Gavriel Yarmish

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Although programmer errors have been investigated, only a limited range of error types typically made by novices have been scrutinized. In this paper we present an expanded classification of the types of errors considered in previous research. In particular, problems which require the use of more difficult program constructs such as nested loops, arrays,(More)
We present a simple, scaleable, distributed simplex implementation for large linear programs. It is designed for coarse-grained computation, particularly, readily available networks of workstations. Scalability is achieved by using the standard form of the simplex rather than the revised method. Virtually all serious implementations are based on the revised(More)
To date there has been considerable investigation into the study of novice programmer errors. The research has analyzed both syntactic and semantic errors. However, the next level of programmers, who make more sophisticated errors, the internmediate level programmers, have been somewhat neglected. In this paper, we focus on the nature of the errors which(More)
One important tool is the optimal clustering of data into useful categories. Dividing similar objects into a smaller number of clusters is of importance in many applications. These include search engines, monitoring of academic performance, biology and wireless networks. We first discuss a number of clustering methods. We present a parallel algorithm for(More)
In this paper we discuss results and advantages of using steepest edge column choice rules and their derivatives. We show empirically, when we utilize the steepest edge column choice rule for the tableau method, that the density crossover point at which the tableau method is more efficient than the revised method drops to 5%. This is much lower than the 72%(More)
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