Context-Oriented Behavioral Programming
Modern systems require programmers to develop code that dynamically adapts to different contexts, leading to the evolution of new context-oriented programming languages. These languages introduce new software-engineering challenges, such as: how to maintain the separation of concerns of the codebase...
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| Veröffentlicht in: | Information and software technology Jg. 133; S. 106504 |
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| Sprache: | Englisch |
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Elsevier B.V
01.05.2021
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| ISSN: | 0950-5849, 1873-6025 |
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| Abstract | Modern systems require programmers to develop code that dynamically adapts to different contexts, leading to the evolution of new context-oriented programming languages. These languages introduce new software-engineering challenges, such as: how to maintain the separation of concerns of the codebase? how to model the changing behaviors? how to verify the system behavior? and more.
This paper introduces Context-Oriented Behavioral Programming (COBP) — a novel paradigm for developing context-aware systems, centered on natural and incremental specification of context-dependent behaviors. As the name suggests, we combine behavioral-programming (BP) — a scenario-based modeling paradigm — with context idioms that explicitly specify when scenarios are relevant and what information they need. The core idea is to connect the behavioral model with a data model that represents the context, allowing an intuitive connection between the models via update and select queries. Combining behavioral-programming with context-oriented programming brings the best of the two worlds, solving issues that arise when using each of the approaches in separation.
We begin with providing abstract semantics for COBP and two implementations for the semantics, laying the foundations for applying reasoning algorithms to context-aware behavioral programs. Next, we exemplify the semantics with formal specifications of systems, including a variant of Conway’s Game of Life. Then, we provide two case studies of real-life context-aware systems (one in robotics and another in IoT) that were developed using this tool. Throughout the examples and case studies, we provide design patterns and a methodology for coping with the above challenges.
The case studies show that the proposed approach is applicable for developing real-life systems, and presents measurable advantages over the alternatives — behavioral programming alone and context-oriented programming alone.
We present a paradigm allowing programmers and system engineers to capture complex context-dependent requirements and align their code with such requirements.
•We extend behavioral programming with idioms for specifying context, which:•Cater for natural and incremental specification of context-dependent requirements.•Connect behavioral and object models into a unified context-based modeling approach.•Allow for direct debugging, execution, and verification of contextual requirements.•We provide theory, methodologies, and tools and study various use-cases. |
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| AbstractList | Modern systems require programmers to develop code that dynamically adapts to different contexts, leading to the evolution of new context-oriented programming languages. These languages introduce new software-engineering challenges, such as: how to maintain the separation of concerns of the codebase? how to model the changing behaviors? how to verify the system behavior? and more.
This paper introduces Context-Oriented Behavioral Programming (COBP) — a novel paradigm for developing context-aware systems, centered on natural and incremental specification of context-dependent behaviors. As the name suggests, we combine behavioral-programming (BP) — a scenario-based modeling paradigm — with context idioms that explicitly specify when scenarios are relevant and what information they need. The core idea is to connect the behavioral model with a data model that represents the context, allowing an intuitive connection between the models via update and select queries. Combining behavioral-programming with context-oriented programming brings the best of the two worlds, solving issues that arise when using each of the approaches in separation.
We begin with providing abstract semantics for COBP and two implementations for the semantics, laying the foundations for applying reasoning algorithms to context-aware behavioral programs. Next, we exemplify the semantics with formal specifications of systems, including a variant of Conway’s Game of Life. Then, we provide two case studies of real-life context-aware systems (one in robotics and another in IoT) that were developed using this tool. Throughout the examples and case studies, we provide design patterns and a methodology for coping with the above challenges.
The case studies show that the proposed approach is applicable for developing real-life systems, and presents measurable advantages over the alternatives — behavioral programming alone and context-oriented programming alone.
We present a paradigm allowing programmers and system engineers to capture complex context-dependent requirements and align their code with such requirements.
•We extend behavioral programming with idioms for specifying context, which:•Cater for natural and incremental specification of context-dependent requirements.•Connect behavioral and object models into a unified context-based modeling approach.•Allow for direct debugging, execution, and verification of contextual requirements.•We provide theory, methodologies, and tools and study various use-cases. |
| ArticleNumber | 106504 |
| Author | Elyasaf, Achiya |
| Author_xml | – sequence: 1 givenname: Achiya surname: Elyasaf fullname: Elyasaf, Achiya email: achiya@bgu.ac.il organization: Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Israel |
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| Keywords | Scenario-based programming Context-oriented programming Behavioral programming Programming paradigm Context-Oriented Behavioral Programming Context awareness |
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