This paper presents an approach for modeling multi-device user interactions, based on task models. We use Concur-TaskTrees (CTTs) as a domain-specific language, which we extend here by a labeling mechanism to model multi-device interactive applications. While CTTs are used to specify temporal and causal relations between tasks, we add operators to specify the device mapping in a flexible and expressive way. The main novelty is the introduction of the two new operators, Any and All, to specify if a task should be executed on any or on all of a set of devices. We show that this is applicable in scenarios of connected, smart devices where a task can be executed on a multitude of devices. We present formal semantics for our extension of CTTs as well as a tool chain based on the Qt toolkit for generating code for distributed UIs. This includes a mapping from high-level tasks to concrete UI controls and a distributed execution model based on state machines. The new concepts are validated in several case studies.
{"title":"A model-based approach for multi-device user interactions","authors":"C. Prehofer, A. Wagner, Yucheng Jin","doi":"10.1145/2976767.2976776","DOIUrl":"https://doi.org/10.1145/2976767.2976776","url":null,"abstract":"This paper presents an approach for modeling multi-device user interactions, based on task models. We use Concur-TaskTrees (CTTs) as a domain-specific language, which we extend here by a labeling mechanism to model multi-device interactive applications. While CTTs are used to specify temporal and causal relations between tasks, we add operators to specify the device mapping in a flexible and expressive way. The main novelty is the introduction of the two new operators, Any and All, to specify if a task should be executed on any or on all of a set of devices. We show that this is applicable in scenarios of connected, smart devices where a task can be executed on a multitude of devices. We present formal semantics for our extension of CTTs as well as a tool chain based on the Qt toolkit for generating code for distributed UIs. This includes a mapping from high-level tasks to concrete UI controls and a distributed execution model based on state machines. The new concepts are validated in several case studies.","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":"125201048","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}
View models are key concepts of domain-specific modeling to provide task-specific focus (e.g., power or communication architecture of a system) to the designers by highlighting only the relevant aspects of the system. View models can be specified by unidirectional forward transformations (frequently captured by graph queries), and automatically maintained upon changes of the underlying source model using incremental transformation techniques. However, tracing back complex changes from one or more abstract view to the underlying source model is a challenging task, which, in general, requires the simultaneous analysis of transformation specifications and well-formedness constraints to create valid changes in the source model. In this paper we introduce a novel delta-based backward transformation technique using SAT solvers to synthetize valid and consistent change candidates in the source model, where only forward transformation rules are specified for the view models.
{"title":"Incremental backward change propagation of view models by logic solvers*","authors":"Oszkár Semeráth, Csaba Debreceni, Á. Horváth, Dániel Varró","doi":"10.1145/2976767.2976788","DOIUrl":"https://doi.org/10.1145/2976767.2976788","url":null,"abstract":"View models are key concepts of domain-specific modeling to provide task-specific focus (e.g., power or communication architecture of a system) to the designers by highlighting only the relevant aspects of the system. View models can be specified by unidirectional forward transformations (frequently captured by graph queries), and automatically maintained upon changes of the underlying source model using incremental transformation techniques. However, tracing back complex changes from one or more abstract view to the underlying source model is a challenging task, which, in general, requires the simultaneous analysis of transformation specifications and well-formedness constraints to create valid changes in the source model. In this paper we introduce a novel delta-based backward transformation technique using SAT solvers to synthetize valid and consistent change candidates in the source model, where only forward transformation rules are specified for the view 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":"121296791","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}
Jaime Font, Lorena Arcega, Øystein Haugen, Carlos Cetina
In this work we propose a feature location approach that targets models as the feature realization artifacts. The approach combines Genetic Algorithms and Information Retrieval techniques. Given a model and a feature description, model fragments extracted from the model are evolved using genetic operations. Then, Formal Concept Analysis is used to cluster the model fragments based on their common attributes into feature realization candidates. Finally, Latent Semantic Analysis is used to rank the candidates based on the similarity with the feature description. As a result, the genetic algorithm evolves the population of model fragments to find the set of most suitable feature realizations. We have evaluated the approach with an industrial case study, locating features with precision and recall values around 90% (baseline obtains less than 40%). Finally, we provide recommendations on how to provide the input to the approach to improve the location of features over the models.
{"title":"Feature location in models through a genetic algorithm driven by information retrieval techniques","authors":"Jaime Font, Lorena Arcega, Øystein Haugen, Carlos Cetina","doi":"10.1145/2976767.2976789","DOIUrl":"https://doi.org/10.1145/2976767.2976789","url":null,"abstract":"In this work we propose a feature location approach that targets models as the feature realization artifacts. The approach combines Genetic Algorithms and Information Retrieval techniques. Given a model and a feature description, model fragments extracted from the model are evolved using genetic operations. Then, Formal Concept Analysis is used to cluster the model fragments based on their common attributes into feature realization candidates. Finally, Latent Semantic Analysis is used to rank the candidates based on the similarity with the feature description. As a result, the genetic algorithm evolves the population of model fragments to find the set of most suitable feature realizations. We have evaluated the approach with an industrial case study, locating features with precision and recall values around 90% (baseline obtains less than 40%). Finally, we provide recommendations on how to provide the input to the approach to improve the location of features over the 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":"127772460","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}
Declarative mapping models aim at simplifying the development of model transformations by separating (1) the configuration of mappings between elements of the source and target meta-model and (2) the execution of these mappings. Existing solutions however require an extended definition of the mappings that, e.g., also describes how generated elements need to be connected. In this paper, we propose a generic transformation algorithm that is able to execute mappings that do not specify such extended information by analyzing the structure of the target meta-model. This limits the effort necessary for the definition of mappings and ensures a valid target model already at early stages of development. After analyzing the tasks that model transformations needs to perform, we present our approach towards generic transformation rules for models that are based on the Eclipse Modeling Framework and illustrate a concrete implementation by means of an integration into our own model transformation framework.
{"title":"A generic transformation algorithm to simplify the development of mapping models","authors":"M. Freund, A. Braune","doi":"10.1145/2976767.2976777","DOIUrl":"https://doi.org/10.1145/2976767.2976777","url":null,"abstract":"Declarative mapping models aim at simplifying the development of model transformations by separating (1) the configuration of mappings between elements of the source and target meta-model and (2) the execution of these mappings. Existing solutions however require an extended definition of the mappings that, e.g., also describes how generated elements need to be connected. In this paper, we propose a generic transformation algorithm that is able to execute mappings that do not specify such extended information by analyzing the structure of the target meta-model. This limits the effort necessary for the definition of mappings and ensures a valid target model already at early stages of development. After analyzing the tasks that model transformations needs to perform, we present our approach towards generic transformation rules for models that are based on the Eclipse Modeling Framework and illustrate a concrete implementation by means of an integration into our own model transformation framework.","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":"130314262","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}
Sahar Kokaly, Rick Salay, Valentin Cassano, T. Maibaum, M. Chechik
Evolution in software systems is a necessary activity that occurs due to fixing bugs, adding functionality or improving system quality. Systems often need to be shown to comply with regulatory standards. Along with demonstrating compliance, an artifact, called an assurance case, is often produced to show that the system indeed satisfies the property imposed by the standard (e.g., safety, privacy, security, etc.). Since each of the system, the standard, and the assurance case can be presented as a model, we propose the extension and use of traditional model management operators to aid in the reuse of parts of the assurance case when the system undergoes an evolution. Specifically, we present a model management approach that eventually produces a partial evolved assurance case and guidelines to help the assurance engineer in completing it. We demonstrate how our approach works on an automotive subsystem regulated by the ISO 26262 standard.
{"title":"A model management approach for assurance case reuse due to system evolution","authors":"Sahar Kokaly, Rick Salay, Valentin Cassano, T. Maibaum, M. Chechik","doi":"10.1145/2976767.2976792","DOIUrl":"https://doi.org/10.1145/2976767.2976792","url":null,"abstract":"Evolution in software systems is a necessary activity that occurs due to fixing bugs, adding functionality or improving system quality. Systems often need to be shown to comply with regulatory standards. Along with demonstrating compliance, an artifact, called an assurance case, is often produced to show that the system indeed satisfies the property imposed by the standard (e.g., safety, privacy, security, etc.). Since each of the system, the standard, and the assurance case can be presented as a model, we propose the extension and use of traditional model management operators to aid in the reuse of parts of the assurance case when the system undergoes an evolution. Specifically, we present a model management approach that eventually produces a partial evolved assurance case and guidelines to help the assurance engineer in completing it. We demonstrate how our approach works on an automotive subsystem regulated by the ISO 26262 standard.","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":"130715639","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}
Requirements inspection is a well-known method for detecting defects. Various defect detection techniques for requirements inspection have been widely applied in practice such as checklist and defect-based techniques. Use case modelling is a widely accepted requirements specification method in practice; therefore, inspecting defects in use case models in a cost-effective manner is an important challenge. However, it does not exist a systematic mutation analysis approach for evaluating inspection techniques for use case models. In this paper we present the methodology we followed to systematically derive mutation operators for use case models. More specifically, we first proposed a defect taxonomy defining 94 defect types, based on the IEEE Std. 830-1998 standard. Second, we systematically applied the basic guide words of the standardized Hazard and Operability Study (HAZOP) methodology to define 191 mutation operators. Last, we defined a set of guidelines for devising defect seeding strategies. The proposed methodology was evaluated by a real world case study and six case studies from the literature. Results show that all the derived mutation operators for Restricted Use Case Modelling (RUCM) models are feasible to apply and the defect taxonomy is the most comprehensive one to compare with the literature.
{"title":"Towards mutation analysis for use cases","authors":"Huihui Zhang, T. Yue, Shaukat Ali, Chao Liu","doi":"10.1145/2976767.2976784","DOIUrl":"https://doi.org/10.1145/2976767.2976784","url":null,"abstract":"Requirements inspection is a well-known method for detecting defects. Various defect detection techniques for requirements inspection have been widely applied in practice such as checklist and defect-based techniques. Use case modelling is a widely accepted requirements specification method in practice; therefore, inspecting defects in use case models in a cost-effective manner is an important challenge. However, it does not exist a systematic mutation analysis approach for evaluating inspection techniques for use case models. In this paper we present the methodology we followed to systematically derive mutation operators for use case models. More specifically, we first proposed a defect taxonomy defining 94 defect types, based on the IEEE Std. 830-1998 standard. Second, we systematically applied the basic guide words of the standardized Hazard and Operability Study (HAZOP) methodology to define 191 mutation operators. Last, we defined a set of guidelines for devising defect seeding strategies. The proposed methodology was evaluated by a real world case study and six case studies from the literature. Results show that all the derived mutation operators for Restricted Use Case Modelling (RUCM) models are feasible to apply and the defect taxonomy is the most comprehensive one to compare with the literature.","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":"115474168","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}
Ulf Rüegg, R. Lakkundi, Ashwin Prasad, Anand Kodaganur, C. Schulze, R. V. Hanxleden
A range of successful modeling tools to develop complex systems use node-link-style diagrams as their underlying language. Over the years such languages can change, for instance as part of a tool update. When migrating existing models, changes in syntax directly affect the placement of elements in their diagrams. Increasing the size of certain nodes may for example result in node overlaps. In this paper we propose two methods based on graph drawing techniques to adjust the layout of existing diagrams after migration. Although we designed these techniques for diagram migration, they are applicable to other scenarios as well, such as users interactively adding or resizing nodes. We evaluate the techniques based on real world diagrams from the LabVIEW suite and discuss the scenarios each technique seems best suited for.
{"title":"Incremental diagram layout for automated model migration","authors":"Ulf Rüegg, R. Lakkundi, Ashwin Prasad, Anand Kodaganur, C. Schulze, R. V. Hanxleden","doi":"10.1145/2976767.2976805","DOIUrl":"https://doi.org/10.1145/2976767.2976805","url":null,"abstract":"A range of successful modeling tools to develop complex systems use node-link-style diagrams as their underlying language. Over the years such languages can change, for instance as part of a tool update. When migrating existing models, changes in syntax directly affect the placement of elements in their diagrams. Increasing the size of certain nodes may for example result in node overlaps. In this paper we propose two methods based on graph drawing techniques to adjust the layout of existing diagrams after migration. Although we designed these techniques for diagram migration, they are applicable to other scenarios as well, such as users interactively adding or resizing nodes. We evaluate the techniques based on real world diagrams from the LabVIEW suite and discuss the scenarios each technique seems best suited for.","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":"129932329","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 Bergmann, Csaba Debreceni, I. Ráth, Dániel Varró
Large-scale model-driven system engineering projects are carried out collaboratively. Engineering artifacts stored in model repositories are developed in either offline (checkout-modify-commit) or online (GoogleDoc-style) scenarios. Complex systems frequently integrate models and components developed by different teams, vendors and suppliers. Thus confidentiality and integrity of design artifacts need to be protected by access control policies. We propose a technique for secure collaborative modeling where (1) fine-grained access control for models can be defined by model queries, and (2) such access control policies are strictly enforced by bidirectional model transformations. Each collaborator obtains a filtered local copy of the model containing only those model elements which they are allowed to read; write access control policies are checked on the server upon submitting model changes. We illustrate the approach and carry out an initial scalability assessment using a case study of the MONDO EU project.
{"title":"Query-based access control for secure collaborative modeling using bidirectional transformations*","authors":"Gábor Bergmann, Csaba Debreceni, I. Ráth, Dániel Varró","doi":"10.1145/2976767.2976793","DOIUrl":"https://doi.org/10.1145/2976767.2976793","url":null,"abstract":"Large-scale model-driven system engineering projects are carried out collaboratively. Engineering artifacts stored in model repositories are developed in either offline (checkout-modify-commit) or online (GoogleDoc-style) scenarios. Complex systems frequently integrate models and components developed by different teams, vendors and suppliers. Thus confidentiality and integrity of design artifacts need to be protected by access control policies. We propose a technique for secure collaborative modeling where (1) fine-grained access control for models can be defined by model queries, and (2) such access control policies are strictly enforced by bidirectional model transformations. Each collaborator obtains a filtered local copy of the model containing only those model elements which they are allowed to read; write access control policies are checked on the server upon submitting model changes. We illustrate the approach and carry out an initial scalability assessment using a case study of the MONDO EU project.","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":"130234613","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}
Chetan Arora, M. Sabetzadeh, L. Briand, Frank Zimmer
Domain modeling is an important step in the transition from natural-language requirements to precise specifications. For large systems, building a domain model manually is a laborious task. Several approaches exist to assist engineers with this task, whereby candidate domain model elements are automatically extracted using Natural Language Processing (NLP). Despite the existing work on domain model extraction, important facets remain under-explored: (1) there is limited empirical evidence about the usefulness of existing extraction rules (heuristics) when applied in industrial settings; (2) existing extraction rules do not adequately exploit the natural-language dependencies detected by modern NLP technologies; and (3) an important class of rules developed by the information retrieval community for information extraction remains unutilized for building domain models. Motivated by addressing the above limitations, we develop a domain model extractor by bringing together existing extraction rules in the software engineering literature, extending these rules with complementary rules from the information retrieval literature, and proposing new rules to better exploit results obtained from modern NLP dependency parsers. We apply our model extractor to four industrial requirements documents, reporting on the frequency of different extraction rules being applied. We conduct an expert study over one of these documents, investigating the accuracy and overall effectiveness of our domain model extractor.
{"title":"Extracting domain models from natural-language requirements: approach and industrial evaluation","authors":"Chetan Arora, M. Sabetzadeh, L. Briand, Frank Zimmer","doi":"10.1145/2976767.2976769","DOIUrl":"https://doi.org/10.1145/2976767.2976769","url":null,"abstract":"Domain modeling is an important step in the transition from natural-language requirements to precise specifications. For large systems, building a domain model manually is a laborious task. Several approaches exist to assist engineers with this task, whereby candidate domain model elements are automatically extracted using Natural Language Processing (NLP). Despite the existing work on domain model extraction, important facets remain under-explored: (1) there is limited empirical evidence about the usefulness of existing extraction rules (heuristics) when applied in industrial settings; (2) existing extraction rules do not adequately exploit the natural-language dependencies detected by modern NLP technologies; and (3) an important class of rules developed by the information retrieval community for information extraction remains unutilized for building domain models. Motivated by addressing the above limitations, we develop a domain model extractor by bringing together existing extraction rules in the software engineering literature, extending these rules with complementary rules from the information retrieval literature, and proposing new rules to better exploit results obtained from modern NLP dependency parsers. We apply our model extractor to four industrial requirements documents, reporting on the frequency of different extraction rules being applied. We conduct an expert study over one of these documents, investigating the accuracy and overall effectiveness of our domain model extractor.","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":"134628403","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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