Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems最新文献_第4页

A model-based approach for multi-device user interactions 多设备用户交互的基于模型的方法

Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems Pub Date : 2016-10-02 DOI: 10.1145/2976767.2976776

C. Prehofer, A. Wagner, Yucheng Jin

引用次数: 6

Incremental backward change propagation of view models by logic solvers* 逻辑解算器对视图模型的增量向后更改传播*

Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems Pub Date : 2016-10-02 DOI: 10.1145/2976767.2976788

Oszkár Semeráth, Csaba Debreceni, Á. Horváth, Dániel Varró

引用次数: 13

Feature location in models through a genetic algorithm driven by information retrieval techniques 通过信息检索技术驱动的遗传算法对模型进行特征定位

Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems Pub Date : 2016-10-02 DOI: 10.1145/2976767.2976789

Jaime Font, Lorena Arcega, Øystein Haugen, Carlos Cetina

引用次数: 29

A generic transformation algorithm to simplify the development of mapping models 一种简化映射模型开发的通用转换算法

Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems Pub Date : 2016-10-02 DOI: 10.1145/2976767.2976777

M. Freund, A. Braune

引用次数: 9

A model management approach for assurance case reuse due to system evolution 由于系统演进，用于保证用例重用的模型管理方法

Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems Pub Date : 2016-10-02 DOI: 10.1145/2976767.2976792

Sahar Kokaly, Rick Salay, Valentin Cassano, T. Maibaum, M. Chechik

引用次数: 29

Towards mutation analysis for use cases 对用例进行突变分析

Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems Pub Date : 2016-10-02 DOI: 10.1145/2976767.2976784

Huihui Zhang, T. Yue, Shaukat Ali, Chao Liu

{"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}

引用次数: 8

Incremental diagram layout for automated model migration 用于自动模型迁移的增量图布局

Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems Pub Date : 2016-10-02 DOI: 10.1145/2976767.2976805

Ulf Rüegg, R. Lakkundi, Ashwin Prasad, Anand Kodaganur, C. Schulze, R. V. Hanxleden

引用次数: 5

Query-based access control for secure collaborative modeling using bidirectional transformations* 使用双向转换的安全协作建模的基于查询的访问控制*

Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems Pub Date : 2016-10-02 DOI: 10.1145/2976767.2976793

Gábor Bergmann, Csaba Debreceni, I. Ráth, Dániel Varró

引用次数: 25

Extracting domain models from natural-language requirements: approach and industrial evaluation 从自然语言需求中提取领域模型:方法和工业评估

Proceedings of the ACM/IEEE 19th International Conference on Model Driven Engineering Languages and Systems Pub Date : 2016-10-02 DOI: 10.1145/2976767.2976769

Chetan Arora, M. Sabetzadeh, L. Briand, Frank Zimmer

{"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}

引用次数: 89