A systematic literature review on the description of software architectures for systems of systems

Guessi, Milena; Neto, Valdemar Vicente Graciano; Bianchi, Thiago; Felizardo, Katia Romero; Oquendo, Flávio; Nakagawa, Elisa Yumi

doi:10.1145/2695664.2695795

Cited by 56 publications

(48 citation statements)

References 28 publications

(33 reference statements)

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“…However, software has become a ubiquitous element in SoS as constituents embed software and become smarter. Hence, the interest in development of software for SoS has grown up, raising a new area of investigation termed Software Engineering for SoS (SESoS) [4,6,16]. Among these techniques, patterns are examples of popular software engineering techniques that can bring productivity and quality for SESoS.…”

Section: Foundationsmentioning

confidence: 99%

Externalizing patterns for simulations in software engineering of systems-of-systems

Neto

Manzano

Rohling³

et al. 2018

Proceedings of the 33rd Annual ACM Symposium on Applied Computing

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Systems-of-Systems (SoS) often support critical domains. They must be trustworthy, i.e., they must keep their operation in progress, being not subject to failures, as they can cause potential damages and hazards to human integrity. Simulations are a recurrent approach in SoS development, as they can anticipate potential failures, consequently increasing the level of trustworthiness and quality exhibited by a SoS. Nevertheless, simulation is still software and demands engineering. Moreover, many simulation formalisms are not trivial of specifying, sometimes tangling software an hardware details to program an executable simulation. Thus, the aim of this paper is contributing for software engineering of SoS by externalizing two patterns for the conception of SoS simulations. We evaluated our patterns by applying them in a case study in two different domains. For both, patterns were successfully applied during automatic generation of functional code, supporting the execution of SoS simulations and prediction of SoS behavior at design-time.

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Section: Foundationsmentioning

confidence: 99%

Externalizing patterns for simulations in software engineering of systems-of-systems

Neto

Manzano

Rohling³

et al. 2018

Proceedings of the 33rd Annual ACM Symposium on Applied Computing

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“…To establish the basis of Stimuli-SoS, we decided to use a SoS architectural model to derive stimuli generators for a SoS simulation via a model transformation. We surveyed the literature to find a formalism that could properly support SoS software architecture modeling and simulation [49]. For this purpose, such formalism should meet the following language requirements, supporting:…”

Section: Presentation Of Stimuli-sosmentioning

confidence: 99%

“…The following modeling languages have been identified as the key ones used for SoS architecture description: Darwin (semi-formal) [50], Wright (formal) [51], π-ADL (formal) [52], UML 2 (semi-formal), SySML 3 (semi-formal), and SoSADL [8] [49].…”

Section: Presentation Of Stimuli-sosmentioning

confidence: 99%

Stimuli-SoS: a model-based approach to derive stimuli generators for simulations of systems-of-systems software architectures

et al. 2017

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Background: Systems-of-systems (SoS) are alliances of independent and interoperable software-intensive systems. SoS often support critical domains, being required to exhibit a reliable operation, specially because people's safety relies on their services. In this direction, simulations enable the validation of different operational scenarios in a controlled environment, allowing a benchmarking of its response as well as revealing possible breaches that could lead to failures. However, simulations are traditionally manual, demanding a high level of human intervention, being costly and error-prone. A stimuli generator could aid in by continuously providing data to trigger a SoS simulation and maintaining its operation. Methods: We established a model-based approach termed Stimuli-SoS to support the creation of stimuli generators to be used in SoS simulations. Stimuli-SoS uses software architecture descriptions for automating the creation of such generators. Specifically, this approach transforms SoSADL, a formal architectural description language for SoS, into dynamic models expressed in DEVS, a simulation formalism. We carried out a case study in which Stimuli-SoS was used to automatically produce stimuli generators for a simulation of a flood monitoring SoS. Results:We run simulations of a SoS architectural configuration with 69 constituent systems, i.e., 42 sensors, 9 crowdsourcing systems, and 18 drones. Stimuli generators were automatically generated for each type of constituent. These stimuli generators were capable of receiving the input data from the database and generating the expected stimuli for the constituents, allowing to simulate constituent systems interoperations into the flood monitoring SoS. Using Stimuli-SoS, we simulated 38 days of flood monitoring in little more than 6 h. Stimuli generators correctly forwarded data to the simulation, which was able to reproduce 29 flood alerts triggered by the SoS during a flooding event. In particular, Stimuli-SoS is almost 65 times more productive than a manual approach to producing data for the same type of simulation. Conclusions: Our approach succeeded in automatically deriving a functional stimuli generator that can reproduce environmental conditions for simulating a SoS. In particular, we presented new contributions regarding productivity and automation for the use of a model-based approach in SoS engineering.

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“…Modeling languages (such as UML 2 , SysML 3 , and CML 4 ) support both representation and validation of static properties of the SoS. However, they lack mechanisms to capture SoS dynamics, hampering evaluation of the operation of SoS [8]. Simulations provide the means to evaluate SoS operation by anticipating failures and unveiling dynamic aspects of systems' operation [5,13,17].…”

Section: Introductionmentioning

confidence: 99%

ASAS: An Approach to Support Simulation of Smart Systems

Neto¹,

Garcés²,

Guessi³

et al. 2018

Proceedings of the 51st Hawaii International Conference on System Sciences

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Smart systems, such as smart cities, smart buildings, and autonomous cars, have recently gained increasing popularity. Each such system is essentially a System-of-Systems (SoS). SoS are dynamically established as alliances among independent and heterogeneous software systems to offer complex functionalities as a result of constituents interoperability. An SoS often supports critical application domains, and, as such, must be reliable. Many SoS have been specified and evaluated for their correct operation using static models. However, specification languages have not supported to capture their inherent dynamic nature nor enabled to monitor their operation. The main contribution of this paper is to present ASAS, an approach to Automatically generate Simulation models for smArt Systems (ASAS) in order to support evaluation of their operation. In particular, our approach makes it possible to transform formal models of the SoS architecture (expressed in SoSADL) into simulation models (expressed in DEVS). We evaluated our approach by conducting two case studies using a flood monitoring system that is intended to be part of a smart city. Results indicate that ASAS can successfully generate functional simulations for the SoS operation, which in turn can enable to reason and monitor an SoS operation, taking into account its dynamic nature.

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A systematic literature review on the description of software architectures for systems of systems

Cited by 56 publications

References 28 publications

Externalizing patterns for simulations in software engineering of systems-of-systems

Externalizing patterns for simulations in software engineering of systems-of-systems

Stimuli-SoS: a model-based approach to derive stimuli generators for simulations of systems-of-systems software architectures

ASAS: An Approach to Support Simulation of Smart Systems

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