International audience

International audience

Abstract Data interoperability implies data exchanges among intra and inter enterprises collaborating with information systems (IS). The multiplicity of these exchanges and the increasing number of data exchanged generates complexity and brings out the needs for control to avoid dysfunctions with a negative impact on the overall performance of the systems. Indeed, actually, interoperability has become a necessary performance lever that thus requires particular attention. Being at a low level in the enterprise interoperability concerns, data interoperability is mainly automated, which leads us to question: Is it possible to evaluate data interoperability performance and security based on inspection and analysis of ongoing data exchanges? We therefore endeavored to answer this question by establishing monitoring and analysis systems. In this paper, we present a research work which addresses services provided by a messaging‐based communication system. In order to collect information on Information System interactions allowing one to assess their level of data interoperability, we propose a messaging metamodel that aggregates the collected information. It provides a single point of control and enables one to determine indicators of potential interoperability problems. The approach is validated on two case studies. An industrial case study of interactions among existing systems is presented to showcase the feasibility and interest of the approach. It is proposed on top of RabbitMQ and allows our partner to identify some issues in the studied information system. The second case study shows that the approach can integrate other protocols, by reading MQTT messages. The approach is implemented using Moose, a software analysis platform.

International audience

Performance benchmarking has become an important topic within robotics. It is indeed, a critical way to compare different solutions under different conditions. In this paper, we focus on performance benchmarking of multi-robot systems which explore and map unknown terrains. We present a collection of metrics to objectively compare different algorithms that can be applied to collaborative multi-robot exploration. We also identify parameters that impact robotic fleet performances. By varying the parameters, we can identify strengths and limits of an algorithm. This work is also a first concrete step to address the general problem of objectively comparing different multi-robot coordination algorithms. We illustrate these contributions with realistic simulations of the frontier-based exploration strategy. The simulations were implemented in ROS, which enables to uncouple the control software from the drivers of the robot body. We can therefore use the same code on both simulation and real robots.

SUMMARY Dependency structural matrix (DSM) is an approach originally developed for process optimization. It has been successfully applied to identify software dependencies among packages and subsystems. A number of algorithms have been proposed to compute the matrix so that it highlights patterns and problematic dependencies between subsystems. However, existing DSM implementations often miss important information to fully support reengineering effort. For example, they do not clearly qualify and quantify problematic relationships, information that is crucial to support remediation tasks. We propose enriched DSM (eDSM), which provides small‐multiple views and micro–macro‐readings by adding fine‐grained information in each cell of the matrix. Each cell is enriched with contextual information about (i) the type of dependencies (inheritance, class reference, etc.), (ii) the proportion of referencing entities, and (iii) the proportion of referenced entities. We distinguish independent cycles and stress potentially simple fixes for cycles by using coloring information. This work is language independent and has been implemented on top of the Moose software analysis platform. In this paper, we expand our previous work. We improved the cell content information view on the basis of user feedback and performed multiple validations: two different case studies on Moose and Seaside software; one user study for validating eDSM as a usable approach for developers. Solutions to problems identified with eDSM have been performed and retrofitted in analyzed software. Copyright © 2012 John Wiley & Sons, Ltd.

Mobile autonomous robots are progressively entering the mass market. Thus, manufacturers have to perform quality assurance tests on series of robots. Therefore, tests should be repeatable and as much automated as possible. Tests are also performed for purpose of repairing robots. This calls for reusing tests already defined for quality assurance. In this paper we introduce a methodology to support the definition of repeatable, reusable, semi-automated tests. Our methodology describes the process of conducting tests in a way that maximizes safety for human operators, while avoiding to damage tested robots.

SUMMARY With the growing need for quality assessment of entire software systems in the industry, new issues are emerging. First, because most software quality metrics are defined at the level of individual software components, there is a need for aggregation methods to summarize the results at the system level. Second, because a software evaluation requires the use of different metrics, with possibly widely varying output ranges, there is a need to combine these results into a unified quality assessment. In this paper we derive, from our experience on real industrial cases and from the scientific literature, requirements for an aggregation method. We then present a solution through the Squale model for metric aggregation, a model specifically designed to address the needs of practitioners. We empirically validate the adequacy of Squale through experiments on Eclipse. Additionally, we compare the Squale model to both traditional aggregation techniques (e.g., the arithmetic mean), and to econometric inequality indices (e.g., the Gini or the Theil indices), recently applied to aggregation of software metrics. Copyright © 2012 John Wiley & Sons, Ltd.

ISO 9126 promotes a three-level model of quality (factors, criteria, and metrics) which allows one to assess quality at the top level of factors and criteria. However, it is difficult to use this model as a tool to increase software quality. In the Squale model, we add practices as an intermediate level between metrics and criteria. Practices abstract away from raw information (metrics, tool reports, audits) and provide technical guidelines to be respected. Moreover, practice marks are adjusted using formulae to suit company development habits or exigences: for example bad marks are stressed to point to places which need more attention. The Squale model has been developed and validated over the last couple of years in an industrial setting with Air France-KLM and PSA Peugeot-Citroen.