3504482
An Intelligent Test Data Generator for Software Branch Coverage
1207779
Experience in Teaching a Management-Oriented Capstone Software Engineering Course
Many computer science departments teach a capstone software engineering course involving the design and implementation of a large-scale project. Such a course is normally taught with students working together in teams; consequently, students must face a number of problems related to project management and team dynamics. Our experience has been that students frequently fail to adequately cope with these organizational problems, and consequently fail to complete their projects at an acceptable level of quality. To prepare students to better face these problems, we have modified our capstone software engineering course to provide equal emphasis in both management and technical areas. Our approach to management topics is formal rather than anecdotal, stressing general principles applied to organizational problems arising specifically from situations that occur frequently in technical organizations. This paper reports on the structure of this course, and provides insight into our initial experience in teaching it.
317687
A Cost Model for Determining the Optimal Number of Software Test Cases
A probabilistic model is presented that demonstrates the optimal number of software test cases required in situations where the following can be estimated as independent parameters: (1) the cost per test; (2) the cost per error if undetected until field implementation; (3) the number of software executions over its lifetime; (4) the number of possible different executions; and (5) the number of faults embedded in the software. A formula is derived by the use of calculus and is solved by approximation techniques. Tables of the optimal number of tests over a range of parameter values are presented to illustrate the results. The model serves as a basis for further research efforts to improve the accuracy of input variable estimation. >
12974717
A System for Learning Routes and Schedules with Genetic Algorithms
34635988
Virtual Travel Training for People with Learning Disabilities Accessing Employment Including the Introduction to the Special Thematic Session "Virtual Reality"
The purpose of this project is to develop a Virtual Learning Environment to assist in the travel training of a group of people with learning disabilities to enable them to gain access to training and employment opportunities. To achieve this a realistic Virtual Travel in Sutton Package will be developed to assist people with special needs to learn independent travel skills, and to assess the effectiveness of the software in achieving this aim.
10497047
Markov Random Field Modelling of Royal Road Genetic Algorithms
Markov Random Fields (MRFs) [5] are a class of probabalistic models that have been applied for many years to the analysis of visual patterns or textures. In this paper, our objective is to establish MRFs as an interesting approach to modelling genetic algorithms. Our approach bears strong similarities to recent work on the Bayesian Optimisation Algorithm [9], but there are also some significant differences. We establish a theoretical result that every genetic algorithm problem can be characterised in terms of a MRF model. This allows us to construct an explicit probabilistic model of the GA fitness function. The model can be used to generate chromosomes, and derive a MRF fitness measure for the population. We then use a specific MRF model to analyse two Royal Road problems, relating our analysis to that of Mitchell et al. [7].
1252083
Formal Security Proofs for a Signature Scheme with Partial Message Recovery
The Pintsov-Vanstone signature scheme with partial message recovery (PVSSR) is a signature scheme with low message expansion (overhead) and variable length recoverable and non-recoverable message parts. The scheme uses three cryptographic primitives: a symmetric cipher, hash function and an elliptic curve group. We give three security proofs for PVSSR in this paper. Each proof makes a concrete and necessary assumption about one primitive, and models the other two primitives by idealizations. Thus, PVSSR with a strong cipher may offer greater security than other common variants of ElGamal signatures.
8716134
Classification and Boundary Vagueness in Mapping Presettlement Forest Types
Presettlement forest types were mapped as fuzzy sets from point data representing trees contained in General Land Office survey notes (circa 1850) for Chippewa County, Michigan. The resulting representation agreed with a polygon map of the same forest types at 66% of the locations (represented as grid cells) in the county. Boundary vagueness was defined in relation to the slope of a linear function fitted to the negative relation between entropy offorest types and distance to polygon boundaries. The similarity between forest type compositions (i.e. classification ambiguity) was shown to account for 55% of the variation in boundary vagueness.