Derek F. Yates

Reducing the effects of infeasible paths in branch testing

Branch testing, which is one of the most widely used methods for program testing, see White [1] for example, involves executing a selected set of program paths in an attempt to exercise all program branches. Criteria for selecting such paths have, to date, received scant attention in the literature and it is the issue of developing a suitable path selection strategy to which this paper is addressed. Specifically, a selection strategy, which aims at reducing the number of infeasible paths generated during the branch testing exercise is proposed. The strategy is founded on an assertion concerning the likely feasibility of program paths. Statistical evidence in support of the assertion is provided, a method implementing the strategy is described, and the results obtained from applying the method to a set of program units are reported and analysed.

Load balancing and capacity constraints in a hierarchical location model

Recent work on the location of perinatal facilities in the municipality of Rio de Janeiro resulted in the development of an uncapacitated, three-level hierarchical model. An important issue that arose during the course of the research was the need to include some form of capacity constraints into the model, especially in the higher, resource intensive level of the hierarchy. This need was felt from technical discussions related to the research work and from contacts with municipality health officials. A capacitated model is presented and solved using a Lagrangean heuristic. For smaller problems optimal solutions are found using CPLEX; it is found that the heuristic usually gives high quality solutions. Next a bi-criterion model is formulated in which the additional objective measure is the imbalance in facility loading. This is solved exactly for a small problem and approximately for the 152-vertex Rio de Janeiro data. � 2004 Elsevier B.V. All rights reserved.

An algorithm to locate perinatal facilities in the municipality of Rio de Janeiro

In order to reduce infant mortality in the municipality of Rio de Janeiro it is desired to encourage all mothers-to-be to attend the appropriate health care facilities. A 3-level hierarchical prenatal–neonatal health care system is described together with a basic model for optimising accessibility to facilities. A genetic algorithm to solve the basic model is developed and some numerical experience reported. Extensions to the basic model and planned future research are briefly indicated.

Inductive Operators and Rule Repair in a Hybrid Genetic Learning System: Some Initial Results

Symbolic knowledge representation schemes have been suggested as one way to improve the performance of classifier systems in the context of complex, real-world problems. The main reason for this is that unlike the traditional binary string representation, high-level languages facilitate the exploitation of problem specific knowledge. However, the two principal genetic operators, crossover and mutation, are, in their basic form, ineffective with regard to discovering useful rules in such representations. Moreover, the operators do not take into account any environmental cues which may benefit the rule discovery process. A further source of inefficiency in classifier systems concerns their capacity for forgetting valuable experience by deleting previously useful rules.

Network reliability and the probabilistic estimation of damage from fire spread

An efficient generalization of Shanthikumars upper bound on two-terminal reliability is developed, that leads to efficient methods for the probabilistic assessment of damage from fire spread and other invasive hazards in segmented structures. The methods exploit a basic relationship between the fire spread problem and the probability of reachability in communications networks. The upper bound employs noncrossing cuts of the network.

The effort required by LCSAJ testing: an assessment via a new path generation strategy

In general, LCSAJ testing more thoroughly exercises the control structure of a piece of software than does either statement or branch testing. Despite this, the exceptionally small number of papers which detail experience of using LCSAJ testing clearly indicates that its popularity falls considerably short of that of the other two methods. One factor that has contributed to this situation is the apparent absence of any attempt to assess the effort entailed by LCSAJ testing in practice, thereby precluding any meaningful cost-effectiveness analysis of the method. Such an attempt is reported in this paper.A significant influence on the effort associated with LCSAJ testing is the number of test paths that must be generated to achieve a specified level of cover, and this is determined by the number of such paths that are found to be infeasible. Effort, therefore, is dependent upon the effectiveness of the path generation method/strategy in avoiding infeasible paths. The attempt to assess the effort entailed by LCSAJ testing which is reported here makes use of a new path selection strategy. This strategy seeks to reduce,a priori, the incidence of infeasible paths in the test set that is generated. Details of the strategy are presented, as are the results which were obtained by applying it to a set of subroutines. From the results, a measure of the effort entailed in employing the strategy is deduced. Subsequently, it is argued that features of the strategy enable pertinent comments to be made not only about the effort associated with employing the strategy, but also about the effort entailed by LCSAJ testing in general.