Scandinavian Thins on Top of Cake: New and Improved Algorithms for Stacking and Packing

We show how to compute the smallest rectangle that can enclose any polygon, from a given set of polygons, in nearly linear time; we also present a PTAS for the problem, as well as a linear-time algorithm for the case when the polygons are rectangles themselves. We prove that finding a smallest convex polygon that encloses any of the given polygons is NP-hard, and give a PTAS for minimizing the perimeter of the convex enclosure. We also give efficient algorithms to find the smallest rectangle simultaneously enclosing a given pair of convex polygons.     

A probabilistic alternative to regression suites

Automated regression suites are essential in developing large applications, while maintaining reasonable quality and timetables. The main argument against the automation of regression suites, in addition to the cost of creation and maintenance, is the observation that if you run the same test many times, it becomes increasingly less likely to find bugs. To alleviate such problems, a new regression suite practice, using random test generators to create regression suites on-the-fly, is becoming more common. In this practice, instead of maintaining tests, we generate test suites on-the-fly by choosing several specifications and generating a number of tests from each specification.     

The Topology of Transportation Networks: A Comparison Between Different Economies

This paper presents an analysis of the topology of transportation networks within different systems of cities. Urban entities and their components are complex systems by their nature; there is no central force that affects their spatial structure. Thus, we study transportation networks within different countries as complex networks. Based on the above, we consider cities as nodes, while direct air and railways routes represent the links. We present characteristics of these networks including their degree and clustering coefficient. Transportation networks can be used as an indicator of economic activity between cities. Cities with strong economic relationship are characterized by high volume of connectivity. Our findings suggest that the topology of the analyzed transportation networks can be used to classify the countries they belong to based on their economic development.

Automatic boosting of cross-product coverage using Bayesian networks

Closing the feedback loop from coverage data to the stimuli generator is one of the main challenges in the verification process. Typically, verification engineers with deep domain knowledge manually prepare a set of stimuli generation directives for that purpose. Bayesian networks based CDG (coverage directed generation) systems have been successfully used to assist the process by automatically closing this feedback loop. However, constructing these CDG systems requires manual effort and a certain amount of domain knowledge from a machine learning specialist. We propose a new method that boosts coverage in the early stages of the verification process with minimal effort, namely a fully automatic construction of a CDG system that requires no domain knowledge. Experimental results on a real-life cross-product coverage model demonstrate the efficiency of the proposed method.     

Efficient Regular Data Structures and Algorithms for Dilation, Location, and Proximity Problems

In this paper we investigate data structures obtained by a recursive partitioning of the multi- dimensional input domain into regions of equal size. One of the best known examples of such a structure is the quadtree . It is used here as a basis for more complex data structures. We also provide multidimensional versions of the stratified tree by van Emde Boas [vEB]. We show that under the assumption that the input points have limited precision (i.e., are drawn from the integer grid of size u ) these data structures yield efficient solutions to many important problems. In particular, they allow us to achieve O(log log u) time per operation for dynamic approximate nearest neighbor (under insertions and deletions) and exact on-line closest pair (under insertions only) in any constant number of dimensions. They allow O(log log u) point location in a given planar shape or in its expansion (dilation by a ball of a given radius). Finally, we provide a linear time (optimal) algorithm for computing the expansion of a shape represented by a region quadtree. This result shows that the spatial order imposed by this regular data structure is sufficient to optimize the operation of dilation by a ball. Received January 19, 1999; revised November 4, 1999.     

On the Wyner-Ziv problem for individual sequences

We consider a variation of the Wyner-Ziv (W-Z) problem pertaining to lossy compression of individual sequences using finite-state encoders and decoders. There are two main results in this paper. The first characterizes the relationship between the performance of the best M-state encoder-decoder pair to that of the best block code of size /spl lscr/ for every input sequence, and shows that the loss of the latter relative to the former (in terms of both rate and distortion) never exceeds the order of (logM)//spl lscr/, independently of the input sequence. Thus, in the limit of large M, the best rate-distortion performance of every infinite source sequence can be approached universally by a sequence of block codes (which are also implementable by finite-state machines). While this result assumes an asymptotic regime where the number of states is fixed, and only the length n of the input sequence grows without bound, we then consider the case where the number of states M=M/sub n/ is allowed to grow concurrently with n. Our second result is then about the critical growth rate of M/sub n/ such that the rate-distortion performance of M/sub n/-state encoder-decoder pairs can still be matched by a universal code. We show that this critical growth rate of M/sub n/ is linear in n.     

Perceived density of road maps

Maps should be designed so that users can comprehend and use the information. Display decisions, such as choosing the scale at which an area is shown, depend on properties of the displayed information such as the perceived density (PD) of the information. Taking a psychophysical approach we suggest that the PD of information in a road map is related to the scale and properties of the mapped area. 54 participants rated the PD of 60 maps from different regions. We provide a simple model that predicts the PD of electronic road map displays, using the logarithm of the number of roads, the logarithm of the number of junctions and the length of the shown roads. The PD model was cross-validated using a different set of 60 maps (n = 44). The model can be used for automatically adjusting display scales and for evaluating map designs, considering the required PD to perform a map-related task.