Abstract Designing a database cost model is one of the main research topics related to the physical design phase. It follows the evolution of database technology in order to evaluate and quantify the performance metrics (e.g., response time, energy consumption, etc.). Therefore, it makes the community researchers sensitive to the generated results. However, reusing and comparing database cost models require extracting related information manually from the research publications. This process is error‐prone and time‐consuming. Unfortunately, many researchers claim the difficulty of surveying and reproducing cost models already published in several/journal articles and/or reports. This difficulty is due to the absence of a process describing the cost model itself formally as well as the context of its utilization. This article presents an approach enabling the extraction of cost models information (context, parameters, features, etc.) as a set of orchestrated services. These services are implemented using natural language processing and machine‐learning techniques via a work‐flow pipeline inspired by DevOps practices. We illustrate our approach on a case study to stress the feasibility and benefits of our proposal by emphasizing the reproduction and automatization facilities.

Autonomous vehicles, such as drones, are gaining great popularity due to their usability and versatility. Nowadays, a significant number of them operate using open source software, such as Robot Operating System (ROS) and the de facto standard MAVLink communication protocol, as they are free and many of them are reusable enough that they can be deployed in various different vehicles. Although these technologies offer a wide variety of resources, using them requires a reasonable background of programming and system engineering. Often, this is not achievable by common drone end-users in the short-term, as they would need to acquire a considerably large amount of know-how before working on specific domains. However, a graphical Domain Specific Modelling Language (DSML) might provide a shortcut to design drone missions using already known concepts to the end-users (or, at least, ones easier to learn). Pursuing this shortcut, RoBMEX is presented as a top-down methodology based on a set of domain specific languages able to enhance the autonomy of ROS-based systems, by allowing the creation of missions graphically, and then generating automatically executable source codes conforming to the designed missions.

In the domain of autonomous unmanned vehicles, some design patterns emerge from various distinct software designs. These patterns are the result of the search for modularity and, in consequence, customisation. They point to the possibility of a more general architecture and design process that are able to comply to at least most of design requirements made for unmanned vehicles, including regulatory ones. This paper explores the possibility of proposing this modular and customisable architecture as a simpler approach to responding to design requirements.

In safety-critical real-time systems domain, obtaining the appropriate operational model which meets the temporal (e.g. deadlines) and business (e.g. redundancy) requirements while being optimal in terms of several metrics is a primordial process in the design life-cycle. Recently, several researches have proposed to explore cross-domain trade-offs for a higher behaviour performance. Indeed, this process represents the first step in the deployment phase, which is very sensitive because it could be error-prone and time consuming.This paper is a work in progress proposing an approach aiming to help real-time system architects to take benefit from existing works, overcome their limits, and capitalize the efforts. Furthermore, the approach is based on the model-driven engineering paradigm and suggests to ease the usage of methods and tools thanks to repositories gathering them as a sort of a shared knowledge.

The idea of having drones into the national airspace raises serious concerns. These concerns are for nearly all spectrum of society which ranges from government facilities and aviation authorities to private citizens. To guarantee a high level of safety and security, drones must be implemented as highly constrained systems with a certain number of functions (technologies). In this paper, we identify the key technologies for drones based on their common and specific usages. These technologies are grouped into four categories: U-space capabilities, system functions, payloads, and tools. We also list the contributions of COMP4DRONES project in terms of improving technologies and easing drone customization including its safe operations.

The potential applications for drones, especially those in manned areas or into non-segregated airspace, are currently not possible without the development and validation of certain key enabling technologies: "detect and avoid", "air traffic management" and "command and control (C2) link". SESAR JU identified that issue has a high impact on European innovation, which demands R&D investments and incentives for the convergence of shared technologies and markets. The COMP4DRONES project complements SESAR JU efforts with a particular focus on safe software and hardware drone architectures. COMP4DRONES will bear a holistically designed ecosystem ranging from application to electronic components. The ecosystem aims at supporting (1) efficient customization and incremental assurance of drone-embedded platforms, (2) safe autonomous decision making concerning individual or cooperative missions, (3) trustworthy drone-to-drone and drone-to-ground communications even in presence of malicious attackers and under the intrinsic platform constraints, and (4) agile and cost-effective design and assurance of drone modules and systems. Lead applications driving ecosystem development and benchmarking on the fields of transport, inspection, logistic, precision agriculture, parcel delivery, among others, will be produced.

Real-time systems are used in many critical domains such as automotive, avionics and nuclear, therefore their temporal behavior needs to be checked rigorously. Many scheduling theory-based analysis tests have been proposed to validate the design of real-time systems. Since each given test is based on a set of assumptions, only the constrained system which satisfies these assumptions can be reliably verified by such a test. These assumptions do not depend on any design language but their interpretation does. Currently, these assumptions are often drowned in scientific paper discussions and expressed in natural languages. In this paper, we aim to make possible to define formally assumptions by real-time systems analysts without being expert of design languages. Indeed, we propose a domain specific language named IRL (Identification Rule Language). We show the benefit of such a language to capitalize efforts. That is, IRL allows to define analysis supports to help the timing verification community to share its knowledge and enables systems designers to use this knowledge easily.

Architecture Analysis and Design Language (AADL) is a standard in avionics system design. However, the communication patterns provided by AADL are not sufficient to the current context of Real-Time Embedded System (RTES) in which some multi-periodic communication patterns may occur. We propose an extension of a precedence model between tasks of different periods (multiperiodic communication). This relies on the Semaphore Precedence Constraint (SPC) model that is inspired from the concept of Semaphore, and more specifically on the m-n producer/consumer paradigm. We reinforce the SPC semantics by allowing cycles in the SPC precedence graph. We also present another viewpoint on the periodicity of tasks system using SPC based on a graph apart from the encoding technique presented in the SPC seminal work. An implementation of SPC in AADL and its associated analysis tool are also provided to study the temporal behaviour of systems using SPC.

Decision support systems (DSS) become more and more complex to deal with decision-making problems related to the current conjuncture. Several agent-oriented methodologies have been proposed to design distributed decision support systems and improve the decision process. This paper presents a comparative study of these existing methodologies (based on a set of relevant criteria like the adaptability, reliability and decision objective) and identifies a set of issues, notably the lack of faults tolerance mechanism and the absence of the formal verification. Hence, we propose a work-in-progress approach (also based on multi-agent paradigm) called ADS2adapted for distributed decision support systems. We also present how ADS2will allow to remove the global control, to reinforce the adaptability and to reduce developers burden thanks to the utilization of model-driven engineering settings.

Real-Time Systems are subject to temporal requirements. To check if these latter are met, performance analysis tests are required. However, the performance analysis through model-based process is still difficult due to (i) the complexity of real-time systems (ii) and the lack of methodologies enabling to leverage performance tests to be applied easily to design models.In this paper, we focus on the temporal scheduling analysis of distributed systems with real-time networks. We present an extension of a pivot scheduling analysis aware methodology in order to explicit the analysis models. That is, we propose a modeling viewpoint dedicated to distributed real-time systems in order to bridge the semantic gap between system design and analysis techniques of real-time networks.Our proposed extension has been implemented and integrated in a modeling framework dedicated to the schedulability analysis. The paper also contains a case study that stresses the contribution and shows its usefulness.

The development of database systems and applications requires the use of metrics to evaluate the quality and the efficiency of each phase, especially as regards the physical phase, where logical, physical and hardware optimizations are mainly used. Since the 1980s, a large range of cost models has been proposed. Each cost model is dedicated to the calculation of specific metrics and mainly pertains to specific target database, the workload, Database Management Systems (DBMS), deployment platforms, etc. Augmenting and improving reuse in complex systems is increasingly recognized as a crucial as it contributes to increasing the quality of the target systems, shortening engineering development time, and to paring down costs for the engineering of typically highly customer-specific solutions. In this paper, we propose a cost models language called CostDL that allows the description of metrics related to the most sensitive database system characteristics. An implementation of CostDL and its usage through a running example are also provided.

We are currently witnessing an explosion of advances in database technology, that cover all phases of database application design: non-functional requirements, conceptual modeling, logical modeling, deployment, physical design and exploitation. Researchers and engineers cooperate to integrate these advances in the database design. Their proposed solutions have to be confronted with similar studies whose results have been either published in scientific papers or on specific websites such as that of TPC (the Transaction Processing Council). Recently, several researchers have highlighted difficulties in reproducing the results of existing studies. As a consequence, certain research communities require that the environment and the results of the testing activities have to be published in order to facilitate their reproduction, to publish their simulator environments, in order to allow evaluators to perform by their own the experiments. This is quite similar to the Volkswagen fake pollution controls scandal. In this paper, we firstly, advocate the transparency of testing in the database field. Secondly, we propose the use of a repository dedicated to store testing environment and results. The environment includes used data sets, deployment platform, non-functional requirements, used algorithms, hypotheses, etc. and the results completed with their measurement units.

To fill the gap between the modeling of real-time systems and the scheduling analysis, we propose a framework that supports seamlessly the two aspects: (1) modeling a system using a methodology, in our case study, the Architecture Analysis and Design Language (AADL), and (2) helping to easily check temporal requirements (schedulability analysis, worst-case response time, sensitivity analysis, etc.). We introduce the usefulness of an intermediate framework called MoSaRT, which supports a rich semantic concerning temporal analysis. We show with a case study how the input model is transformed into a MoSaRT model, and how our framework is able to generate the proper models as inputs to several classic temporal analysis tools.