Subconjuntos Mínimos de Corrección para explicar características muertas en Modelos de Líneas de Productos. El caso de los Modelos de Características

Aprovechar los beneficios que ofrecen las líneas de productos depende, entre otros aspectos, de la calidad de los modelos que representan cada línea de productos. Una parte de la calidad consiste en asegurar que los Modelos de Líneas de Productos (MLPs) se encuentran libres de defectos. Un tipo de defecto de los MLPs son las características muertas, ellas son elementos reutilizables que no están presente en ningún producto configurado a partir del MLPs. Cuando las características muertas aparecen, quien crea los MLPs necesita herramientas que le permitan identificar por qué se presentan las características muertas y cómo podría corregirse el modelo. Sin embargo, aunque muchos trabajos en la literatura identifican características muertas, pocos explican por qué se originan o lo explican de manera incompleta. En este artículo se propone un nuevo método para explicar por qué se presentan características muertas en un MLP expresado con la notación modelos de características. Nuestra explicación consiste en identificar diferentes subconjuntos de elementos que podrían ser modificados para corregir el modelo cada que se presente una característica muerta. Esta explicación ofrece al modelador información completa sobre cómo corregir el modelo para cada característica muerta encontrada

Towards Highly Scalable Runtime Models with History

Advanced systems such as IoT comprise many heterogeneous, interconnected, and autonomous entities operating in often highly dynamic environments. Due to their large scale and complexity, large volumes of monitoring data are generated and need to be stored, retrieved, and mined in a time- and resource-efficient manner. Architectural self-adaptation automates the control, orchestration, and operation of such systems. This can only be achieved via sophisticated decision-making schemes supported by monitoring data that fully captures the system behavior and its history. Employing model-driven engineering techniques we propose a highly scalable, history-aware approach to store and retrieve monitoring data in form of enriched runtime models. We take advantage of rule-based adaptation where change events in the system trigger adaptation rules. We first present a scheme to incrementally check model queries in the form of temporal logic formulas which represent the conditions of adaptation rules against a runtime model with history. Then we enhance the model to retain only information that is temporally relevant to the queries, therefore reducing the accumulation of information to a required minimum. Finally, we demonstrate the feasibility and scalability of our approach via experiments on a simulated smart healthcare system employing a real-world medical guideline.Comment: 8 pages, 4 figures, 15th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS2020

Consistency-Preserving Evolution Planning on Feature Models

A software product line (SPL) enables large-scale reuse in a family of related software systems through configurable features. SPLs represent a long-term investment so that their ongoing evolution becomes paramount and requires careful planning. While existing approaches enable to create an evolution plan for an SPL on feature-model (FM) level, they assume the plan to be rigid and do not support retroactive changes. In this paper, we present a method that enables to create and retroactively adapt an FM evolution plan while preventing undesired impacts on its structural and logical consistency. This method is founded in structural operational semantics and linear temporal logic. We implement our method using rewriting logic, integrate it within an FM tool suite and perform an evaluation using a collection of existing FM evolution scenarios

Analysis as first-class citizens – an application to Architecture Description Languages

Architecture Description Languages (ADLs) support modeling and analysis of systems through models transformation and exploration. Various contributions made proposals to bring verification capabilities to designers through model-based frame- works and illustrated benefits to the overall system quality. Model-level analyses are usually performed as an exogenous, unidirectional and semantically weak transformation towards a third-party model. We claim such process can be incomplete and/or inefficient because gathered results lead to evolution of the primary model. This is particularly problematic for the design of Distributed Real-Time Embedded (DRE) systems that has to tackle many concerns like time, security or safety. In this paper, we argue why analysis should no longer be considered as a side step in the design process but, rather, should be embedded as a first-class citizen in the model itself. We review several standardized architecture description languages, which consider analysis as a goal. As an element of solution, we introduce current work on the definition of a language dedicated to the analysis of models within the scope of one particular ADL, namely the Architecture Analysis and Design Language (AADL)

Static analysis techniques to verify mutual exclusion situations within SysML models

AVATAR is a real-time extension of SysML supported by the TTool open-source toolkit. So far, formal verification of AVATAR models has relied on reachability techniques that face a state explosion problem. The paper explores a new avenue: applying structural analysis to AVATAR model, so as to identify mutual exclusion situations. In practice, TTool translates a subset of an AVATAR model into a Petri net and solves an equation system built upon the incidence matrix of the net. TTool implements a push-button approach and displays verification results at the AVATAR model level. The approach is not restricted to AVATAR and may be adapted to other UML profiles

Modeling and verification of Functional and Non-Functional Requirements of ambient Self-Adaptive Systems

International audienceSelf-Adaptive Systems modify their behavior at run-time in response to changing environmental conditions. For these systems, Non-Functional Requirements play an important role, and one has to identify as early as possible the requirements that are adaptable. We propose an integrated approach for modeling and verify- ing the requirements of Self-Adaptive Systems using Model Driven Engineering techniques. For this, we use Relax, which is a Requirements Engineering language which introduces flexibility in Non-Functional Require- ments. We then use the concepts of Goal-Oriented Requirements Engineering for eliciting and modeling the requirements of Self-Adaptive Systems. For properties verification, we use OMEGA2/IFx profile and toolset. We illustrate our proposed approach by applying it on an academic case study

Reflecting on the past and the present with temporal graph-based models

Self-adaptive systems (SAS) need to reflect on the current environment conditions, their past and current behaviour to support decision making. Decisions may have different effects depending on the context. On the one hand, some adaptations may have run into difficulties. On the other hand, users or operators may want to know why the system evolved in a certain direction. Users may just want to know why the system is showing a given behaviour or has made a decision as the behaviour may be surprising or not expected. We argue that answering emerging questions related to situations like these requires storing execution trace models in a way that allows for travelling back and forth in time, qualifying the decision making against available evidence. In this paper, we propose temporal graph databases as a useful representation for trace models to support self-explanation, interactive diagnosis or forensic analysis. We define a generic meta-model for structuring execution traces of SAS, and show how a sequence of traces can be turned into a temporal graph model. We present a first version of a query language for these temporal graphs through a case study, and outline the potential applications for forensic analysis (after the system has finished in a potentially abnormal way), self-explanation, and interactive diagnosis at runtime

Project Final Report Use and Dissemination of Foreground

This document is the final report on use and dissemination of foreground, part of the CONNECT final report. The document provides the lists of: publications, dissemination activities, and exploitable foregroun