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A Set of Inspection Techniques on Software Product Line Models Rafael Cunha Nokia <strong>Institute</strong> of Technology INdT Manaus, Brazil rafael.cunha@indt.org.br Eduardo Santana de Almeida Reuse in Software Engineering (RiSE) Universidade Federal da Bahia (UFBA) Salvador, Brazil esa@dcc.ufba.br Tayana Conte Grupo de Usabilidade e Engenharia de Software Universidade Federal do Amazonas (UFAM) Manaus, Brazil tayana@icomp.ufam.edu.br José Carlos Maldonado Departamento de Ciência da Computação Universidade de São Paulo (USP) São Carlos, Brazil jcmaldon@icmc.usp.br Abstract— Software Product Lines are an approach that enables organizations to develop a number of similar products in the same application domain reducing development and maintenance cost and increasing productivity. As in traditional software development approach, software product lines model need to be evaluated for improving software quality. This work proposes a set of inspection techniques, named SPLIT, for evaluating software product lines models. An in vitro experiment was conducted for comparing a defect type based inspection approach and the proposed set of techniques. Results indicated that our techniques found a greater number of defects than a defect type based inspection approach. Keywords-inspection technique; software product line; feature model; empirical study I. INTRODUCTION A Software Product Line (SPL) supports reusability by developing a set of products sharing a core com monalities and differing variabilities [1]. T hus, instead of in traditional software development where it usually models one product a time, it models a set of products. An essential reason for introducing product line engineering is cost reduction [2]. Since every product uses the same core features and some optional ones, it can be reused aiming in a cost reduction for each system. Although these artifacts can be reused, it is necessary investments for creating them planning the reuse mechanism, so that they are able to provide managed reuse. In a software product line, in general, the time to market indeed is initially higher, as the com mon artifacts have to be built first. H owever, it is considerably shortened as m any artifacts can be reused for each new product [2]. Software product lines need to address the same issues as in traditional software developmen t as inconsistencies betw een requirements and software specifications. One approach that is applied to traditional softw are development that im proves quality and reduces costs is inspection techniques, w hich is used to identify defects in ear ly stage of development [3]. Inspections of software design may be especially crucial since design defects can directly affect the quality of, and effort required for, the im plementation [3]. Because SPL models are quite different from single sy stem development, standard techniques are insufficient to address the specific characteristics of reusable systems [4], thus new inspection techniques tailored to the SPL models are needed. This scenario has m otivated one of our research’s goals: to define a set of inspection techniques, named SPLIT, tailored to support quality assurance concerned with specific models used for Software Product Lines specification. This paper proposes and validates, using a controlled experiment, a set of techniques to evaluate a feature model and a product map against software requirement document and feature model inconsistencies. We propose that our set of techniques find a greater number of defects than a defect type based inspection approach. The remainder of this paper is structured as follow s: Section 2 presents background information on Software Product Lines. Section 3 presents the set of inspection techniques, SPLIT, proposed for software product line specifications. In Section 4, the controlled experiment to evaluate the set of the proposed techniques is discussed in detail, including goals and experi mental design. In Section 5, the results are presented and discussed. Section 6 describes threats to the validity of our study. Finally, conclusions and comments on future work are given in Section 7. II. SOFTWARE PRODUCT LINE Software Product Lines are a set of software-intensive systems sharing a common, managed set of features that satisfy the specific needs of a particul ar market segment or mission and that are developed from a common set of core assets in a prescribed way [5]. The artifacts used in different products have to adaptable to fit each system created in the product line. 657
It means that throughout the development process, we have to identify and describe where the products created by the product line may differ in terms of the features they provide, the requirements they fulfill, or even in terms of the underlying architecture [5]. This flexibility is called variability and it is the basis for the software product line engineering since it represents the difference in each product produced by the Software Product Line. Different models have been proposed for specifying Software Product Line, features models proposed in Feature- Oriented Domain Analysis (FODA) approach [6] is one of the most used [7]. Product line scoping is also an important phase in product line engineering to d ecide not only what products to include in a product line but also whether or not an organization should launch the product line [8]. One approach for product line scoping is product m ap [9] for selecting a subset of products to be created by the product line . The inspection techniques proposed use feature models and product map. These m odels are further discussed in the following sections. A. Feature Models Feature models are hierarchi cal models that capture the commonality and variability of a Product Line. This feature - oriented concept is based on the emphasis placed by the method on identifying those featur es a user commonly expects in applications domain. The feature concept used for modeling the feature models is that it is a prom inent distinctive user-visible aspect, quality, or characteristic of software system [6]. The purpose of the feature model is to represent the general capabilities for the applications in the domain. Feature Models are created using m andatory, optional, alternatives and or features. The m andatory features represent the features, which must be c ontained in every product created by the product line. The optional features represents the features which can be contained or not in the prod uct from the SPL. Alternative features repres ent an alternative betw een two or more others features so th at only one of them must be contained in products from the SPL. And or features represent an alternative betw een two or m ore features in w hich at least one of them must be contained in the products from the SPL. The feature m odels also have constraints elem ents: implication and exclusion. Th e implication notation im plies that if one feature is selected , some other feature must be selected as well. The exclusion constraint indicates that two features must not be selected in the sam e product so they are mutually exclusive. B. Product Map The selection of optional or alternative features is not m ade arbitrarily. It is usually made based on a number of objective s or concerns that the end-user (and customer) has [6]. The product map [9] aims to complement the feature model by specifying the products, which are compliant with the software requirements. The product map lists all features available in the y-axis and the products specified by the requirements in the x-axis. Every product in the x-axis matches a list of features according to the software product line requirements. Then the software product line only creates the products specified in the requirements. III. SOFTWARE PRODUCT LINE INSPECTION TECHNIQUE A Software Product Line creates a set of products sharing common features and features which differs from product to product. Therefore, it is im portant to assure the quality of their models, as they specify several products. A mapping study [10] was conducted to obtain evidence about quality assurance techniques for SPL models. M apping studies [10] are a formal process that uses a methodology to identify all research related to a specific topic [10]. U nlike informal literature review s, mapping studies uses a scientific rigorous approach to assert an efficient survey of the current knowledge. The databases used for this mapping study were the IEEE Xplore, ACM Digital Library and Scopus. Our formal process, as well as all selected studies, is described in a Technical Report [11]. The initial search returned a total of 841 papers, as described in Table I. After the first filter, in w hich the title and abstract from the selected papers were analyzed, it has been filtered to 90 papers. In the second filter, it w as also analyzed the introduction and conclusion from papers selected after the first filter, resulting a total of 27 papers about quality assurance techniques for SPL models. The data extracted presented that 23 (85% ) papers used model checking techniques, 3 (11% ) used ontologies for modeling and model checking and code inspections were presented in 2 papers (7%). Although the benefits of inspection techniques [3] and the need for inspections tailored for SPL [4], no inspection technique for assuring quality for softw are product line models was identified [11]. TABLE I. Database PAPERS SELECTED IN THE MAPPING STUDY Papers returned for the 1 st filter Papers selected after the 1 st filter Papers selected after the 2 nd filter IEEE Xplore 88 22 5 ACM Digital Library 482 28 10 Scopus 271 40 12 We have proposed a set of checklist based techniques, named Software Product Line Inspection Techniques (SPLIT), for verifying feature models and product map in comparison with themselves and the software requirem ents specification. The software requirem ent specification needs to enum erate functional and non-functional requirem ents and the products created by the software product line and its constraints. An overview of SPLIT is presented in Figure 1: 658
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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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and the risk level. Existing assess
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diagram could give developers an in
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• Sensor(Lexical): at the top and
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An Overview of the RSLingo Approach
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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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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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VI. EXPERIMENTAL RESULTS The presen
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test duration(s) for the scenario(s
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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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Enforcing Contracts for Aspect-orie
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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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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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B. Trace Semantics of DAP Fig. 1. A
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transformation idea in MDA [13] . T
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executing a continuous transition,
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protocol of DATS we used is properl
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4.4. An Illustrative Example Now le
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Evolutionary Learning and Fuzzy Log
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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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esults. To be more specific, they w
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(a) Volatility (b) Complexity (c) R
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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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complete in zero-time, and thus hav
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figure assumes the experiment with
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III.BUSINESS RULES FRAMEWORK FOR KN
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stored. If event failure, external
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Patient Doctor Doctor Patient Direc
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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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eventually triggers a co mmon task.
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access control exists, the action i
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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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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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Figure 1. Figure 1 shows an overvie
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A Context Ontology Model for Pervas
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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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Model & Method Feasibility Evaluati
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Structural Testing for Multithreade
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derivation dependencies. The third
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model extension as proposed in [6].
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Figure 1. The process for engineeri
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way to detect something which could
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obtain the input of experts on desi
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A. Pattern Reuse In patterns reuse
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IV. SCATTER In order to enhance pat
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These latter would be clustered acc
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DC2AP Element and their Application
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(1) V □ (A) ⊆ V □ (B), V ♦
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Adaptive software should basically
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F. Step S6 - Monitor at Run-Time Th
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Figure 1, a metamodel defines an XM
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Figure 3 is a feature diagram that
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ecause the system of C-net model is
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Visual Studio Achievements, a Visua
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the project. This achievement has t
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proposed in this work requires the
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FTS is an important research area,
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C. Dependent Variables and Measures
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D. Conclusion Validity Conclusion v
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evaluation of team productivity, qu
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Figure 3: Process Fragment Example
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complexity issues traditionally inv
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Fig. 1: Swing Framework Class Diagr
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ize:Class”, with an empty precond
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Fig. 11: Overwritten Method Fig. 12
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Investigating the use of Bayesian n
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process for the network. Thus, this
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Reuse of Experiences Applied to Req
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Step 1: To start the process, the u
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Specification of Safety Critical Sy
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current belief of agents in order t
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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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Page 715 and 716: data dependencies required for keep
Page 717 and 718: Spacemaker: Practical Formal Synthe
Page 719 and 720: Fig. 1. The ecommerce object model.
Page 721 and 722: Fig. 3. Mapping diagram for Figure
Page 723 and 724: A formal support for incremental be
Page 725 and 726: machine may be empty which should l
Page 727 and 728: software, based on revised requirem
Page 729 and 730: A Process-Based Approach to Improvi
Page 731 and 732: Appropriate processes m ust support
Page 733 and 734: Figure 2. Reordered layers of the k
Page 735 and 736: 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
Page 765 and 766:
4) Associations: In the first test
Page 767 and 768:
III. GRAPH REPRESENTATION OF CLASS
Page 769 and 770:
as an add-in to popular UML m odeli
Page 771 and 772:
742
Page 773 and 774:
744
Page 775 and 776:
746
Page 777 and 778:
her necessities. However, the progr
Page 779 and 780:
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
Page 789 and 790:
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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