14180342
On Some Properties of the Optimally Refined Proportional Sampling Strategy
The optimally refined proportional sampling strategy has been recommended as a better alternative to random testing, when dividing the input domain into equal-sized partitions is easy. This paper investigates some properties of the optimally refined proportional sampling strategy. This investigation provides some useful information on how well the optimally refined proportional sampling strategy outperforms random testing.
29539871
On the effectiveness of classification trees for test case construction
Abstract The notion of the classification-hierarchy table and the classification-tree construction algorithm provide a systematic approach to the construction of classification trees from given sets of classifications and their associated classes. Using classification trees, the set of all possible test cases can be constructed from functional specifications. This paper extends their study by introducing a metric to measure the effectiveness of a classification tree with respect to the construction of test cases, and providing ways to improve this effectiveness.
26835658
On the test allocations for the best lower bound performance of partition testing
A partition testing strategy divides the program's input domain into subdomains according to a partitioning scheme, and selects test cases from each subdomain according to a test allocation scheme. Previous studies have shown that partition testing strategies can be very effective or very ineffective in detecting faults, depending on both the partitioning scheme and the test allocation scheme. Given a partitioning scheme, the maximin criterion chooses a test allocation scheme that will maximally improve the lower bound performance of the partition testing strategy. In an earlier work, we have proved that the Basic Maximin Algorithm can generate such a test allocation scheme. In this paper, we derive further properties of the Basic Maximin Algorithm and present the Complete Maximin Algorithm that generates all possible test allocation schemes that satisfy the maximin criterion.
12141135
Construction of classification trees via the classification-hierarchy table
Abstract The classification-tree method developed by Grochtmann and coworkers is a black box testing technique to assist test engineers to construct test cases systematically from the functional specifications, via the construction of classification trees. This paper supplements their studies by proposing a methodology to construct classification trees systematically from given sets of classifications and their associated classes, via the notion of the classification-hierarchy table. The intuition of the classification-hierarchy table is to capture the hierarchical relationship for every pair of distinct classifications from which classification trees can be constructed.
44900435
Two test data selection strategies towards testing of Boolean specifications
Test data selection for software represented as Boolean formulae has not received much attention until the last decade. Most of the approaches are expression driven because generation of test cases is based on the Boolean formulae being tested. The paper discusses test data generation using a fault based approach in the sense that generation of test cases is based on particular types of faults occurring in the Boolean expression. Two special types of faults are considered. Moreover, two strategies of test case selection that guarantee the detection of these two types of faults are proposed.
28566545
A new heuristic for test suite reduction
Abstract A testing objective has to be defined in testing a program. A test suite is then constructed to satisfy the testing objective. The constructed test suite contains redundancy when some of its proper subsets can still satisfy the same testing objective. Since the costs of executing test cases and maintaining a test suite for regression testing may be expensive, the problem of test suite reduction arises. This paper proposes a heuristic towards the optimization of a test suite.
8821639
Realistic video avatar
We present a system for the implementation of a photorealistic avatar using video captured from a user. This is achieved by constructing the dynamic video texture map and combining it with the 3D mesh model of the user to render the photorealistic avatar. The dynamic video texture map reflects the user's facial expressions and is generated by composing the cylindrical texture map of the user with constant updates either directly from the input video or derived from a temporal and spatial interpolation scheme. To derive the 3D mesh model for the user, we define feature points on a generic model and use the feature points identified on the video sequence to deform and obtain the avatar model. The goal of this realistic video avatar project is to provide a vivid representation of participants with a more realistic quality avatar, as compared to using only the facial animation parameters defined in MPEG-4 without the corresponding image updates. This scheme is suitable for conferencing applications because it requires much lower bandwidth than live video, and yet provides a 3D avatar representation for any virtual environment.
31957165
International Symposium on Quality Electronic Design
10812503
Mapping gene ontology to proteins based on protein-protein interaction data
MOTIVATION
Gene Ontology (GO) consortium provides structural description of protein function that is used as a common language for gene annotation in many organisms. Large-scale techniques have generated many valuable protein-protein interaction datasets that are useful for the study of protein function. Combining both GO and protein-protein interaction data allows the prediction of function for unknown proteins.


RESULT
We apply a Markov random field method to the prediction of yeast protein function based on multiple protein-protein interaction datasets. We assign function to unknown proteins with a probability representing the confidence of this prediction. The functions are based on three general categories of cellular component, molecular function and biological process defined in GO. The yeast proteins are defined in the Saccharomyces Genome Database (SGD). The protein-protein interaction datasets are obtained from the Munich Information Center for Protein Sequences (MIPS), including physical interactions and genetic interactions. The efficiency of our prediction is measured by applying the leave-one-out validation procedure to a functional path matching scheme, which compares the prediction with the GO description of a protein's function from the abstract level to the detailed level along the GO structure. For biological process, the leave-one-out validation procedure shows 52% precision and recall of our method, much better than that of the simple guilty-by-association methods.
11068219
An approximation algorithm for haplotype inference by maximum parsimony
This paper studies haplotype inference by maximum parsimony using population data. We define the optimal haplotype inference (OHI) problem as given a set of genotypes and a set of related haplotypes, find a minimum subset of haplotypes that can resolve all the genotypes. We prove that OHI is NP-hard and can be formulated as an integer quadratic programming (IQP) problem. To solve the IQP problem, we propose an iterative semi-definite programming based approximation algorithm, (called SDPHapInfer). We show that this algorithm finds a solution within a factor of O(logn) of the optimal solution, where n is the number of genotypes. This algorithm has been implemented and tested on a variety of simulated and biological data. In comparison with three other methods: HAPAR, HAPLOTYPER, and PHASE, the experimental results indicate that SDPHapInfer and HAPLOTYPER have similar error rates. In addition, the results generated by PHASE have lower error rates on some data but higher error rates on others. The error rates of HAPAR are higher than the others on biological data. In terms of efficiency, SDPHapInfer, HAPLOTYPER, and PHASE output a solution in a stable and consistent way, and they run much faster than HAPAR when the number of genotypes becomes large.
45004012
Dual-Hamiltonian-path-based multicasting on wormhole-routed star graph interconnection networks
The star graph interconnection network has been recognized as an attractive alternative to the popular hypercube network. In this paper we first address a dual-Hamiltonian-path-based (DHPB) routing model with two virtual channels based on two Hamiltonian paths and a network partitioning strategy for wormhole-routed star graph networks. Then, we propose three efficient multicast routing schemes on basis of such a model. The proposed schemes are network-selection-based (NSB), heuristic-network-selection-based (HNSB), and two-phase heuristic-network-selection-based (TP-HNSB) dual-path routing. All of the three proposed schemes are deadlock-free. Finally, experimental results are given to show our proposed three routing schemes outperform the unicast-based, the Hamiltonian-path, and the single-Hamiltonian-path-based (SHPB) dual-path routing schemes significantly.