Salvador Trujillo

Feature Oriented Model Driven Development: A Case Study for Portlets

Model driven development (MDD) is an emerging paradigm for software construction that uses models to specify programs, and model transformations to synthesize executables. Feature oriented programming (FOP) is a paradigm for software product lines where programs are synthesized by composing features. feature oriented model driven development (FOMDD) is a blend of FOP and MDD that shows how products in a software product line can be synthesized in an MDD way by composing features to create models, and then transforming these models into executables. We present a case study of FOMDD on a product line of portlets, which are components of web portals. We reveal mathematical properties of portlet synthesis that helped us to validate the correctness of our abstractions, tools, and specifications, as well as optimize portlet synthesis.

Software diversity: state of the art and perspectives

Diversity is prevalent in modern software systems to facilitate adapting the software to customer requirements or the execution environment. Diversity has an impact on all phases of the software development process. Appropriate means and organizational structures are required to deal with the additional complexity introduced by software variability. This introductory article to the special section “Software Diversity—Modeling, Analysis and Evolution” provides an overview of the current state of the art in diverse systems development and discusses challenges and potential solutions. The article covers requirements analysis, design, implementation, verification and validation, maintenance and evolution as well as organizational aspects. It also provides an overview of the articles which are part of this special section and addresses particular issues of diverse systems development.

Model Superimposition in Software Product Lines

In software product line engineering, feature composition generates software tailored to specific requirements from a common set of artifacts. Superimposition is a technique to merge code pieces belonging to different features. The advent of model-driven development raises the question of how to support the variability of software product lines in modeling techniques. We propose to use superimposition as a model composition technique in order to support variability. We analyze the feasibility of superimposition for model composition, offer corresponding tool support, and discuss our experiences with three case studies (including an industrial case study).

Feature refactoring a multi-representation program into a product line

Feature refactoring is the process of decomposing a program into aset of modules, called features, that encapsulate increments in program functionality. Different compositions of features yield different programs. As programs are defined using multiple representations, such as code, makefiles, and documentation, feature refactoring requires all representations to be factored. Thus, composing features produces consistent representations of code, make files, documentation, etc. for a target program. We present acase study of feature refactoring a substantial tool suite that usesmultiple representations. We describe the key technical problems encountered, and sketch the tool support needed for simplifying such refactorings in the future.

Guaranteeing Syntactic Correctness for All Product Line Variants: A Language-Independent Approach

A software product line (SPL) is a family of related program variants in a well-defined domain, generated from a set of features. A fundamental difference from classical application development is that engineers develop not a single program but a whole family with hundreds to millions of variants. This makes it infeasible to separately check every distinct variant for errors. Still engineers want guarantees on the entire SPL. A further challenge is that an SPL may contain artifacts in different languages (code, documentation, models, etc.) that should be checked. In this paper, we present CIDE, an SPL development tool that guarantees syntactic correctness for all variants of an SPL. We show how CIDE’s underlying mechanism abstracts from textual representation and we generalize it to arbitrary languages. Furthermore, we automate the generation of plug-ins for additional languages from annotated grammars. To demonstrate the language-independent capabilities, we applied CIDE to a series of case studies with artifacts written in Java, C++, C, Haskell, ANTLR, HTML, and XML.

On refining XML artifacts

Step-wise refinement is a powerful paradigm for developing a complex program from a simple program by adding features incrementally where each feature is an increment in program functionality. Existing works focus on object-oriented representations such as Java or C++ artifacts. For this paradigm to be brought to the Web, refinement should be realised for XML representations. This paper elaborates on the notion of XML refinement by addressing what and how XML can be refined. These ideas are realised in the XAK language. A Struts application serves to illustrate the approach.

Generative metaprogramming

Recent advances in Software Engineering have reduced the cost of coding programs at the expense of increasing the complexity of program synthesis, i.e. metaprograms, which when executed, will synthesize a target program. The traditional cycle of configuring-linking-compiling, now needs to be supplemented with additional transformation steps that refine and enhance an initial specification until the target program is obtained. So far, these synthesis processes are based on error-prone, hand-crafted scripting. To depart from this situation, this paper addresses generative metaprogramming, i.e. the generation of program-synthesis metaprograms from declarative specifications. To this end, we explore (i) the (meta) primitives for program synthesis, (ii) the architecture that dictates how these primitives can be intertwined, and (iii) the declarative specification of the metaprogram from which the code counterpart is generated.

Context-Aware Staged Configuration of Process Variants@Runtime

Process-based context-aware applications are increasingly becoming more complex and dynamic. Besides the large sets of process variants to be managed in such dynamic systems, process variants need to be context sensitive in order to accommodate new user requirements and intrinsic complexity. This paradigm shift forces us to defer decisions to runtime where process variants must be customized and executed based on a recognized context. However, there exists a lack of deferral of the entire process variant configuration and execution to perform an automated decision of subsequent variation points at runtime. In this paper, we present a holistic methodology to automatically resolve process variability at runtime. The proposed solution performs a staged configuration considering static and dynamic context data to accomplish effective decision making. We demonstrate our approach by exemplifying a storage operation process in a smart logistics scenario. Our evaluation demonstrates the performance and scalability results of our methodology.

Supporting production strategies as refinements of the production process

The promotion of a clear separation between artifact construction and artifact assembling is one of the hallmarks of software product lines. This work rests on the assumption that the mechanisms for producing products considerably quicker, cheaper or at a higher quality, rest not only on the artifacts but on the assembling process itself. This leads to promoting production processes as “first-class artifacts”, and as such, liable to vary to accommodate distinct features. Production process variability and its role to support either production features or production strategies are analyzed. As prove of concept, the AHEAD Tool Suite is used to support a sample application where features require variations on the production process.

Context variability modeling for runtime configuration of service-based dynamic software product lines

In emerging domains such as Cloud-based Industrial Control Systems (ICSs) and SCADA systems where data-intensive and high performance computing are needed, a higher degree of flexibility is being demanded to meet new stakeholder requirements, context changes and intrinsic complexity. In this light, Dynamic Software Product Lines (DSPLs) provide a way to build self-managing systems exploiting traditional product line engineering concepts at runtime. Although context-awareness is widely perceived to be a first-class concern in such runtime variability mechanisms, existing approaches do not provide the necessary level of formalization to model and enact context variability for DSPLs. This is crucial for operational analytics processes since variant configuration could differ from context to context depending on diverse data values linked to context features and cross-tree constraints in a feature model. In this paper, we propose a context variability modeling approach, demonstrate its applicability and usability via a wind farm use case, and present the fundamental building blocks of a framework for enabling context variability in service-based DSPLs which provide Workflow as a Service (WFaaS).