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ȯɽÂêÌÜ¡§ÏÀʸ¾Ò²ð ¡ÉDesign
Pattern Density Defined¡É ȯɽ³µÍס§In this paper, there newly defined the metric ¡ÇDesign Pattern Density¡Ç and it would
measure how much of an object-oriented design can be understood and represented
as instances of design patterns. Expert developers have long believed that a
high design pattern density implies a high maturity of the design under
inspection. This paper presents a quantifiable and observable definition of
this metric. The metric is illustrated and qualitatively validated using 4
real-world case studies. It
presents also several hypotheses of the metric¡Çs meaning and their
implications, including the one about design maturity. The paper proposes that
the design pattern density of a maturing framework has a fixed point and it
shows that if software design patterns make learning frameworks easier, a
framework¡Çs design pattern density is a measure of how much easier it will
become. | ||
Marcos Daniel Villagra | ¥³¥ó¥Ô¥å¡¼¥Æ¥£¥ó¥°¡¦¥¢¡¼¥¥Æ¥¯¥Á¥ã | ÃæÅç ¹¯É§ |
ȯɽÂêÌÜ¡§Quantum Walks: Introductory Overview and Ongoing Research
ȯɽ³µÍס§The design of quantum algorithms is nowadays one of the major problems in the quantum computing community. An emergent alternative for the design of algorithms is quantum walks. A quantum walk is the quantum counter-part of classical random walks. Results in this field showed that quantum walks can outperform its classical counterpart by exploiting quantum effects such as interference and superposition, giving an exponential speedup for certain types of graphs, and polynomial speedup for some practical applications. In this research, a study on quantum walks on the line is presented. The walk is defined using a coin operator with phase parameters. These parameters are in charge of tuning the standard deviation of the walk, this way the walk can be adapted according to the structure of the search space. Closed-form formulas for the state of the quantum walk are deducted using Fourier analysis and the steepest descent method for asymptotic approximation. | ||