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A data collaboration model for collaborative design based on C-net Xin Gao, Wenhui Hu, Wei Ye, ZHANG Shi-kun School of Electronics Engineering and Computer Science, National Engineering Research Center for Software Engineering Key laboratory of High Confidence Software Technologies (Ministry of Education) Peking University Beijing, China gaoxin54@gmail.com Xuan Sun Key Lab of Universal Wireless Communications, MOE Wireless Network Lab Beijing University of Posts and Telecommunications Beijing, China E-mail: sunxuanbupt@gmail.com Abstract—Process modeling is the base of complex product collaborative design, and the requirements of data collaboration in collaborative design process challenge at the aspects of parameter flow, concurrency, multi-versioning, repeat design and so on. To specify the data collaboration between design processes based on parameters, this paper provides a dataflow-oriented process collaboration model based on C-net model. Through the analysis of the data collaboration between design processes, we conclude some process collaboration patterns, including level task interaction, concurrent task interaction and repeat task interaction. Then provide the structure descriptions for these patterns, and explain the application scenes of theses patterns in collaborative design. At last, define the collaborative unit for each pattern and describe the data collaboration mechanism of process collaboration patterns by their element and relationship. Keywords- collborative design; data collaboration; C-net I. INTRODUCTION In the process of complex product design, the way of collaborative product design and development is the advanced cooperation model, which organizes the distributed team into a group to develop the product collaboratively so as t o improve the efficiency of development [1]. Comparing to traditional product design process, collaborative design process has the features of concurrency, distribution, dynamism and collaboration. In workflow, collaborative design process mainly depends on data collaboration based on parameter exchange. So how to implement the modeling for data collaboration of design process effectively becomes an important research topic, and at the same time it presents critical challenge to workflow modeling, which includes following aspects: Support iteration of design process Support the expression of data flow and control flow Support data collaboration in different scope From these facts, we can see that collaborative design actually is the complex distributed parallel interaction process, which execute data collaboration mainly in the form of data exchange. So traditional control flow oriented business workflow can’t describe complex data relationship and data exchange process, and need to take the idea and method of science workflow which mainly focus on data flow. Comparing to business workflow, science workflow can describe complex process and large-scale data exchange and transformation. At the same time, traditional business workflow can’t deal with the alterations of process collaboration which are caused by the changeability of design requirements at runtime. Meanwhile science workflow support breakpoint setting, and iterative execution, which can improve the flexibility of data collaboration among processes. Based on these features of collaborative design workflow, this paper takes the advantage of business workflow and science workflow, expresses dataflow oriented, constraint, parallel and iterative execution by C-net model. Then conclude a set of process collaboration model by analyzing the features of collaborative design workflow. At last, provide the construction mechanism of collaboration model based on C-net, so that the data collaboration model for collaborative design can ensure the workflow based on this model to effectively implement data collaboration process. II. RELATED WORK A. Workflow modeling To the research of workflow modeling, currently there are still no uniform modeling standard. From current work, the modeling methods mainly include flow chart, state diagram, activity network, IDEF, ECAA, event driven process model, Petri net and so on. Among these modeling methods, Petri net is the most widely used modeling method [2]. To implement the parallel execution, collaboration and optimization between the workflows of related design teams, it needs to build the model which can reflect the relationships between upstream and downstream of design organizations, and process modeling is t he important base of parallel execution. Traditional Petri net can’t effectively support the expression of the combination of data flow and control flow, data collaboration, iterative execution. So C-net model which presents by doctor Yuan[3] is used in this paper to describe data collaboration among collaborative design workflows, 541
ecause the system of C-net model is qu antification structure which is similar with net system. “C” stands for computing and communication. C-net describes token and variable separately based on the basic principles of Petri net, so that C-net is suitable to describe collaborative design workflow. B. Collaboration mechanism description To the description of coarse collaboration mechanism, paper [4] integrates the branch of workflow and the object of software engineering into Petri net, and builds the invoking relationship, in which collaborate unit nets are collaborated around process net. Paper [5] presents a m ethod of multiworkflow interaction and coordination based on bus. The research direction of these works is t o build coarse collaboration mechanism to implement data translation and progress control among processes, but it can’t reflect the collaboration between tasks because its element is not task. To the description of fine grit collaboration mechanism, paper [6] presents the solution of workflow collaboration by combing agent technology with ontology. Paper [7] describes workflow based on Petri net, and uses an annotation language to describe data exchange and process schedule between processes. Both of these two works present the description of fine grit collaboration mechanism, but they use different modeling methods to describe the workflow and the collaboration mechanism between workflows. The inconsistency between workflow model and collaboration mechanism model brings complexity to analysis of the dynamic process data and execution state of workflow, and there are also some researches on the unified formalization of collaboration design process. Paper [8] uses Pi-Calculus technology to formally define the inter-organizational business process structure, and use the special mechanism of Pi- Calculus to describe parallel processes and their communication. But its problem is th at the process model based on Pi-Calculus is too complex and abstract to let designer understand the process and conduct the implementation of specific design process. Paper [9] provides a set process modeling mechanism of pub/sub system based on color net, which adopts Petri net model to describe pub component so as to realize process collaboration and only focus on the description of control flow. So according to the feature of collaborative design, it n eeds a k ind modeling method which can describe both design process and design collaboration of collaborative design by the data exchange of fine grit task level. The collaboration at task level asks for more requirements to process modeling, which mainly is reflected in the description of the process and collaboration between processes. III. DATA COLLABORATION DESCRIPTION OF COLLBORATIVE DESIGN Through C-net model, we can describe the basic process of dataflow oriented collaborative design, and we conclude three main process collaboration patterns in the scene of data collaboration between collaborative design processes. Then we use C-net to build model for process collaboration patterns. A. C-net model The formal definition of C-net is as follow: , , ; , , to stand for r C_netand xV,t T, p P. P, V and T separately stand for the token set, variable set and transition set of CN and F, R and Wr separately stand for flow relationship, read relationship and write relationship. Definition 1 Use CN PV T F RW It is critical to realize the communication between processes by the collaboration between tasks and support the description of parameters exchange between tasks and constraints between parameters in collaborative design. C-net support parameters passing of collaborative design, because C- net introduces variable set which can make some corresponding extensions so as to provide the description of data flow and control flow between design tasks. B. Data collaboration model of collaborative design According the features of collaborative design, including inter-organization, data flow oriented, parallel and iterative execution, we conclude three major parameter interaction patterns to describe the complex data collaboration between design processes, including task interaction between superior process and subordinate process, task interaction between parallel processes and task interaction between iterative processes. Pattern 1 : task interaction between superior process and subordinate process In this pattern, the relationship between superior process and subordinate process are reflected into parameter passing from one or more tasks of subordinate process to the task of superior process. This pattern often is used in the level structure to describe the interaction between the tasks which belong to the processes of different level. These interactions include the monitoring, collection, statistics and analysis of superior process to subordinate process, and the specific abstract process is as follow: Figure 1. Task interaction pattern between superior and subordinate process In figure 1, transition T strands for the task of superior process which implements the interaction with subordinate process. It shows that T collects parameters from T2, T3 and Ti. T2 T3 T Ti Tj Pattern 2 : task interaction between parallel processes In this pattern, the tasks of different parallel processes interact with each other based on parameters, which is reflected into two scenes: one is that some tasks can pass parameters to multi tasks from other parallel processes; the other is that some tasks can receive parameters from multi-tasks from other parallel processes. In collaborative design process, this pattern is mainly used to describe data collaboration process in the form of parameter which is c aused by the dependence of the design contents among different design teams. This pattern also describes the parameter interaction caused by multidisciplinary 542
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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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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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Cloud Application Resource Mapping
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An Empirical Study of Software Metr
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TABLE I SOFTWARE DATASETS CHARACTER
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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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Client-Side Rendering Mechanism: A
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JavaScript code directly within the
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[9] but no validation is provided i
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scribed by the equation: where η i
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such as one week and gradually dete
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Towards More Generic Aspect-Oriente
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Aspect-Orientation in the Developme
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Evaluating Open Source Reverse Engi
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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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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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subject also caused outliers for re
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Choosing licenses in free open sour
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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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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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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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contains broadcast of Subject to Ob
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level); in UML/J2EE technology [11]
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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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III.BUSINESS RULES FRAMEWORK FOR KN
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ensure users the trustworthiness of
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Patient Doctor Doctor Patient Direc
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Decidability of Minimal Supports of
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satisfies R( D) R( C) S 1. Compa
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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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High-level Petri net Place Place Ty
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verification and thus is often limi
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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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Ontology-based Representation of Si
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Automatic Generation of Architectur
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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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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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Objective Figure 4. Testing
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k v ( df i ) 0 , it means that the
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Structural Testing for Multithreade
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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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A Mapping Study on Software Product
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most relevant sources in software e
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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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contribution of each study was made
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assets, the plugin approach can be
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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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sub-dimension is categorized as, co
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A Proposal of Reference Architectur
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A Variability Management Method for
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means patterns which are shown in s
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Tool Support for Anomaly Detection
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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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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
Page 733 and 734:
Figure 2. Reordered layers of the k
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Automatic Acquisition of isA Relati
Page 737 and 738:
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
Page 743 and 744:
i.d. subsets of cubes focused on se
Page 745 and 746:
Match production rules Enterprise S
Page 747 and 748:
A Tool for Visualization of a Knowl
Page 749 and 750:
other ontology visualization tools
Page 751 and 752:
shown at Figure 5. Objectives are s
Page 753 and 754:
Rendering UML Activity Diagrams as
Page 755 and 756:
a = O1 → a → O2 b = O2 → b
Page 757 and 758:
ecordProblem → A → reproducePro
Page 759 and 760:
umlTUowl - A Both Generic and Vendo
Page 761 and 762:
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
Page 767 and 768:
III. GRAPH REPRESENTATION OF CLASS
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as an add-in to popular UML m odeli
Page 771 and 772:
742
Page 773 and 774:
744
Page 775 and 776:
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
Page 785 and 786:
756
Page 787 and 788:
758
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With the GDUC approach, we can mode
Page 791 and 792:
Figure 6. Three proposals containin
Page 793 and 794:
764
Page 795 and 796:
766
Page 797 and 798:
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
Page 811 and 812:
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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