 and 796:
766
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Proactive Two Way Mobile Advertisem
Page 799 and 800:
information. If more than one adver
Page 801 and 802:
Users can al so publish adv ertisem
Page 803 and 804:
The COIN Platform: Supporting the M
Page 805 and 806:
A-3
Page 807 and 808:
Checking Contracts for AOP using XP
Page 809 and 810:
Maicon B. da Silveira, 112 Aldo Dag
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Seyedehmehrnaz Mireslami, 70 Takao
Page 813 and 814:
Wei Zhang, 422 Wenbo Zhang, 188 Zhi
Page 815 and 816:
Desmond Greer Eric Gregoire Christi
Page 817 and 818:
Poster/Demo Presenter’s Index A A
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SEKE 2012 Proceedings - Knowledge Systems Institute

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