Engineering Delta Modeling Languages

Delta modeling is a modular, yet flexible approach to capture spatial and temporal variability by explicitly representing the differences between system variants or versions. The conceptual idea of delta modeling is language-independent. But, in order to apply delta modeling for a concrete language, so far, a delta language had to be manually developed on top of the base language leading to a large variety of heterogeneous language concepts. In this paper, we present a process that allows deriving a delta language from the grammar of a given base language. Our approach relies on an automatically generated language extension that can be manually adapted to meet domain-specific needs. We illustrate our approach using delta modeling on a textual variant of statecharts.Comment: 10 pages, 8 figures. Proceedings of the 17th International Software Product Line Conference, Tokyo, September 2013, pp.22-31, ACM, 201

Representing Variability in Software Architecture: A Systematic Literature Review

Variability in software - intensive systems is the ability of a software artefact (e.g., a system, subsystem, or component) to be extended, customised or configured for deployment in a specific context. Software Architecture is a high - level description of a software - intensive system that abstracts the system implementation details allowing the architect to view the system as a whole. Although variability in software architecture is recognised as a challenge in multiple domains, there has been no formal consensus on how variability should be captured or represented. The objective of this research was to provide a snapshot of the state - of - the - art on representing variability in software architecture while assessing the nature of the different approaches. To achieve this objective, a Systematic Literature Review (SLR) was conducted covering literature produced from January 1991 until June 2016. Then, grounded theory was used to conduct the analysis and draw conclusions from data, mini mising threats to validity. In this paper , we report on the findings from the study

Extração e evolução de linhas de produtos de software usando Delta-Oriented Programming : um relato de experiência

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Exatas, Departamento de Ciência da Computação, 2019.Delta-Oriented Programming (DOP) é uma abordagem flexível e modular para a implementação de Linha de Produtos de Software (LPS). Desde 2010, ano em que a abordagem foi proposta, vários trabalhos sobre DOP foram publicados. Entretanto, após a condução de um estudo de mapeamento sistemático da literatura para analisar as reais implicações da técnica, notou-se que poucos desses trabalhos avaliavam de forma rigorosa os aspectos relacionados à evolução de LPS em DOP. Assim sendo, este trabalho apresenta um relato das implicações do uso dessa abordagem através de três diferentes perspectivas: (i) a extração e evolução de um aplicativo mobile em uma linha de produtos usando a DOP; (ii) a caracterização dos cenários de evolução segura e parcialmente segura de DOP através dos templates existentes na literatura; e (iii) uma análise em relação à propagação de mudanças e modularidade da técnica durante o seu processo de evolução. Os resultados mostraram que, apesar da técnica possuir uma maior aderência ao princípio open-closed, o seu uso pode não ser apropriado caso o principal interesse seja a evolução modular de features da linha de produtos, além de que, atualmente, a técnica ainda está limitada ao desenvolvimento em Java, em virtude da falta de plugins ou ferramentas que suportar outras linguagens de programação.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).Delta-OrientedProgramming(DOP)isaflexibleandmodularapproachtoSoftwareProduct Line (SPL) implementation. Since 2010, the year the approach was proposed, several papers about DOP have been published. However, after conducting a systematic literature mapping study to analyze the real implications of the technique, it was noted that fewofthesestudiesrigorouslyevaluatedtheaspectsrelatedtotheevolutionofSPLdeltaoriented. Therefore, this work reports the implications of using this approach from three different perspectives: (i) extracting and evolving an Android application to a SPL using DOP; (ii) the characterization of safe and partially safe delta-oriented evolution scenarios throughthetemplatesexistingintheliterature; and(iii)ananalysisregardingthechange impact and modularity properties of the technique during its evolution process. The results showed that, although the technique has a greater adherence to the open-closed principle, its use may not be appropriate if the main interest is the modular evolution of product line features, and currently the technique is still limited to Java development because of the lack of plugins or tools that support other programming languages

Representing Variability in Software Architecture

Software Architecture is a high level description of a software intensive system that enables architects to have a better intellectual control over the complete system. It is also used as a communication vehicle among the various system stakeholders. Variability in software-intensive systems is the ability of a software artefact (e.g., a system, subsystem, or component) to be extended, customised, or configured for deployment in a specific context. Although variability in software architecture is recognised as a challenge in multiple domains, there has been no formal consensus on how variability should be captured or represented. In this research, we addressed the problem of representing variability in software architecture through a three phase approach. First, we examined existing literature using the Systematic Literature Review (SLR) methodology, which helped us identify the gaps and challenges within the current body of knowledge. Equipped with the findings from the SLR, a set of design principles have been formulated that are used to introduce variability management capabilities to an existing Architecture Description Language (ADL). The chosen ADL was developed within our research group (ALI) and to which we have had complete access. Finally, we evaluated the new version of the ADL produced using two distinct case studies: one from the Information Systems domain, an Asset Management System (AMS); and another from the embedded systems domain, a Wheel Brake System (WBS). This thesis presents the main findings from the three phases of the research work, including a comprehensive study of the state-of-the-art; the complete specification of an ADL that is focused on managing variability; and the lessons learnt from the evaluation work of two distinct real-life case studies

Delta-oriented Architectural Variability Using MontiCore

Modeling of software architectures is a fundamental part of software development processes. Reuse of software components and early analysis of software topologies allow the reduction of development costs and increases software quality. Integrating variability modeling concepts into architecture description languages (ADLs) is essential for the development of diverse software systems with high demands on software quality. In this paper, we present the integration of delta modeling into the existing ADL MontiArc. Delta modeling is a language-independent variability modeling approach supporting proactive, reactive and extractive product line development. We show how ∆-MontiArc, a language for explicit modeling of architectural variability based on delta modeling, is implemented as domain-specific language (DSL) using the DSL development framework MontiCore. We also demonstrate how MontiCore’s language reuse mechanisms provide efficient means to derive an implementation of ∆-MontiArc tool implementation. We evaluate ∆-Monti-Arc by comparing it with annotative variability modeling

Interdisziplinäre Variabilitätsmodellierung und Performance Analyse für langlebige Systeme in der Automatisierungstechnik

In this day and age, automation systems have to deal with differing customer needs, environmental requirements and multiple application contexts. Automation systems have to be variable enough to satisfy all of these demands. The development and maintenance of such highly-customizable systems is a challenging task and becomes increasingly more difficult considering multiple involved engineering disciplines and long lifetimes, which is characteristic for industrial systems of the automation domain. Software product line engineering provides developers with fundamental concepts to manage the variability of such systems. However, these concepts are not established in the domain of automation systems. In addition, the involvement of multiple engineering disciplines poses a threat to existing SPL techniques. This thesis contributes novel approaches to improve the development and maintenance of software-intensive automation product lines. In total, three major contributions are made, spanning across the complete design phase of an automation system. (1) The feature modeling process is improved by detecting hidden dependencies between interrelated feature models from separate engineering disciplines. Furthermore, hidden dependencies and occurring defects in the feature models are explained in a user-friendly manner. (2) A model-driven development approach is introduced consisting of UML models, which are extended with delta modeling to manage variability in the automation product line. The models encompass information that is needed to automatically derive and analyze a performance model. (3) Subsequently, an efficient family-product-based performance analysis is proposed for the previously derived UML models that is vastly superior compared to common product-based approaches. All of these techniques have been evaluated using multiple case studies, with one being a real-world automation system.In der heutigen Zeit sehen sich Automatisierungssysteme mit einer steigenden Komplexität konfrontiert. Einzelne Kunden haben unterschiedliche Ansprüche an das System und ebenso müssen Umweltbedingungen der verschiedenen Betriebsumgebungen sowie abweichende Anwendungsgebiete bei der Entwicklung eines Automatisierungssystems berücksichtigt werden. Diese Komplexitätsaspekte werden unter dem Stichwort Variabilität zusammengefasst. Ein Automatisierungssystem muss in der Lage sein, sämtliche Anforderungen zu erfüllen. Die Entwicklung und Wartung dieser Systeme wird jedoch durch die stetig wachsende Variabilität und eine potentiell lange Lebensdauer immer schwieriger. Zusätzlich sind an dem Entwicklungsprozess eines Automatisierungssystems mehrere Ingenieursdisziplinen beteiligt. Die Techniken aus dem Bereich der Software-Produktlinienentwicklung bilden Lösungen, um die Variabilität beherrschbar zu machen. In der Automatisierungstechnik sind diese Techniken weitgehend unbekannt und durch den interdisziplinären Charakter oft nicht ausreichend. Daher werden in dieser Dissertation neue Ansätze entwickelt und vorgestellt, die auf die Domäne der Automatisierungstechnik zugeschnitten sind. Insgesamt leistet diese Dissertation folgende drei wissenschaftlichen Beiträge: (1) Die Entwicklung von Feature-Modellen wird durch die Detektion von verborgenen Abhängigkeiten, die zwischen Feature-Modellen der unterschiedlichen Ingenieursdisziplinen existieren, verbessert. Gleichzeitig liefert der vorgestellte Algorithmus die Erklärung für die Existenz dieser Abhängigkeiten. Dieses Konzept wird auf weitere Defekte in Feature-Modellen ausgeweitet. (2) Einen modell-basierten Ansatz zur Entwicklung eines Automatisierungssystems. Der Ansatz basiert auf Modellen aus der UML, die mit Hilfe der Delta Modellierung Variabilität abbilden können. Zusätzlich sind die Modelle mit Informationen über Performance Eigenschaften angereichert und erlauben die automatische Ableitung eines Performance-Modells. (3) Eine effiziente Performance Analyse von allen Varianten des Automatisierungssystems, die auf den zuvor abgeleiteten Performance-Modellen basiert. Alle Beiträge wurden mit Fallstudien evaluiert. Eine Fallstudie repräsentiert ein reales Automatisierungssystem

Integrated Management of Variability in Space and Time in Software Families

Software Product Lines (SPLs) and Software Ecosystems (SECOs) are approaches to capturing families of closely related software systems in terms of common and variable functionality (variability in space). SPLs and especially SECOs are subject to software evolution to adapt to new or changed requirements resulting in different versions of the software family and its variable assets (variability in time). Both dimensions may be interconnected (e.g., through version incompatibilities) and, thus, have to be handled simultaneously as not all customers upgrade their respective products immediately or completely. However, there currently is no integrated approach allowing variant derivation of features in different version combinations. In this thesis, remedy is provided in the form of an integrated approach making contributions in three areas: (1) As variability model, Hyper-Feature Models (HFMs) and a version-aware constraint language are introduced to conceptually capture variability in time as features and feature versions. (2) As variability realization mechanism, delta modeling is extended for variability in time, and a language creation infrastructure is provided to devise suitable delta languages. (3) For the variant derivation procedure, an automatic version selection mechanism is presented as well as a procedure to derive large parts of the application order for delta modules from the structure of the HFM. The presented integrated approach enables derivation of concrete software systems from an SPL or a SECO where both features and feature versions may be configured.:I. Context and Preliminaries 1. The Configurable TurtleBot Driver as Running Example 1.1. TurtleBot: A Domestic Service Robot 1.2. Configurable Driver Functionality 1.3. Software Realization Artifacts 1.4. Development History of the Driver Software 2. Families of Variable Software Systems 2.1. Variability 2.1.1. Variability in Space and Time 2.1.2. Internal and External Variability 2.2. Manifestations of Configuration Knowledge 2.2.1. Variability Models 2.2.2. Variability Realization Mechanisms 2.2.3. Variability in Realization Assets 2.3. Types of Software Families 2.3.1. Software Product Lines 2.3.2. Software Ecosystems 2.3.3. Comparison of Software Product Lines and Software Ecosystems 3. Fundamental Approaches and Technologies of the Thesis 3.1. Model-Driven Software Development 3.1.1. Metamodeling Levels 3.1.2. Utilizing Models in Generative Approaches 3.1.3. Representation of Languages using Metamodels 3.1.4. Changing the Model-Representation of Artifacts 3.1.5. Suitability of Model-Driven Software Development 3.2. Fundamental Variability Management Techniques of the Thesis 3.2.1. Feature Models as Variability Models 3.2.2. Delta Modeling as Variability Realization Mechanism 3.2.3. Variant Derivation Process of Delta Modeling with Feature Models 3.3. Constraint Satisfaction Problems 3.4. Scope 3.4.1. Problem Statement 3.4.2. Requirements 3.4.3. Assumptions and Boundaries II. Integrated Management of Variability in Space and Time 4. Capturing Variability in Space and Time with Hyper-Feature Models 4.1. Feature Models Cannot Capture Variability in Time 4.2. Formal Definition of Feature Models 4.3. Definition of Hyper-Feature Models 4.4. Creation of Hyper-Feature Model Versions 4.5. Version-Aware Constraints to Represent Version Dependencies and Incompatibilities 4.6. Hyper-Feature Models are a True Extension to Feature Models 4.7. Case Study 4.8. Demarcation from Related Work 4.9. Chapter Summary 5. Creating Delta Languages Suitable for Variability in Space and Time 5.1. Current Delta Languages are not Suitable for Variability in Time 5.2. Software Fault Trees as Example of a Source Language 5.3. Evolution Delta Modules as Manifestation of Variability in Time 5.4. Automating Delta Language Generation 5.4.1. Standard Delta Operations Realize Usual Functionality 5.4.2. Custom Delta Operations Realize Specialized Functionality 5.5. Delta Language Creation Infrastructure 5.5.1. The Common Base Delta Language Provides Shared Functionality for all Delta Languages 5.5.2. Delta Dialects Define Delta Operations for Custom Delta Languages 5.5.3. Custom Delta Languages Enable Variability in Source Languages 5.6. Case Study 5.7. Demarcation from Related Work 5.8. Chapter Summary 6. Deriving Variants with Variability in Space and Time 6.1. Variant Derivation Cannot Handle Variability in Time 6.2. Associating Features and Feature Versions with Delta Modules 6.3. Automatically Select Versions to Ease Configuration 6.4. Application Order and Implicitly Required Delta Modules 6.4.1. Determining Relevant Delta Modules 6.4.2. Forming a Dependency Graph of Delta Modules 6.4.3. Performing a Topological Sorting of Delta Modules 6.5. Generating Variants with Versions of Variable Assets 6.6. Case Study 6.7. Demarcation from Related Work 6.8. Chapter Summary III. Realization and Application 7. Realization as Tool Suite DeltaEcore 7.1. Creating Delta Languages 7.1.1. Shared Base Metamodel 7.1.2. Common Base Delta Language 7.1.3. Delta Dialects 7.2. Specifying a Software Family with Variability in Space and Time 7.2.1. Hyper-Feature Models 7.2.2. Version-Aware Constraints 7.2.3. Delta Modules 7.2.4. Application-Order Constraints 7.2.5. Mapping Models 7.3. Deriving Variants 7.3.1. Creating a Configuration 7.3.2. Collecting Delta Modules 7.3.3. Ordering Delta Modules 7.3.4. Applying Delta Modules 8. Evaluation 8.1. Configurable TurtleBot Driver Software 8.1.1. Variability in Space 8.1.2. Variability in Time 8.1.3. Integrated Management of Variability in Space and Time 8.2. Metamodel Family for Role-Based Modeling and Programming Languages 8.2.1. Variability in Space 8.2.2. Variability in Time 8.2.3. Integrated Management of Variability in Space and Time 8.3. A Software Product Line of Feature Modeling Notations and Constraint Languages 8.3.1. Variability in Space 8.3.2. Variability in Time 8.3.3. Integrated Management of Variability in Space and Time 8.4. Results and Discussion 8.4.1. Results and Discussion of RQ1: Variability Model 8.4.2. Results and Discussion of RQ2: Variability Realization Mechanism 8.4.3. Results and Discussion of RQ3: Variant Derivation Procedure 9. Conclusion 9.1. Discussion 9.1.1. Supported Evolutionary Changes 9.1.2. Conceptual Representation of Variability in Time 9.1.3. Perception of Versions as Incremental 9.1.4. Version Numbering Schemes 9.1.5. Created Delta Languages 9.1.6. Scalability of Approach 9.2. Possible Future Application Areas 9.2.1. Extend to Full Software Ecosystem Feature Model 9.2.2. Model Software Ecosystems 9.2.3. Extract Hyper-Feature Model Versions and Record Delta Modules 9.2.4. Introduce Metaevolution Delta Modules 9.2.5. Support Incremental Reconfiguration 9.2.6. Apply for Evolution Analysis and Planning 9.2.7. Enable Evolution of Variable Safety-Critical Systems 9.3. Contribution 9.3.1. Individual Contributions 9.3.2. Handling Updater Stereotypes IV. Appendix A. Delta Operation Generation Algorithm B. Delta Dialects B.1. Delta Dialect for Java B.2. Delta Dialect for Eclipse Projects B.3. Delta Dialect for DocBook Markup B.4. Delta Dialect for Software Fault Trees B.5. Delta Dialect for Component Fault Diagrams B.6. Delta Dialect for Checklists B.7. Delta Dialect for the Goal Structuring Notation B.8. Delta Dialect for EMF Ecore B.9. Delta Dialect for EMFText Concrete Syntax File

Maßgeschneiderte Produktlinienextraktion

Industry faces an increasing number of challenges regarding the functionality, efficiency and reliability of software. A common approach to reduce the linked development effort and respective costs are model-based languages, such as Matlab/Simulink and statecharts. While these languages help companies during development of single systems, the high demand for customized software is an increasing challenge. As a result, variants with high similarity and only slight differences have to be developed in an efficient way. As reimplementation of complex functionality for each variant is no option, copies of existing solutions are often modified for new customers. In the short-run, this so-called clone-and-own approach allows to save costs as existing solutions can easily be reused. However, this approach also involves risks as the relations between the copied systems are rarely documented and errors have to be fixed for each variant in isolation. Thus, with a growing number of potentially large system copies, the resulting maintenance effort can become a problem. To overcome these problems, this thesis contributes an approach to semi-automatically migrate existing model variants to software product lines. These product lines allow to generate all variants from the identified reusable artifacts. As industry uses a variety of different modeling languages, the focus of the approach lies on an easy adaptation for different languages. Furthermore, the approach can be custom-tailored to include domain knowledge or language-specific details in the variability identification. The first step of the approach performs a high-level analysis of variants to identify outliers (e.g., variants that diverged too much from the rest) and clusters of strongly related variants. The second step executes variability mining to identify corresponding low-level variability relations (i.e. the common and varying parts) for these clusters. The third step uses these detailed variability relations for an automatic migration of the compared variants to a delta-oriented software product line. The approach is evaluated using publicly available case studies with industrial background as well as model variants provided by an industry partner.Die Industrie steht einer steigenden Anzahl an Herausforderungen bezüglich der Funktionalität, Effizienz und Zuverlässigkeit von Software gegenüber. Um den damit verbundenen Entwicklungsaufwand und entsprechende Kosten zu reduzieren, werden häufig modellbasierte Sprachen wie Matlab/Simulink oder Zustandsautomaten eingesetzt. Obwohl diese Sprachen die Unternehmen während der Entwicklung von Einzelsystemen unterstützen, führt die große Nachfrage nach maßgeschneiderter Software zu neuen Herausforderungen. Entsprechend müssen Varianten mit hoher Ähnlichkeit und nur geringfügigen Unterschieden effizient entwickelt werden. Da eine Neuimplementierung komplexer Funktionalität für jede Variante keine Option darstellt, werden häufig Kopien existierender Lösungen für Kunden angepasst. Auf kurze Sicht ermöglicht dieser sogenannte clone-and-own-Ansatz Kosten zu sparen, da existierende Lösungen leicht wiederverwendet werden können. Jedoch birgt der Ansatz auch Risiken, da Beziehungen zwischen den Systemkopien selten dokumentiert werden und Fehler für jede der Variante einzeln behoben werden müssen. Somit kann mit einer wachsenden Anzahl an möglicherweise umfangreichen Systemkopien der Wartungsaufwand zu einem Problem werden. Um diese Probleme zu lösen, bietet diese Arbeit einen Ansatz zur semi-automatischen Überführung existierender Modellvarianten in Softwareproduktlinien. Diese ermöglichen eine anschließende Generierung der Varianten aus den identifizierten wiederverwendbaren Artefakten. Da in der Industrie eine große Menge von Modellierungssprachen eingesetzt wird, liegt der Fokus auf der einfachen Adaption für unterschiedliche Sprachen. Zusätzlich kann durch Einbeziehung von Expertenwissen oder sprachspezifische Details die Variabilitätsidentifikation beeinflusst werden. Der erste Schritt des Ansatzes analysiert die Varianten auf hohem Abstraktionslevel, um Außenseiter (z.B. Varianten die stark von den restlichen Variaten abweichen) und Cluster von stark verwandten Varianten zu identifizieren. Der zweite Schritt analysiert diese Cluster auf niedrigem Abstraktionslevel, um entsprechende Variabilitätsrelationen (d.h. gemeinsame und unterschiedliche Teile) zu identifizieren. Der dritte Schritt nutzt diese detaillierten Variabilitätsrelationen für eine automatische Migration der verglichenen Varianten in eine delta-orientierte Softwareproduktlinie. Der Ansatz ist an Fallstudien mit industriellem Kontext sowie Modellvarianten eines Industriepartners evaluiert worden