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Many metrics have been proposed to measure the complexity or cohesion of object-oriented software. However, the complexity or cohesion of a piece of software is more difficult to capture than these metrics imply. In fact, studies have shown that existing metrics consistently fail to capture complexity or cohesion well. This study explores the reasons behind these results: cohesion is difficult to capture from syntactic elements of code, complexity is too multi-faceted to be captured by one metric and the qualities of complexity and cohesion are not independent. These factors have resulted in metrics that are purported to measure complexity or cohesion but are inadequate or misclassified. This study shows that there is overlap between some of the complexity and cohesion metrics and points to a more basic relationship between complexity and cohesion: that a lack of cohesion may be associated with high complexity

Assessing progress and stability in rapid, highly iterative and agile object-oriented software development processes is difficult because program evolution appears somewhat disorderly. With agile software development methods, the expected time to reach software stability is obscured by the dynamic nature of the agile process itself. The System Design Instability (SDI) metric was developed to help analyze objectoriented software evolution under these conditions. In this paper we examine a new version of SDI, called SDI e , based on the maximum entropy in a system. We believe our new measure is easier to calculate than the original version of SDI since it is based on data that are more commonly available than those used by SDI; also, SDI e gives a more accurate indication of software stability and maturity since it suffers less from data spikes. To validate the new metric, we use maintenance data from a commercial software project, developed using an agile process; these are the same data that were collected and analyzed in the original SDI study. In addition, we apply the refined SDI metric to the evolution of a well-established, open-source, iterativelydeveloped software product. The results of our case study indicate our new SDI e metric is a viable measure of system design stability.

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The use of GPS for personal location using wireless devices requires satellite signal measurements both outdoors and indoors. In the outdoor environment propagation paths may range from line-of-sight to shaded or blocked. The indoor environment may range from single-floor wooden constructions to high-rise buildings and underground facilities. In this paper, a high-sensitivity receiver which operates in unaided stand-alone mode is tested under a range of shaded and blocked signal environments, ranging from residential outdoor areas to urban canyons and residential houses. The measurement analysis is performed in both the observation and position domains. The results show that the receiver tested is able to yield measurements with C/N 0 degradations in excess of 20 dB-Hz, as compared to line-of-sight measurements. Position results are a function of the geometry of the remaining satellites, which in turn is a function of the environment.