The DOPLER meta-tool for decision-oriented variability modeling: a multiple case study

The variability of a product line is typically defined in models. However, many existing variability modeling approaches are rigid and don’t allow sufficient domain-specific adaptations. We have thus been developing a flexible and extensible approach for defining product line variability models. Its main purposes are to guide stakeholders through product derivation and to automatically generate product configurations. Our approach is supported by the DOPLER (Decision-Oriented Product Line Engineering for effective Reuse) meta-tool that allows modelers to specify the types of reusable assets, their attributes, and dependencies for their specific system and context. The aim of this paper is to investigate the suitability of our approach for different domains. More specifically, we explored two research questions regarding the implementation of variability and the utility of DOPLER for variability modeling in different domains. We conducted a multiple case study consisting of four cases in the domains of industrial automation systems and business software. In each of these case studies we analyzed variability implementation techniques. Experts from our industry partners then developed domain-specific meta-models, tool extensions, and variability models for their product lines using DOPLER. The four cases demonstrate the flexibility of the DOPLER approach and the extensibility and adaptability of the supporting meta tool.     

基于UML的软件产品线建模方法研究

软件产品线方法是一种面向特定领域的、大规模、大粒度的软件复用技术。文章简要介绍了基于UML的软件产品线建模方法。由于软件产品线对于产品线成员公共性和变化性的特殊关注,其用例模型、交互模型、状态模型、静态模型、特征模型和单一软件系统相比都有所区别。文章对各种模型进行描述的同时,以报业排版软件产品线样张打印功能为例,进行具体说明。     

Architecture-level software performance abstractions for online performance prediction

Modern service-oriented enterprise systems have increasingly complex and dynamic loosely-coupled architectures that often exhibit poor performance and resource efficiency and have high operating costs. This is due to the inability to predict at run-time the effect of workload changes on performance-relevant application-level dependencies and adapt the system configuration accordingly. Architecture-level performance models provide a powerful tool for performance prediction, however, current approaches to modeling the context of software components are not suitable for use at run-time. In this paper, we analyze typical online performance prediction scenarios and propose a performance meta-model for (i) expressing and resolving parameter and context dependencies, (ii) modeling service abstractions at different levels of granularity and (iii) modeling the deployment of software components in complex resource landscapes. The presented meta-model is a subset of the Descartes Meta-Model (DMM) for online performance prediction, specifically designed for use in online scenarios. We motivate and validate our approach in the context of realistic and representative online performance prediction scenarios based on the SPECjEnterprise2010 standard benchmark.     

Efficient synthesis of feature models

ContextVariability modeling, and in particular feature modeling, is a central element of model-driven software product line architectures. Such architectures often emerge from legacy code, but, creating feature models from large, legacy systems is a long and arduous task. We describe three synthesis scenarios that can benefit from the algorithms in this paper.ObjectiveThis paper addresses the problem of automatic synthesis of feature models from propositional constraints. We show that the decision version of the problem is NP-hard. We designed two efficient algorithms for synthesis of feature models from CNF and DNF formulas respectively.MethodWe performed an experimental evaluation of the algorithms against a binary decision diagram (BDD)-based approach and a formal concept analysis (FCA)-based approach using models derived from realistic models.ResultsOur evaluation shows a 10 to 1,000-fold performance improvement for our algorithms over the BDD-based approach. The performance of the DNF-based algorithm was similar to the FCA-based approach, with advantages for both techniques. We identified input properties that affect the runtimes of the CNF- and DNF-based algorithms.ConclusionsOur algorithms are the first known techniques that are efficient enough to be used on dependencies extracted from real systems, opening new possibilities of creating reverse engineering and model management tools for variability models.     

Supporting distributed product configuration by integrating heterogeneous variability modeling approaches

ContextIn industrial settings products are developed by more than one organization. Software vendors and suppliers commonly typically maintain their own product lines, which contribute to a larger (multi) product line or software ecosystem. It is unrealistic to assume that the participating organizations will agree on using a specific variability modeling technique—they will rather use different approaches and tools to manage the variability of their systems.ObjectiveWe aim to support product configuration in software ecosystems based on several variability models with different semantics that have been created using different notations.MethodWe present an integrative approach that provides a unified perspective to users configuring products in multi product line environments, regardless of the different modeling methods and tools used internally. We also present a technical infrastructure and a prototype implementation based on web services.ResultsWe show the feasibility of the approach and its implementation by using it with the three most widespread types of variability modeling approaches in the product line community, i.e., feature-based, OVM-style, and decision-oriented modeling. To demonstrate the feasibility and flexibility of our approach, we present an example derived from industrial experience in enterprise resource planning. We further applied the approach to support the configuration of privacy settings in the Android ecosystem based on multiple variability models. We also evaluated the performance of different model enactment strategies used in our approach.ConclusionsTools and techniques allowing stakeholders to handle variability in a uniform manner can considerably foster the initiation and growth of software ecosystems from the perspective of software reuse and configuration.     

Purpose based access control for privacy protection in relational database systems

In this article, we present a comprehensive approach for privacy preserving access control based on the notion of purpose. In our model, purpose information associated with a given data element specifies the intended use of the data element. A key feature of our model is that it allows multiple purposes to be associated with each data element and also supports explicit prohibitions, thus allowing privacy officers to specify that some data should not be used for certain purposes. An important issue addressed in this article is the granularity of data labeling, i.e., the units of data with which purposes can be associated. We address this issue in the context of relational databases and propose four different labeling schemes, each providing a different granularity. We also propose an approach to represent purpose information, which results in low storage overhead, and we exploit query modification techniques to support access control based on purpose information. Another contribution of our work is that we address the problem of how to determine the purpose for which certain data are accessed by a given user. Our proposed solution relies on role-based access control (RBAC) models as well as the notion of conditional role which is based on the notions of role attribute and system attribute.     

Configuring use case models in product families

In many domains such as automotive and avionics, the size and complexity of software systems is quickly increasing. At the same time, many stakeholders tend to be involved in the development of such systems, which typically must also be configured for multiple customers with varying needs. Product Line Engineering (PLE) is therefore an inevitable practice for such systems. Furthermore, because in many areas requirements must be explicit and traceability to them is required by standards, use cases and domain models are common practice for requirements elicitation and analysis. In this paper, based on the above observations, we aim at supporting PLE in the context of use case-centric development. Therefore, we propose, apply, and assess a use case-driven configuration approach which interactively receives configuration decisions from the analysts to generate product-specific (PS) use case and domain models. Our approach provides the following: (1) a use case-centric product line modeling method (PUM), (2) automated, interactive configuration support based on PUM, and (3) an automatic generation of PS use case and domain models from Product Line (PL) models and configuration decisions. The approach is supported by a tool relying on Natural Language Processing (NLP) and integrated with an industrial requirements management tool, i.e., IBM DOORS. We successfully applied and evaluated our approach to an industrial case study in the automotive domain, thus showing evidence that the approach is practical and beneficial to capture variability at the appropriate level of granularity and to configure PS use case and domain models in industrial settings.     

MOD2-SCM: A model-driven product line for software configuration management systems

ContextSoftware Configuration Management (SCM) is the discipline of controlling the evolution of large and complex software systems. Over the years many different SCM systems sharing similar concepts have been implemented from scratch. Since these concepts usually are hard-wired into the respective program code, reuse is hardly possible.ObjectiveOur objective is to create a model-driven product line for SCM systems. By explicitly describing the different concepts using models, reuse can be performed on the modeling level. Since models are executable, the need for manual programming is eliminated. Furthermore, by providing a library of loosely coupled modules, we intend to support flexible composition of SCM systems.MethodWe developed a method and a tool set for model-driven software product line engineering which we applied to the SCM domain. For domain analysis, we applied the FORM method, resulting in a layered feature model for SCM systems. Furthermore, we developed an executable object-oriented domain model which was annotated with features from the feature model. A specific SCM system is configured by selecting features from the feature model and elements of the domain model realizing these features.ResultsDue to the orthogonality of both feature model and domain model, a very large number of SCM systems may be configured. We tested our approach by creating instances of the product line which mimic wide-spread systems such as CVS, GIT, Mercurial, and Subversion.ConclusionThe experiences gained from this project demonstrate the feasibility of our approach to model-driven software product line engineering. Furthermore, our work advances the state of the art in the domain of SCM systems since it support the modular composition of SCM systems at the model rather than the code level.     

Managing requirements specifications for product lines - An approach and industry case study

Software product line development has emerged as a leading approach for software reuse. This paper describes an approach to manage natural-language requirements specifications in a software product line context. Variability in such product line specifications is modeled and managed using a feature model. The proposed approach has been introduced in the Swedish defense industry. We present a multiple-case study covering two different product lines with in total eight product instances. These were compared to experiences from previous projects in the organization employing clone-and-own reuse. We conclude that the proposed product line approach performs better than clone-and-own reuse of requirements specifications in this particular industrial context.     

Managing complexity and variability of a model-based embedded software product line

This paper presents a framework for model-based product lines of embedded systems. We show how to integrate model-based product line techniques into a consistent framework that can deal with large product lines as they are common in industry. The framework demonstrates the strengths of model-based techniques like abstraction, support for customised representations, and a high degree of automation. In particular, we provide the following contributions: (1) to shift existing product lines towards a model-based approach, we support the (semi-) automated extraction of models from existing requirement, test, and implementation artefacts; (2) to cope with the complexity of artefacts and their interrelations in industrial product lines, we support the generation of context-specific views. These views support developers, e.g., in analysing complex dependencies between different artefacts; (3) finally, we support automated product derivation based on an integrated hardware abstraction layer. Most of the presented concepts have been inspired by challenges arising in the industrial application of product line techniques in the model-based engineering of embedded systems. We report on experiences gathered during the application of the techniques to a prototypical product line (on a rapid prototyping platform in the university lab) and to industrial sample cases (at the industry partner).     

A scoped approach to traceability management

Traceability is the ability to describe and follow the life of a software artifact and a means for modeling the relations between software artifacts in an explicit way. Traceability has been successfully applied in many software engineering communities and has recently been adopted to document the transition among requirements, architecture and implementation. We present an approach to customize traceability to the situation at hand. Instead of automating tracing, or representing all possible traces, we scope the traces to be maintained to the activities stakeholders must carry out. We define core traceability paths, consisting of essential traceability links required to support the activities. We illustrate the approach through two examples: product derivation in software product lines, and release planning in software process management. By using a running software product line example, we explain why the core traceability paths identified are needed when navigating from feature to structural models and from family to product level and backward between models used in software product derivation. A feasibility study in release planning carried out in an industrial setting further illustrates the use of core traceability paths during production and measures the increase in performance of the development processes supported by our approach. These examples show that our approach can be successfully used to support both product and process traceability in a pragmatic yet efficient way.     

A type-centric framework for specifying heterogeneous, large-scale, component-oriented, architectures

Maintaining integrity and consistency, and effecting conformance in architectures of large-scale systems require specification and enforcement of many different forms of structural constraints. While type systems have proved effective for enforcing structural constraints in programs and data structures, most architectural modeling frameworks include only weak notions of typing or rely on first order logic constraint languages that have steep learning curves associated with them and that become unwieldy when scaling to large systems.We present the Cadena Architecture Language with Meta-modeling (CALM) — that uses multi-level type systems to specify and enforce a variety of architectural constraints relevant to the development of large-scale component-based systems. Cadena is a robust and extensible tool that has been used to specify a number of industrial strength component models and applied in multiple industrial research projects on model-driven development and software product lines.     

Multifunctional software systems: Structured modeling and specification of functional requirements

This paper deals with the structured specification of interface behavior of multifunctional systems, which are systems that offer a variety of functions for different purposes and use cases. It introduces a theory and first concepts of a methodology for the identification, structured modeling, and formalization of functional requirements of multifunctional systems. Service hierarchies specify multifunctional systems in terms of their provided sub-functions called services together with their mutual relationships and dependencies. A service hierarchy describes the functionality of multifunctional systems in a structured way. Each service is specified independently and the specification is added to the service hierarchy. Modes help to specify the feature interactions and by that functional dependencies between the services. The approach is based on the Focus theory for modeling interface behavior and services.     

VbTrace: using view-based and model-driven development to support traceability in process-driven SOAs

In process-driven, service-oriented architectures, there are a number of important factors that hinder the traceability between design and implementation artifacts. First of all, there are no explicit links between process design and implementation languages not only due to the differences of syntax and semantics but also the differences of granularity. The second factor is the complexity caused by tangled process concerns that multiplies the difficulty of analyzing and understanding the trace dependencies. Finally, there is a lack of adequate tool support for establishing and maintaining the trace dependencies between process designs and implementations. We present in this article a view-based, model-driven traceability approach that tackles these challenges. Our approach supports (semi-)automatically eliciting and (semi-)formalizing trace dependencies among process development artifacts at different levels of granularity and abstraction. A proof-of-concept tool support has been realized, and its functionality is illustrated via an industrial case study.     

Model-based pairwise testing for feature interaction coverage in software product line engineering

Testing software product lines (SPLs) is very challenging due to a high degree of variability leading to an enormous number of possible products. The vast majority of today??s testing approaches for SPLs validate products individually using different kinds of reuse techniques for testing. Because of their reusability and adaptability capabilities, model-based approaches are suitable to describe variability and are therefore frequently used for implementation and testing purposes of SPLs. Due to the enormous number of possible products, individual product testing becomes more and more infeasible. Pairwise testing offers one possibility to test a subset of all possible products. However, according to the best of our knowledge, there is no contribution discussing and rating this approach in the SPL context. In this contribution, we provide a mapping between feature models describing the common and variable parts of an SPL and a reusable test model in the form of statecharts. Thereby, we interrelate feature model-based coverage criteria and test model-based coverage criteria such as control and data flow coverage and are therefore able to discuss the potentials and limitations of pairwise testing. We pay particular attention to test requirements for feature interactions constituting a major challenge in SPL engineering. We give a concise definition of feature dependencies and feature interactions from a testing point of view, and we discuss adequacy criteria for SPL coverage under pairwise feature interaction testing and give a generalization to the T-wise case. The concept and implementation of our approach are evaluated by means of a case study from the automotive domain.     

Integration of DFDs into a UML-based Model-driven Engineering Approach

The main aim of this article is to discuss how the functional and the object-oriented views can be inter-played to represent the various modeling perspectives of embedded systems. We discuss whether the object-oriented modeling paradigm, the predominant one to develop software at the present time, is also adequate for modeling embedded software and how it can be used with the functional paradigm. More specifically, we present how the main modeling tool of the traditional structured methods, data flow diagrams, can be integrated in an object-oriented development strategy based on the unified modeling language. The rationale behind the approach is that both views are important for modeling purposes in embedded systems environments, and thus a combined and integrated model is not only useful, but also fundamental for developing complex systems. The approach was integrated in a model-driven engineering process, where tool support for the models used was provided. In addition, model transformations have been specified and implemented to automate the process. We exemplify the approach with an IPv6 router case study.This article is an extension of two papers [1,2] published in the proceedings of IEEE International Conference and Workshop on the Engineering of Computer Based Systems (ECBS 2004).     

Variability extraction and modeling for product variants

Fast-changing hardware and software technologies in addition to larger and more specialized customer bases demand software tailored to meet very diverse requirements. Software development approaches that aim at capturing this diversity on a single consolidated platform often require large upfront investments, e.g., time or budget. Alternatively, companies resort to developing one variant of a software product at a time by reusing as much as possible from already-existing product variants. However, identifying and extracting the parts to reuse is an error-prone and inefficient task compounded by the typically large number of product variants. Hence, more disciplined and systematic approaches are needed to cope with the complexity of developing and maintaining sets of product variants. Such approaches require detailed information about the product variants, the features they provide and their relations. In this paper, we present an approach to extract such variability information from product variants. It identifies traces from features and feature interactions to their implementation artifacts, and computes their dependencies. This work can be useful in many scenarios ranging from ad hoc development approaches such as clone-and-own to systematic reuse approaches such as software product lines. We applied our variability extraction approach to six case studies and provide a detailed evaluation. The results show that the extracted variability information is consistent with the variability in our six case study systems given by their variability models and available product variants.     

On the modeling and generation of service-oriented tool chains

Tool chains have grown from ad-hoc solutions to complex software systems, which often have a service-oriented architecture. With service-oriented tool integration, development tools are made available as services, which can be orchestrated to form tool chains. Due to the increasing sophistication and size of tool chains, there is a need for a systematic development approach for service-oriented tool chains. We propose a domain-specific modeling language (DSML) that allows us to describe the tool chain on an appropriate level of abstraction. We present how this language supports three activities when developing service-oriented tool chains: communication, design and realization. A generative approach supports the realization of the tool chain using the service component architecture. We present experiences from an industrial case study, which applies the DSML to support the creation of a service-oriented tool chain. We evaluate the approach both qualitatively and quantitatively by comparing it with a traditional development approach.     

面向软件产品家族的变化性建模方法

用户需求和运行环境的变化增加了软件产品开发、维护和演化的难度.另一方面,如果能对同类软件(比如软件产品家族)的变化性实施有效的控制,则可以极大地促进软件复用,提高软件生产效率和质量.对变化性建模是控制变化性的有效手段,既有助于变化性的识别和规约,又能够提供足够的机制支持变化性的演化.提出了一种面向产品家族的变化性建模方法,以变化性的管理策略为指导,从扩展的用况(use case)模型入手捕获系统行为的变化性,以特征模型来组织功能性需求和质量属性并识别其变化性,两种模型对变化性的建模采用相同的机制.还结合一个实例讨论了产品家族变化性建模的全过程.该研究对产品家族变化性的分析与建模具有一定的参考作用.     

Knowledge and software modeling using UML

Ontology can be considered as a comprehensive knowledge model which enables the developer to practice knowledge, instead of code, reuse. In the development of knowledge-based systems, different modeling languages are employed at different stages of the development process. By using a common modeling language for the knowledge and software models, knowledge instead of software reuse can be achieved. We illustrate the process by first presenting an ontology developed for an industrial domain and then investigate Unified Modeling Language (UML) as an ontology modeling tool. Since any model expressed in UML can be translated into a software model, the transition from the knowledge model to system implementation is better supported with the proposed approach. The industrial domain of selecting a remediation technique for petroleum contaminated sites is adopted for the illustration case study.