33188963
Improving the quality of classification trees via restructuring
The classification-hierarchy table developed by Chen and Poon (1996) provides a systematic approach to construct classification trees from given sets of classifications and their associated classes. The paper enhances their study by defining a metric to measure the "quality" of a classification tree, and providing an algorithm to improve this quality.
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.
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.
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.
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.
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.
5909245
Modeling Gene Expression with Differential Equations
We propose a differential equation model for gene expression and provide two methods to construct the model from a set of temporal data. We model both transcription and translation by kinetic equations with feedback loops from translation products to transcription. Degradation of proteins and mRNAs is also incorporated. We study two methods to construct the model from experimental data: Minimum Weight Solutions to Linear Equations (MWSLE), which determines the regulation by solving under-determined linear equations, and Fourier Transform for Stable Systems (FTSS), which refines the model with cell cycle constraints. The results suggest that a minor set of temporal data may be sufficient to construct the model at the genome level. We also give a comprehensive discussion of other extended models: the RNA Model, the Protein Model, and the Time Delay Model.
15532502
Illumination normalization for face recognition and uneven background correction using total variation based image models
We present a new algorithm for illumination normalization and uneven background correction in images, utilizing the recently proposed TV+L/sup 1/ model: minimizing the total variation of the output cartoon while subject to an L/sup 1/-norm fidelity term. We give intuitive proofs of its main advantages, including the well-known edge preserving capability, minimal signal distortion, and scale-dependent but intensity-independent foreground extraction. We then propose a novel TV-based quotient image model (TVQI) for illumination normalization, an important preprocessing for face recognition under different lighting conditions. Using this model, we achieve 100% face recognition rate on Yale face database B if the reference images are under good lighting condition and 99.45% if not. These results, compared to the average 65% recognition rate of the quotient image model and the average 95% recognition rate of the more recent self quotient image model, show a clear improvement. In addition, this model requires no training data, no assumption on the light source, and no alignment between different images for illumination normalization. We also present the results of the related applications - uneven background correction for cDNA mic roar ray films and digital microscope images. We believe the proposed works can serve important roles in the related fields.
1816267
From Region Encoding To Extended Dewey: On Efficient Processing of XML Twig Pattern Matching
Finding all the occurrences of a twig pattern in an XML database is a core operation for efficient evaluation of XML queries. A number of algorithms have been proposed to process a twig query based on region encoding labeling scheme. While region encoding supports efficient determination of structural relationship between two elements, we observe that the information within a single label is very limited. In this paper, we propose a new labeling scheme, called extended Dewey. This is a powerful labeling scheme, since from the label of an element alone, we can derive all the elements names along the path from the root to the element. Based on extended Dewey, we design a novel holistic twig join algorithm, called TJFast. Unlike all previous algorithms based on region encoding, to answer a twig query, TJFast only needs to access the labels of the leaf query nodes. Through this, not only do we reduce disk access, but we also support the efficient evaluation of queries with wildcards in branching nodes, which is very difficult to be answered by algorithms based on region encoding. Finally, we report our experimental results to show that our algorithms are superior to previous approaches in terms of the number of elements scanned, the size of intermediate results and query performance.
60400
A dynamic programming approach to de novo peptide sequencing via tandem mass spectrometry
Tandem mass spectrometry fragments a large number of molecules of the same peptide sequence into charged molecules of prefix and suffix peptide subsequences and then measures mass/charge ratios of these ions. The de novo peptide sequencing problem is to reconstruct the peptide sequence from a given tandem mass spectral data of k ions. By implicitly transforming the spectral data into an NC-spectrum graph G (V, E) where /V/ = 2k + 2, we can solve this problem in O(/V//E/) time and O(/V/2) space using dynamic programming. For an ideal noise-free spectrum with only b- and y-ions, we improve the algorithm to O(/V/ + /E/) time and O(/V/) space. Our approach can be further used to discover a modified amino acid in O(/V//E/) time. The algorithms have been implemented and tested on experimental data.
2301190
On the Informational Asymmetry between Upper and Lower Bounds for Ultrametric Evolutionary Trees
This paper addresses the informational asymmetry for constructing an ultrametric evolutionary tree from upper and lower bounds on pairwise distances between n given species. We show that the tallest ultrametric tree exists and can be constructed in O(n2) time, while the existence of the shortest ultrametric tree depends on whether the lower bounds are ultrametric. The tallest tree construction algorithm gives a very simple solution to the construction of an ultrametric tree. We also provide an efficient O(n2)-time algorithm for checking the uniqueness of an ultrametric tree, and study a query problem for testing whether an ultrametric tree satisfies both upper and lower bounds.