Context-aware pervasive computing has attracted a significant research interest from both academy and industry worldwide. It covers a broad range of applications that support many manufacturing and daily life activities. For instance, industrial robots detect the changes of the working environment in the factory to adapt their operations to the requirements. Automotive control systems may observe other vehicles, detect obstacles, and monitor the essence level or the air quality in order to warn the drivers in case of emergency. Another example is power-aware embedded systems that need to work based on current power/energy availability since power consumption is an important issue. Those kinds of systems can also be considered as smart applications. In practice, successful implementation and deployment of context-aware systems depend on the mechanism to recognize and react to variabilities happening in the environment. In other words, we need a well-defined and efficient adaptation approach so that the systems' behavior can be dynamically customized at runtime. Moreover, concurrency should be exploited to improve the performance and responsiveness of the systems. All those requirements, along with the need for safety, dependability, and reliability pose a big challenge for developers.In this thesis, we propose a novel programming language called INI, which supports both event-based and rule-based programming paradigms and is suitable for building concurrent and context-aware reactive applications. In our language, both events and rules can be defined explicitly, in a stand-alone way or in combination. Events in INI run in parallel (synchronously or asynchronously) in order to handle multiple tasks concurrently and may trigger the actions defined in rules. Besides, events can interact with the execution environment to adjust their behavior if necessary and respond to unpredictable changes. We apply INI in both academic and industrial case studies, namely an object tracking program running on the humanoid robot Nao and a M2M gateway. This demonstrates the soundness of our approach as well as INI's capabilities for constructing context-aware systems. Additionally, since context-aware programs are wide applicable and more complex than regular ones, this poses a higher demand for quality assurance with those kinds of applications. Therefore, we formalize several aspects of INI, including its type system and operational semantics. Furthermore, we develop a tool called INICheck, which can convert a significant subset of INI to Promela, the input modeling language of the model checker SPIN. Hence, SPIN can be applied to verify properties or constraints that need to be satisfied by INI programs. Our tool allows the programmers to have insurance on their code and its behavior.