This paper presents a survey describing recent developments in the area of mathematical programming techniques for various types of sensor network applications. We discuss mathematical programming formulations associated with these applications, as well as methods for solving the corresponding problems. We also address some of the challenges arising in this area, including both conceptual and computational aspects
During the past six years, the authors have experimented with various modeling and quality control techniques while teaching software engineering to university students. The first group of experiments compared UML to natural languages (e.g. English); the second group modeled the entire software development process as a sequence of translations from more abstract languages to more formal languages (e.g. from English to UML, from UML to C++, etc.). In these experiments the authors and their students discovered new approaches to increasing productivity of software developers. On this basis, the authors have developed the framework that extends traditional development processes. The framework is built upon two simple, yet powerful principles: Reverse Semantic Traceability (RST) and Speechless Modeling.The authors have over two years of experience of using RST in computing curricula, and also have over six years of experience of applying Speechless Modeling in teaching computer science and software engineering. Both approaches resulted in improving the quality of education and generated positive feedback from students. Some students started to practice the authors' framework in their professional careers. In this paper, the authors present their experience of integrating RST and Speechless Modeling into university computer science/software engineering curricula.
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