D. D. Ruscio, I. Malavolta, Patrizio Pelliccione, Massimo Tivoli
Drones are increasingly popular since they promise to simplify a myriad of everyday tasks. Currently vendors provide low-level APIs and basic primitives to program drones, making mission development a task-specific and error-prone activity. As a consequence, current approaches are affordable only for users that have a strong technical expertise. Then, it emerges the need for software engineering techniques supporting the definition, development, and realization of missions involving swarms of autonomous drones while guaranteeing the safety today's users expect. In this paper we consider mission specifications expressed through a domain-specific modeling language which can be effectively used by end-users with no technical expertise, e.g., firefighters and rescue workers. Our generation method automatically derives the lower level logic that each drone must perform to accomplish the specified mission, prevents collisions between drones and obstacles, and ensures the preservation of no-fly zones.
{"title":"Automatic generation of detailed flight plans from high-level mission descriptions","authors":"D. D. Ruscio, I. Malavolta, Patrizio Pelliccione, Massimo Tivoli","doi":"10.1145/2976767.2976794","DOIUrl":"https://doi.org/10.1145/2976767.2976794","url":null,"abstract":"Drones are increasingly popular since they promise to simplify a myriad of everyday tasks. Currently vendors provide low-level APIs and basic primitives to program drones, making mission development a task-specific and error-prone activity. As a consequence, current approaches are affordable only for users that have a strong technical expertise. Then, it emerges the need for software engineering techniques supporting the definition, development, and realization of missions involving swarms of autonomous drones while guaranteeing the safety today's users expect. In this paper we consider mission specifications expressed through a domain-specific modeling language which can be effectively used by end-users with no technical expertise, e.g., firefighters and rescue workers. Our generation method automatically derives the lower level logic that each drone must perform to accomplish the specified mission, prevents collisions between drones and obstacles, and ensures the preservation of no-fly zones.","PeriodicalId":179690,"journal":{"name":"Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115434496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Martial Chabot, L. Pierre, Alexandre Nabais-Moreno
In cyber-physical systems, the operations of various physical entities are controlled by computing cores. Therefore the design of these systems involves multi-disciplinary teams, for the development of the electronic devices and embedded firmware, but also for the design of the physical components (with mechanical, electrical, thermal, electromagnetic features). This intimate coupling of disparate elements makes correctness analysis very complex. Composite requirements have to be verified. In many application domains some of these requirements come from standardization documents, e.g., for systems that have to conform to IEC standards. One of the main challenges is to make the variety of experts coordinate towards the satisfaction of these requirements, in spite of the fact that they are accustomed to focusing on their domain-specific issues, with their specialized tools. The aim of the method proposed here is to provide a unified testing framework to enable the validation of cross-disciplinary requirements. Since we target a general-purpose solution, usable by all disciplines, the method is specified using an abstract modeling language, namely SysML.
{"title":"A requirement driven testing method for multi-disciplinary system design","authors":"Martial Chabot, L. Pierre, Alexandre Nabais-Moreno","doi":"10.1145/2976767.2976795","DOIUrl":"https://doi.org/10.1145/2976767.2976795","url":null,"abstract":"In cyber-physical systems, the operations of various physical entities are controlled by computing cores. Therefore the design of these systems involves multi-disciplinary teams, for the development of the electronic devices and embedded firmware, but also for the design of the physical components (with mechanical, electrical, thermal, electromagnetic features). This intimate coupling of disparate elements makes correctness analysis very complex. Composite requirements have to be verified. In many application domains some of these requirements come from standardization documents, e.g., for systems that have to conform to IEC standards. One of the main challenges is to make the variety of experts coordinate towards the satisfaction of these requirements, in spite of the fact that they are accustomed to focusing on their domain-specific issues, with their specialized tools. The aim of the method proposed here is to provide a unified testing framework to enable the validation of cross-disciplinary requirements. Since we target a general-purpose solution, usable by all disciplines, the method is specified using an abstract modeling language, namely SysML.","PeriodicalId":179690,"journal":{"name":"Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134151493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Gábor Szárnyas, Z. Kővári, Ágnes Salánki, Dániel Varró
Custom generators of graph-based models are used in MDE for many purposes such as functional testing and performance benchmarking of modeling environments to ensure the correctness and scalability of tools. However, while existing generators may generate large models in increasing size, these models are claimed to be simple and synthetic, which hinders their credibility for industrial and research benchmarking purposes. But how to characterize a realistic model used in software and systems engineering? This question is investigated in the paper by collecting over 17 different widely used graph metrics taken from other disciplines (e.g. network theory) and evaluating them on 83 instance models originating from six modeling domains. Our preliminary results show that certain metrics are similar within a domain, but differ greatly between domains, which makes them suitable input for future instance model generators to derive more realistic models.
{"title":"Towards the characterization of realistic models: evaluation of multidisciplinary graph metrics","authors":"Gábor Szárnyas, Z. Kővári, Ágnes Salánki, Dániel Varró","doi":"10.1145/2976767.2976786","DOIUrl":"https://doi.org/10.1145/2976767.2976786","url":null,"abstract":"Custom generators of graph-based models are used in MDE for many purposes such as functional testing and performance benchmarking of modeling environments to ensure the correctness and scalability of tools. However, while existing generators may generate large models in increasing size, these models are claimed to be simple and synthetic, which hinders their credibility for industrial and research benchmarking purposes. But how to characterize a realistic model used in software and systems engineering? This question is investigated in the paper by collecting over 17 different widely used graph metrics taken from other disciplines (e.g. network theory) and evaluating them on 83 instance models originating from six modeling domains. Our preliminary results show that certain metrics are similar within a domain, but differ greatly between domains, which makes them suitable input for future instance model generators to derive more realistic models.","PeriodicalId":179690,"journal":{"name":"Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134447146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bader Alkhazi, Terry Ruas, M. Kessentini, M. Wimmer, W. Grosky
Model transformation programs evolve through a process of continuous change. However, this process may weaken the design of the transformation programs and make it unnecessarily complex, leading to increased fault-proneness. Refactoring improves the software design while preserving overall functionality and behavior. However, very few studies addressed the problem of refactoring model transformation programs. These existing studies provided an entirely manual or semi-automated refactoring support to transformation languages such as ATL. In this paper, we propose a fully-automated search-based approach to refactor model transformations based on a multi-objective algorithm that recommends the best refactoring sequence (e.g. extract rule, merge rules, etc.) optimizing a set of ATL-based quality metrics (e.g. number of rules, coupling, etc.). To validate our approach, we apply it to a comprehensive dataset of model transformations. The statistical analysis of our experiments over 30 runs shows that our automated approach recommended useful refactorings based on benchmark of ATL programs and compared to random search, mono-objective search formulation and a semi-automated refactoring approach not based heuristic search.
{"title":"Automated refactoring of ATL model transformations: a search-based approach","authors":"Bader Alkhazi, Terry Ruas, M. Kessentini, M. Wimmer, W. Grosky","doi":"10.1145/2976767.2976782","DOIUrl":"https://doi.org/10.1145/2976767.2976782","url":null,"abstract":"Model transformation programs evolve through a process of continuous change. However, this process may weaken the design of the transformation programs and make it unnecessarily complex, leading to increased fault-proneness. Refactoring improves the software design while preserving overall functionality and behavior. However, very few studies addressed the problem of refactoring model transformation programs. These existing studies provided an entirely manual or semi-automated refactoring support to transformation languages such as ATL. In this paper, we propose a fully-automated search-based approach to refactor model transformations based on a multi-objective algorithm that recommends the best refactoring sequence (e.g. extract rule, merge rules, etc.) optimizing a set of ATL-based quality metrics (e.g. number of rules, coupling, etc.). To validate our approach, we apply it to a comprehensive dataset of model transformations. The statistical analysis of our experiments over 30 runs shows that our automated approach recommended useful refactorings based on benchmark of ATL programs and compared to random search, mono-objective search formulation and a semi-automated refactoring approach not based heuristic search.","PeriodicalId":179690,"journal":{"name":"Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114394757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Model Finding is an established method to increase the confidence in the correctness of a UML/OCL model, e. g., by automatically determining valid system states or counterexamples. In the recent past, numerous approaches have been proposed for this purpose. In order to cope with the underlying complexity, approaches based on satisfiability solvers have been found promising. They require a translation of all OCL constraints of the model for a corresponding solver. In this paper, SMT-based model finding is investigated. It is shown that certain OCL operations are causing huge SMT formulations which harm the solving process. However, this is not necessary if a fixed structure of the model can be assumed. Motivated by this, a new concept called ground setting properties is introduced which allows for an efficient translation of OCL into SMT. This concept is illustrated by means of a running example and compared to existing solutions.
{"title":"Ground setting properties for an efficient translation of OCL in SMT-based model finding","authors":"Nils Przigoda, R. Wille, R. Drechsler","doi":"10.1145/2976767.2976780","DOIUrl":"https://doi.org/10.1145/2976767.2976780","url":null,"abstract":"Model Finding is an established method to increase the confidence in the correctness of a UML/OCL model, e. g., by automatically determining valid system states or counterexamples. In the recent past, numerous approaches have been proposed for this purpose. In order to cope with the underlying complexity, approaches based on satisfiability solvers have been found promising. They require a translation of all OCL constraints of the model for a corresponding solver. In this paper, SMT-based model finding is investigated. It is shown that certain OCL operations are causing huge SMT formulations which harm the solving process. However, this is not necessary if a fixed structure of the model can be assumed. Motivated by this, a new concept called ground setting properties is introduced which allows for an efficient translation of OCL into SMT. This concept is illustrated by means of a running example and compared to existing solutions.","PeriodicalId":179690,"journal":{"name":"Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122980259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose a generic framework for model-set selection for learning or testing Model-Driven Engineering tasks. We target specifically tasks that apply to or manipulate models, such as model definition, model well-formedness checking, and model transformation. In our framework, we view the model-set selection as a multi-objective optimization problem. The framework can be tailored to the learning or testing of a specific task by firstly expressing the coverage criterion, which will be encoded as a first optimization objective. The coverage is expressed by tagging the subset of the input metamodel that is relevant to the considered task. Then, one or more minimality criteria are selected as additional optimization objectives. We illustrate the use of our framework with the testing of metamodels. This case study shows that the multi-objective approach gives better results than random and mono-objective selections.
{"title":"A generic framework for model-set selection for the unification of testing and learning MDE tasks","authors":"Edouard R. Batot, H. Sahraoui","doi":"10.1145/2976767.2976785","DOIUrl":"https://doi.org/10.1145/2976767.2976785","url":null,"abstract":"We propose a generic framework for model-set selection for learning or testing Model-Driven Engineering tasks. We target specifically tasks that apply to or manipulate models, such as model definition, model well-formedness checking, and model transformation. In our framework, we view the model-set selection as a multi-objective optimization problem. The framework can be tailored to the learning or testing of a specific task by firstly expressing the coverage criterion, which will be encoded as a first optimization objective. The coverage is expressed by tagging the subset of the input metamodel that is relevant to the considered task. Then, one or more minimality criteria are selected as additional optimization objectives. We illustrate the use of our framework with the testing of metamodels. This case study shows that the multi-objective approach gives better results than random and mono-objective selections.","PeriodicalId":179690,"journal":{"name":"Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126659157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nicolas Harrand, Franck Fleurey, Brice Morin, Knut Eilif Husa
One of the selling points of Model-Driven Software Engineering (MDSE) is the increase in productivity offered by automatically generating code from models. However, the practical adoption of code generation remains relatively slow and limited to niche applications. Tooling issues are often pointed out but more fundamentally, experience shows that: (i) models and modeling languages used for other purposes are not necessarily well suited for code generation and (ii) code generators are often seen as black-boxes which are not easy to trust and produce sub-optimal code. This paper presents and discusses our experiences applying the ThingML approach to different domains. ThingML includes a modeling language and tool designed for supporting code generation and a highly customizable multi-platform code generation framework. The approach is implemented in an open-source tool providing a family of code generators targeting heterogeneous platforms. It has been evaluated through several case studies and is being used for in the development of a commercial ambient assisted living system.
{"title":"ThingML: a language and code generation framework for heterogeneous targets","authors":"Nicolas Harrand, Franck Fleurey, Brice Morin, Knut Eilif Husa","doi":"10.1145/2976767.2976812","DOIUrl":"https://doi.org/10.1145/2976767.2976812","url":null,"abstract":"One of the selling points of Model-Driven Software Engineering (MDSE) is the increase in productivity offered by automatically generating code from models. However, the practical adoption of code generation remains relatively slow and limited to niche applications. Tooling issues are often pointed out but more fundamentally, experience shows that: (i) models and modeling languages used for other purposes are not necessarily well suited for code generation and (ii) code generators are often seen as black-boxes which are not easy to trust and produce sub-optimal code. This paper presents and discusses our experiences applying the ThingML approach to different domains. ThingML includes a modeling language and tool designed for supporting code generation and a highly customizable multi-platform code generation framework. The approach is implemented in an open-source tool providing a family of code generators targeting heterogeneous platforms. It has been evaluated through several case studies and is being used for in the development of a commercial ambient assisted living system.","PeriodicalId":179690,"journal":{"name":"Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115243474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Utilizing models for software construction is a well-studied research topic. Recent research investigates the integration of models into running systems to provide additional information about the system configuration at runtime. While this additional information enables innovative self-adaptive mechanisms, it is still an open research question if the information provided by models can also improve the analysis capabilities of human users where manual intervention is inevitable for investigating runtime phenomena. This paper contributes to fill this gap by conducting a controlled experiment where the correctness and completion time of tasks regarding runtime information are assessed. A control and experiment group had to analyze the output of a software system, and the experiment group additionally received traceability links between models and associated runtime records. The results show that improvements of the analysis can especially be observed where model elements emphasize relationships between system parts that are hardly recognizable in the implementation code.
{"title":"Controlled experiment on the comprehension of runtime phenomena using models created at design time","authors":"Michael Szvetits, Uwe Zdun","doi":"10.1145/2976767.2976768","DOIUrl":"https://doi.org/10.1145/2976767.2976768","url":null,"abstract":"Utilizing models for software construction is a well-studied research topic. Recent research investigates the integration of models into running systems to provide additional information about the system configuration at runtime. While this additional information enables innovative self-adaptive mechanisms, it is still an open research question if the information provided by models can also improve the analysis capabilities of human users where manual intervention is inevitable for investigating runtime phenomena. This paper contributes to fill this gap by conducting a controlled experiment where the correctness and completion time of tasks regarding runtime information are assessed. A control and experiment group had to analyze the output of a software system, and the experiment group additionally received traceability links between models and associated runtime records. The results show that improvements of the analysis can especially be observed where model elements emphasize relationships between system parts that are hardly recognizable in the implementation code.","PeriodicalId":179690,"journal":{"name":"Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121699629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. García-Domínguez, Konstantinos Barmpis, D. Kolovos, M. A. D. Silva, Antonin Abhervé, A. Bagnato
Softeam has over 20 years of experience providing UML-based modelling solutions, such as its Modelio modelling tool, and its Constellation enterprise model management and collaboration environment. Due to the increasing number and size of the models used by Softeam's clients, Softeam joined the MONDO FP7 EU research project, which worked on solutions for these scalability challenges and produced the Hawk model indexer among other results. This paper presents the technical details and several case studies on the integration of Hawk into Softeam's toolset. The first case study measured the performance of Hawk's Modelio support using varying amounts of memory for the Neo4j backend. In another case study, Hawk was integrated into Constellation to provide scalable global querying of model repositories. Finally, the combination of Hawk and the Epsilon Generation Language was compared against Modelio for document generation: for the largest model, Hawk was two orders of magnitude faster.
{"title":"Integration of a graph-based model indexer in commercial modelling tools","authors":"A. García-Domínguez, Konstantinos Barmpis, D. Kolovos, M. A. D. Silva, Antonin Abhervé, A. Bagnato","doi":"10.1145/2976767.2976809","DOIUrl":"https://doi.org/10.1145/2976767.2976809","url":null,"abstract":"Softeam has over 20 years of experience providing UML-based modelling solutions, such as its Modelio modelling tool, and its Constellation enterprise model management and collaboration environment. Due to the increasing number and size of the models used by Softeam's clients, Softeam joined the MONDO FP7 EU research project, which worked on solutions for these scalability challenges and produced the Hawk model indexer among other results. This paper presents the technical details and several case studies on the integration of Hawk into Softeam's toolset. The first case study measured the performance of Hawk's Modelio support using varying amounts of memory for the Neo4j backend. In another case study, Hawk was integrated into Constellation to provide scalable global querying of model repositories. Finally, the combination of Hawk and the Epsilon Generation Language was compared against Modelio for document generation: for the largest model, Hawk was two orders of magnitude faster.","PeriodicalId":179690,"journal":{"name":"Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133706723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Prefetching and caching are well-known techniques integrated in database engines and file systems in order to speed-up data access. They have been studied for decades and have proven their efficiency to improve the performance of I/O intensive applications. Existing solutions do not fit well with scalable model persistence frameworks because the prefetcher operates at the data level, ignoring potential optimizations based on the information available at the metamodel level. Furthermore, prefetching components are common in relational databases but typically missing (or rather limited) in NoSQL databases, a common option for model storage nowadays. To overcome this situation we propose PrefetchML, a framework that executes prefetching and caching strategies over models. Our solution embeds a DSL to precisely configure the prefetching rules to follow. Our experiments show that PrefetchML provides a significant execution time speedup. Tool support is fully available online.
{"title":"PrefetchML: a framework for prefetching and caching models","authors":"Gwendal Daniel, G. Sunyé, Jordi Cabot","doi":"10.1145/2976767.2976775","DOIUrl":"https://doi.org/10.1145/2976767.2976775","url":null,"abstract":"Prefetching and caching are well-known techniques integrated in database engines and file systems in order to speed-up data access. They have been studied for decades and have proven their efficiency to improve the performance of I/O intensive applications. Existing solutions do not fit well with scalable model persistence frameworks because the prefetcher operates at the data level, ignoring potential optimizations based on the information available at the metamodel level. Furthermore, prefetching components are common in relational databases but typically missing (or rather limited) in NoSQL databases, a common option for model storage nowadays. To overcome this situation we propose PrefetchML, a framework that executes prefetching and caching strategies over models. Our solution embeds a DSL to precisely configure the prefetching rules to follow. Our experiments show that PrefetchML provides a significant execution time speedup. Tool support is fully available online.","PeriodicalId":179690,"journal":{"name":"Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134057779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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