DOCSLIB.ORG

Mapping SPL Feature Models to a Relational Database

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Mapping SPL Feature Models to a Relational Database Mapping SPL Feature Models to a Relational Database Hazim Shatnawi∗ H. Conrad Cunningham University of Mississippi University of Mississippi Department of Computer and Information Science Department of Computer and Information Science University, Mississippi 38677 University, Mississippi 38677 [email protected] [email protected] ABSTRACT may vary in how those features are realized. To identify these com- Building a software product line (SPL) is a systematic strategy for monalities and variabilities, developers must analyze the domain reusing software within a family of related systems from some ap- to identify the organization’s business goals, the SPL’s scope, the plication domain. To dene an SPL, domain analysts must identify types of products to be developed, and the features of those prod- the common and variable aspects of systems in the family and cap- ucts. They often document the details of the feature analysis as a ture this information so that it can be used eectively to construct tree-structured feature model. A parent node represents a decision specic products. Often analysts record this information using a fea- in the design of a product. The children of that node represent more ture model expressed visually as a feature diagram. The overall goal detailed decisions for realizing the parent decision. The constraints of this project is to enable wider use of SPLs by identifying relevant among the nodes determine how valid products can be congured concepts, dening systematic methods, and developing practical in the SPL. tools that leverage familiar web programming technologies. This Feature models are represented in various ways in the litera- paper presents a novel approach to specication of feature models: ture. These include the FODA feature diagram [18] and several capture the details using automatically generated user interfaces, extensions [8, 12, 13, 16, 19, 27], special purpose languages [17, 33], encode the models in a relational database, and then validate the and formal models [4, 31]. However, these have one or more short- models and construct specic products using SQL. comings: some do not support automated analysis of SPLs or spe- cic product congurations; some focus on specic programming KEYWORDS languages; and some require the mastery of language, logic, or algebraic concepts unfamiliar to many programmers. Software product line, feature model, relational database, domain The overall goal of this project is to enable wider use of SPLs analysis, domain design, feature selection. by identifying relevant concepts, dening systematic methods, and ACM Reference format: developing practical tools that leverage familiar web programming Hazim Shatnawi and H. Conrad Cunningham. 2017. Mapping SPL Feature technologies. In Section 5, we present a novel approach to speci- Models to a Relational Database. In Proceedings of ACM SouthEast Conference, cation of feature models: encoding them in a relational database Kennesaw, GA, USA, April 2017 (ACMSE‘17), 8 pages. (RDB). An RDB separates the concept of a feature from its actual im- DOI: 10.475/123_4 plementation, which helps developers and clients to understand the feature model. We leverage the capabilities of the database query 1 INTRODUCTION language (SQL) to extract information about features and their re- Four decades ago Parnas observed that “software will inevitably lationships to validate the model and construct specic products. exist in many versions” [23]. Thus, a “software designer should be The database design also enables our tool to generate a web-based aware that he is not designing a single program but a family of user interface for product conguration. programs” [24]. He describes a software family as a set “of programs Before we present our approach, let us review relevant aspects whose common properties are so extensive that it is advantageous of software product lines, feature models, and relational databases. to study the common properties of the programs before analyzing 2 SOFTWARE PRODUCT LINES individual members” [23]. That is, developers should study the commonalities of the programs before studying their variabilities. According to the Software Engineering Institute (SEI), an SPL is These ideas underlie contemporary research on software product a “set of software-intensive systems sharing a common, managed lines [26]. set of features that satisfy the specic need of a particular market A software product line (SPL) in some application domain is a segment or mission and that are developed from a common set of set of related systems that share common software features but core assets in a prescribed way” [10]. A feature is a stakeholder- visible behavior of a software system [18]. Czarnecki and Eisenecke ∗Also with National Center for Computational Hydroscience and Engineering. [12] suggest making a feature visible not only helps the customer to understand the software, but it also helps domain engineers, Permission to make digital or hard copies of part or all of this work for personal or software engineers, and others in the development of the SPL. classroom use is granted without fee provided that copies are not made or distributed for prot or commercial advantage and that copies bear this notice and the full citation SPLs focus on reusing domain knowledge [22]. A domain is an on the rst page. Copyrights for third-party components of this work must be honored. abstract space in which a set of related systems share common ter- For all other uses, contact the owner/author(s). minology, requirements, and design choices. An organization can ACMSE‘17, Kennesaw, GA, USA © 2017 Copyright held by the owner/author(s). 123-4567-24-567/08/06...$15.00 build reusable software assets that capture the detailed knowledge DOI: 10.475/123_4 specic to a certain domain area. Consider a company that develops ACMSE‘17, April 2017, Kennesaw, GA, USA Hazim Shatnawi and H. Conrad Cunningham Root D A C B excludes requires E FG H Figure 2: A feature model for a product line Figure 1: SPL development process A feature model documents the product line architecture result- ing from the domain analysis [18]. In traditional feature models, a software for banks. Instead of developing a unique banking system model is depicted as a tree that represents all design choices (i.e., for each client, the company can use its general knowledge of bank- features) as nodes and the constraints that one choice imposes on ing systems—the domain—to produce a family of similar systems others by various types of edges between the nodes. Based on the that share common core functionalities but that can be customized dened relationships among the features in the model, the prod- for specic clients. This family forms a software product line. uct line can generate a specic product by selecting a valid set Figure 1 shows the development of an SPL consisting of two pro- of features—a set of features that satises all the constraints (i.e., domain engineering application engineering cesses: and [1]. rules). Domain engineering is the process of analyzing a domain by study- A feature model captures the commonalties and variabilities by ing the stakeholders’ requirements, reviewing existing systems representing the primary relationships among features as a tree. domain analysis within the domain, and performing . The domain The root represents the entire product line. An edge between a analysis identies the types of products included in the SPL and parent and a child is a relationship between a high-level design identies the design choices that are common to the entire domain decision and a detailed design decision needed in its realization. and those that vary among the specic applications. These design Kang proposed feature models for use in the Feature-Oriented choices are implemented as software parts that represent the com- Domain Analysis (FODA) method [18]. Other researchers have mon and variable features of a product. In addition, the domain extended the feature modeling notation in various ways [12, 13, 16, analysis examines customers’ requests and decides whether to in- 19, 27]. tegrate these requests within the product line or just to implement In feature models, features are connected by two kinds of rela- them as custom features for specic requests. tionships: Application engineering is the process of delivering a product by selecting a valid set of features from the SPL and implementing • Relationships between parent and child features new customer requirements that are within the scope of the SPL. • Cross-tree inclusion or exclusion constraints between fea- Domain analysis with feature modeling represents the problem tures space of a product line. A problem space denes a feature as a high- We can express a feature model visually as a feature diagram level abstraction by separating the feature from its implementation as shown in Figure 2. Root nodes are called concepts. Each con- details. This gives the stakeholders a clear description of the product cept represents a domain [2] or a complete product line [6]. The line features. The solution space represents features as source code model structures the other features into a multi-level parent-child and converts the stakeholders’ selections into concrete products. hierarchy. There are four kinds of parent-child relationships in feature 3 FEATURE MODELS models: mandatory, optional, alternative, and OR features [4, 12, 18, A feature model captures all the design choices in one high-level 27]. description [3, 14, 29]. Each feature corresponds to one design Mandatory features are software artifacts that must appear in choice. Some features are shared across all products in a product all possible congurations (generated products) of a product line. line (i.e., a commonality). Some only appear in specic products A mandatory feature can be a parent or child feature. If the feature (i.e., a variability). The success of an SPL depends upon eective is mandatory, then it has to be selected in the generated product management of the variabilities.
Load more

Recommended publications
  • Change and Version Management in Variability Models for Modular Ontologies
    Change and Version Management in Variability Models for Modular Ontologies Melanie Langermeier1, Thomas Driessen1, Heiner Oberkampf1;2, Peter Rosina1 and Bernhard Bauer1 1Software Methodologies for Distributed Systems, University of Augsburg, Augsburg, Germany 2Siemens AG, Corporate Technology, Munich, Germany Keywords: Variability Model, Modular Ontologies, Version Management, Change Management, Enterprise Architecture Management. Abstract: Modular ontology management tries to overcome the disadvantages of large ontologies regarding reuse and performance. A possibility for the formalization of the various combinations are variability models, which originate from the software product line domain. Similar to that domain, knowledge models can then be individualized for a specific application through selection and exclusion of modules. However, the ontology repository as well as the requirements of the domain are not stable over time. A process is needed, that enables knowledge engineers and domain experts to adapt the principles of version and change management to the domain of modular ontology management. In this paper, we define the existing change scenarios and provide support for keeping the repository, the variability model and also the configurations consistent using Semantic Web technologies. The approach is presented with a use case from the enterprise architecture domain as running example. 1 INTRODUCTION quirements, for instance, that the domain Ontology A and Ontology B should not be used together. For the Knowledge management is an important aspect in or- creation of a configuration, this variability knowledge ganizations. Typically, different models are used to can be automatically processed, and therewith sup- capture all relevant aspects of the organization. These ports the domain expert in creating a consistent con- models can extend each other, but can also overlay figuration.
    [Show full text]
  • Innovations in Model-Based Software and Systems Engineering
    Journal of Object Technology Published by AITO — Association Internationale pour les Technologies Objets http://www.jot.fm/ Innovations in Model-based Software And Systems Engineering Katrin Hölldoblera Judith Michaela Jan Oliver Ringertb Bernhard Rumpea Andreas Wortmanna a. Software Engineering, RWTH Aachen University, Germany b. Department of Informatics, University of Leicester, UK Abstract Engineering software and software intensive systems has become in- creasingly complex over the last decades. In the ongoing digitalization of all aspects of our lives in almost every domain, including, e.g., mechanical engineering, electrical engineering, medicine, entertainment, or jurisdiction, software is not only used to enable low-level controls of machines, but also to understand system conditions and optimizations potentials. To remain in control of all these heterogeneous systems of systems, a precise, but abstract understanding of these systems is necessary. To this end, models in their various forms are an important prerequisite to gain this understanding. In this article, we summarize research activities focusing on the de- velopment and use of models in software and systems engineering. This research has been carried out by the working group of Bernhard Rumpe, which started 25 years ago in Munich, continued in Braunschweig, and since 10 years carries on at RWTH Aachen University. Keywords Model, Modeling, Software Engineering, Language Workbench 1 Introduction Development of a system consists of understanding what the system should do, decom- posing the problem into smaller problems until they can be solved individually and composed into an overall solution. An important part of this process is decomposition, which leads to an architecture for the individual components.
    [Show full text]
  • Feature-Based Composition of Software Architectures Carlos Parra, Anthony Cleve, Xavier Blanc, Laurence Duchien
    Feature-based Composition of Software Architectures Carlos Parra, Anthony Cleve, Xavier Blanc, Laurence Duchien To cite this version: Carlos Parra, Anthony Cleve, Xavier Blanc, Laurence Duchien. Feature-based Composition of Soft- ware Architectures. 4th European Conference on Software Architecture, Aug 2010, Copenhagen, Denmark. pp.230-245, 10.1007/978-3-642-15114-9_18. inria-00512716 HAL Id: inria-00512716 https://hal.inria.fr/inria-00512716 Submitted on 31 Aug 2010 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Feature-based Composition of Software Architectures Carlos Parra, Anthony Cleve, Xavier Blanc, and Laurence Duchien INRIA Lille-Nord Europe, LIFL CNRS UMR 8022, Universit´edes Sciences et Technologies de Lille, France {carlos.parra, anthony.cleve, xavier.blanc, laurence.duchien}@inria.fr Abstract. In Software Product Lines variability refers to the definition and utilization of differences between several products. Feature Diagrams (FD) are a well-known approach to express variability, and can be used to automate the derivation process. Nevertheless, this may be highly complex due to possible interactions between selected features and the artifacts realizing them. Deriving concrete products typically involves the composition of such inter-dependent software artifacts.
    [Show full text]
  • A Model-Based Approach to Managing Feature Binding Time in Software Product Line Engineering
    A Model-Based Approach to Managing Feature Binding Time in Software Product Line Engineering Armaya’u Zango Umar Jaejoon Lee Lancaster University Lancaster University Lancaster, United Kingdom Lancaster, United Kingdom [email protected] [email protected] ABSTRACT EduPL Software Product Line Engineering (SPLE) is a software reuse par- Course Registration adigm for developing software products, from managed reusable Result Computation................. Account Creation Payment ...... ..... assets, based on analysis of commonality and variability (C & V) .......... ......... Application of a product line. Many approaches of SPLE use a feature as a Messaging Service Sub-degree key abstraction to capture the C&V. Recently, there have been in- Contact Validation Email Graduate creasing demands for the provision of flexibility about not only Text Message Under Graduate the variability of features but also the variability of when features Composition Rule Legend should be selected (i.e., variability on feature binding times). Cur- Contact Validation Requires Messaging Service Optional Alternative Group rent approaches to support variations of feature binding time mostly GraduateRequires Payment OR group Composed-of relationship focused on ad hoc implementation mechanisms. In this paper, we first identify the challenges of feature binding time management and then propose an approach to analyze the variation of feature Figure 1: Partial feature model of EduPl binding times and use the results to specify model-based architec- tural components for the product line. Based on the specification, components implementing variable features are parameterized with be tailored to produce a potentially unique architecture for each of the binding times and the source codes for the components and the the products of a product line.
    [Show full text]
  • Reactive Variability Realization with Test-Driven Development and Refactoring
    Reactive Variability Realization with Test-Driven Development and Refactoring Glauco Silva Neves Patrícia Vilain Informatics and Statistics Department - INE Informatics and Statistics Department - INE Federal University of Santa Catarina - UFSC Federal University of Santa Catarina - UFSC Florianópolis, Brazil Florianópolis, Brazil [email protected] [email protected] Abstract— Software product line is a practice that has proven its Despite its advantages, a SPL requires a high upfront and advantages since it can offer to a company the reduction of time long-term investment to design and to develop the core assets to market, the decrease of development costs, the increase of repository, hindering the SPL use in dynamic markets due to productivity and the improvement of the final product quality. the risk of unforeseen changes and the cost of developing However, this practice requires a high initial investment and artifacts that may no longer be reused. To overcome this offers long-term risks to dynamic markets where changes are difficulty, there is a proposal of combining agile software difficult to predict. One of these markets is the mobile application development practices with SPL, resulting in the Agile Product development, which presents a growing demand, with Line Engineering (APLE) [2]. smartphone and tablets having already surpassed sales of PCs and notebooks. Currently, proposals bring the advantages of One example of a dynamic market that has grown rapidly is software product line for dynamic markets through the use of the one of applications for mobile devices. Smartphones and agile software development practices, which is called Agile tablets have surpassed PC and laptop sales [3].
    [Show full text]
  • Feature and Class Models in Clafer: Mixed, Specialized, and Coupled
    Feature and Class Models in Clafer: Mixed, Specialized, and Coupled University of Waterloo Technical Report CS-2010-10 Kacper Bąk1, Krzysztof Czarnecki1, and Andrzej Wąsowski2 1 Generative Software Development Lab, University of Waterloo, Canada, {kbak,kczarnec}@gsd.uwaterloo.ca 2 IT University of Copenhagen, Denmark, [email protected] Abstract. We present Clafer, a class modeling language with first-class support for feature modeling. We designed Clafer as a concise notation for class models, feature models, mixtures of class and feature models (such as components with options), and models that couple feature models and class models via constraints (such as mapping feature configurations to component configurations). Clafer also allows arranging models into mul- tiple specialization and extension layers via constraints and inheritance. We identified four key mechanisms allowing a class modeling language to express feature models concisely and show that Clafer meets its design objectives using a sample product line. 1 Introduction Both feature and class modeling have been used in software product line en- gineering to model variability. Feature models are tree-like menus of mostly Boolean—but sometimes also integer and string—configuration options, aug- mented with cross-tree constraints [15]. These models are typically used to show the variation of user-relevant characteristics of products within a product line. In contrast, class models, as supported by the Unified Modeling Language (UML), have been used to represent the components and connectors of product line ar- chitectures and the valid ways to connect them. Thus, the nature of variability expressed by each type of models is different: feature models capture simple se- lections from predefined (mostly Boolean) choices within a fixed (tree) structure; and class models support making new structures by creating multiple instances of classes and connecting them via object references.
    [Show full text]
  • Using Feature Modeling for Program Comprehension and Software
    Using Feature Modeling for Program Comprehension and Software Architecture Recovery Ilian Pashov, Matthias Riebisch Technical University Ilmenau, Max-Planck-Ring 14, P.O. Box 100565 98684 Ilmenau, Germany {idpashov|matthias.riebisch}@tu-ilmenau.de Abstract: The available evidence in a legacy software their life cycle. Evolving often means refactoring or system, which can help in its understanding and recovery migrating to a new approach, for example component based systems or product lines. However, to succeed in of its architecture are not always sufficient. Very often the system’s documentation is poor and outdated. One such a step, a full understanding of the software system may argue that the most reliable resource of information is required leading to the need for its architecture and design decisions to be recovered. is the system’s source code. Nevertheless a significant knowledge about the problem domain is required in Due to the long life cycle of these systems, in most of order to facilitate the extraction of the system’s useful the cases it is impossible to keep the same development architectural information. team. A lot of knowledge about the system is lost along In this approach feature modeling is introduced as an with the developers. Often the system’s documentation is additional step in a system’s architectural recovery out of date and insufficient. This means that additional process. Feature modeling structures the system’s help is required for the architectural recovery of the system from the reverse engineers and the reverse functionality and supports reverse engineering by detecting the relations between source code elements and engineering methods.
    [Show full text]
  • An Overview of Feature-Oriented Software Development
    Vol. 8, No. 4, July{August 2009 An Overview of Feature-Oriented Software Development Sven Apel, Department of Informatics and Mathematics, University of Passau, Germany Christian K¨astner, School of Computer Science, University of Magdeburg, Germany Feature-oriented software development (FOSD) is a paradigm for the construction, customization, and synthesis of large-scale software systems. In this survey, we give an overview and a personal perspective on the roots of FOSD, connections to other software development paradigms, and recent developments in this field. Our aim is to point to connections between different lines of research and to identify open issues. 1 INTRODUCTION Feature-oriented software development (FOSD) is a paradigm for the construction, customization, and synthesis of large-scale software systems. The concept of a fea- ture is at the heart of FOSD. A feature is a unit of functionality of a software system that satisfies a requirement, represents a design decision, and provides a potential configuration option. The basic idea of FOSD is to decompose a software system in terms of the features it provides. The goal of the decomposition is to construct well-structured software that can be tailored to the needs of the user and the appli- cation scenario. Typically, from a set of features, many different software systems can be generated that share common features and differ in other features. The set of software systems generated from a set of features is also called a software product line [45,101]. FOSD aims essentially at three properties: structure, reuse, and variation. De- velopers use the concept of a feature to structure design and code of a software system, features are the primary units of reuse in FOSD, and the variants of a software system vary in the features they provide.
    [Show full text]
  • Quality Attributes Modeling in Feature Models and Feature Model
    A thesis submitted in fulfillment of requirement for the degree of Doctor of Philosophy GUOHENG ZHANG School of Electrical Engineering and Computer Science The University of Newcastle, Callaghan, NSW, 2308, Australia March 2013 Statement of Originality The thesis contains no material which has been accepted for the award of any other degree or diploma in any university or other tertiary institution and, to the best of my knowledge and belief, contains no material previously published or written by another person, except where due reference has been made in the text. I give consent to the final version of my thesis being made available worldwide when deposited in the University’s Digital Repository. Guoheng Zhang Acknowledgement I would like to acknowledge the support and encouragement of several people, without whom, this thesis would not be possible. Firstly, I am grateful for my two supervisors, Associate Prof. Huilin Ye and Dr. Yuqing Lin. I have learnt almost everything about research from them. In the last four years, they have given me guidance and encouragement, support and generosity in sharing their time, knowledge, and expertise during the preparation of my Ph.D thesis and throughout my research work. My research has been funded by Australian Research Council under Discovery Project DP0772799. I would like to thank the Council for this great opportunity. I wish to thank my wife for her love, encouragement and continuous support. I am grateful to my parents for their support and education. During several conferences, I had the pleasure to meet many passionate people from the software product line community.
    [Show full text]
  • Agile Product Line Engineering: the Agifpl Method
    Agile Product Line Engineering: The AgiFPL Method Hassan Haidar1, Manuel Kolp1 and Yves Wautelet2 1LouRIM-CEMIS, Université Catholique de Louvain, Belgium 2KULeuven, Faculty of Economics and Business, Belgium Keywords: Software Product Line Engineering, Agile Software Development, Agile Product Line Engineering, AgiFPL, Scrum, Scrumban, Features. Abstract: Integrating Agile Software Development (ASD) with Software Product Line Engineering (PLE) has resulted in proposing Agile Product Line Engineering (APLE). The goal of combining both approaches is to overcome the weaknesses of each other while maximizing their benefits. However, combining them represents a big challenge in software engineering. Several methods have been proposed to provide a practical process for applying APLE in organizations, but none covers all the required APLE features. This paper proposes an APLE methodology called AgiFPL: Agile Framework for managing evolving PL with the intention to address the deficiencies identified in current methods, while making use of their advantages. 1 INTRODUCTION as presenting strengths and weaknesses. Furthermore, the study of the existing APLE methods has revealed Over the past years, the software industry has been that no single method covers all the needed APLE searching for methods, processes and techniques to features. increase the delivery of high quality software while In this context, this paper proposes an APLE reducing development costs. Several paradigms have methodology called AgiFPL (Agile Framework for been proposed in order to fulfil this target. “Agile managing evolving SPL). The intention behind the Software Development” (ASD) and “Product Line definition of this APLE method is to address the Engineering” (PLE) are well-known approaches deficiencies identified in current methods, while proposed by researchers and practitioners for dealing making use of their advantages.
    [Show full text]
  • Applying Feature-Oriented Software Development in Saas Systems: Real Experience, Measurements, and Findings
    Applying Feature-Oriented Software Development in SaaS Systems: Real Experience, Measurements, and Findings Oscar Pedreira1, Fernando Silva-Coira1, Angeles´ Saavedra Places1, Miguel R. Luaces1 and Leticia Gonzalez´ Folgueira2 1Universidade da Coruña, Centro de Investigación CITIC, Facultade de Informática, A Coruña, Spain 2Enxenio S.L., A Coruña, Spain E-mail: [email protected]; [email protected]; [email protected]; [email protected]; [email protected] Received 14 January 2019; Accepted 06 June 2019 Abstract Distributing software as a service (SaaS) has become a major trend for web-based systems. However, this software distribution model poses many challenges. One of them is feature variability, that is, some features of the system may be required by some users, but not by all of them. In addition, variability is more complex than just including or excluding a feature, since different types of relationships may exist between features. The implementation of this variability, and the parametrization and configuration of the system can be complex in this context, so the development process of a SaaS system must adequately address variability management. In this paper we present an Journal of Web Engineering, Vol. 18 4-6, 447–476. doi: 10.13052/jwe1540-9589.18467 c 2019 River Publishers 448 O. Pedreira et al. experience applying feature oriented software development (FOSD) in the context of SaaS web-based systems development. We present a real experience in the development of a web-based system for managing home care services for dependent people. The article describes the problem of variability management in this domain, and the feature model of the system.
    [Show full text]
  • Ontology-Based Context Event Representation, Reasoning, and Enhancing in Academic Environments
    future internet Article Ontology-Based Context Event Representation, Reasoning, and Enhancing in Academic Environments Josué Padilla-Cuevas , José A. Reyes-Ortiz * and Maricela Bravo Departamento de Sistemas, Universidad Autónoma Metropolitana, Azcapotzalco 02200, Mexico; [email protected] (J.P.-C.); [email protected] (M.B.) * Correspondence: [email protected] Abstract: An Ambient Intelligence responds to user requests based on several contexts. A relevant context is related to what has happened in the ambient; therefore, it focuses a primordial interest on events. These involve information about time, space, or people, which is significant for modeling the context. In this paper, we propose an event-driven approach for context representation based on an ontological model. This approach is extendable and adaptable for academic domains. Moreover, the ontological model to be proposed is used in reasoning and enrichment processes with the context event information. Our event-driven approach considers five contexts as a modular perspective in the model: Person, temporal (time), physical space (location), network (resources to acquire data from the ambient), and academic events. We carried out an evaluation process for the approach based on an ontological model focused on (a) the extensibility and adaptability of use case scenarios for events in an academic environment, (b) the level of reasoning by using competence questions related to events, (c) and the consistency and coherence in the proposed model. The evaluation Citation: Padilla-Cuevas, J.; process shows promising results for our event-driven approach for context representation based on Reyes-Ortiz, J.A.; Bravo, M. the ontological model. Ontology-Based Context Event Representation, Reasoning, and Keywords: knowledge engineering; event-driven representation; ontology model; context reasoning; Enhancing in Academic event enhancing Environments.
    [Show full text]