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Fundamentals of OOP and data structures in Java
Abstract
FASE (pronounced like "phase"), the Forum for Advancing Software
engineering Education, was started in 1991 by members of the
software engineering education community in order to have a
electronic forum for the dissemination and discussion of events
related ...
... In this subsection, 20 Java programs are selected from Wiener and Pinson's book Fundamentals of OOP and Data Structures in Java [10]. Each program is analyzed in terms of the physical size (with the unit known as lines of code or LOC) and cognitive functional size (with the unit of cognitive weight or CWU) as shown in Table 2 and illustrated in Fig. 3. unit of cognitive weight or CWU) as shown in Table 2 and illustrated in Fig. 3. ...
One of the central problems in software engineering is the inherent complexity. Since software is the result of human creative activity, cognitive informatics plays an important role in understanding its fundamental characteristics. This paper models one of the fundamental characteristics of software, complexity, by examining the cognitive weights of basic software control structures. Based on this approach a new concept of cognitive functional size of software is developed. Comparative case studies of the cognitive complexity and physical size of 20 programs are reported. The cognitive functional size provides a foundation for cross-platform analysis of complexity, size, and comprehension effort in the design, implementation, and maintenance phases of software engineering.
The creation of large-scale simulation models is a difficult and time-consuming task. Yet simulation is one of the techniques most frequently used by practitioners in Operations Research and Industrial Engineering, as it is less limited by modeling assumptions than many analytical methods. The effective generation of simulation models is an important challenge. Due to the rapid increase in computing power, it is possible to simulate significantly larger systems than in the past. However, the verification and validation of these large-scale simulations is typically a very challenging task. This thesis introduces a simulation framework that can generate a large variety of manufacturing simulation models. These models have to be described with a simulation data specification. This specification is then used to generate a simulation model which is described as a Petri net. This approach reduces the effort of model verification. The proposed Petri net data structure has extensions for time and token priorities. Since it builds on existing theory for classical Petri nets, it is possible to make certain assertions about the behavior of the generated simulation model. The elements of the proposed framework and the simulation execution mechanism are described in detail. Measures of complexity for simulation models that are built with the framework are also developed. The applicability of the framework to real-world systems is demonstrated by means of a semiconductor manufacturing system simulation model. Ph.D. Committee Chair: Alexopoulos, Christos; Committee Co-Chair: McGinnis, Leon; Committee Member: Egerstedt, Magnus; Committee Member: Fujimoto, Richard; Committee Member: Goldsman, David
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