28280708
Prioritization of Test Cases in MUMCUT Test Sets: An Empirical Study
Software developers often have to test a program with a large number of test cases to reveal faults in the program. Some of these test cases may detect faults, and some may not. This leads to an important question on how to arrange the test cases to be executed so that more faults can be detected earlier. With a higher rate of fault detection at the early stage of testing, software developers can then spend more time on fixing the faults. This paper studies several ways of prioritizing test cases in a MUMCUT test set, which guarantees to detect certain types of faults in a Boolean specification written in irredundant disjunctive normal form. Our results suggest a certain ordering that reveals more faults earlier in the testing phases.
37474982
A Study on a Path-based Strategy for Selecting Black-box Generated Test Cases
Various black-box methods for the generation of test cases have been proposed in the literature. Many of these methods, including the category-partition method and the classification-tree method, follow the approach of partition testing, in which the input domain is partitioned into subdomains according to important aspects of the specification, and test cases are then derived from the subdomains. Though comprehensive in terms of these important aspects, execution of all the test cases so generated may not be feasible under the constraint of tight testing resources. In such circumstances, there is a need to select a smaller subset of test cases from the original test suite for execution. In this paper, we propose the use of white-box information to guide the selection of test cases from the original test suite generated by a black-box testing method. Furthermore, we have developed some techniques and algorithms to facilitate the implementation of our approach, and demonstrated its viability and benefits by means of a case study.
26872843
Promoting the use of information technology in education via lightweight authoring tools
The potential benefits of using information technology in classrooms for enhancing students' learning have been well known, but the realisation of these benefits is often hindered by a number of factors, notably the lack of knowledge/skills of teachers, the lack of appropriate software, insufficient teacher time, and the limitation of hardware and network infrastructure. In this paper, we introduce the approach of using lightweight authoring tools to address the difficulties faced by teachers. This approach has been adopted on many occasions for the continuing development of primary school teachers in Hong Kong, including many workshops and a formal in-service teacher education course. This paper describes how the approach works, and reports our experiences and the very encouraging feedback we received with the use of lightweight authoring tools.
17708725
An extended fault class hierarchy for specification-based testing
Kuhn, followed by Tsuchiya and Kikuno, have developed a hierarchy of relationships among several common types of faults (such as variable and expression faults) for specification-based testing by studying the corresponding fault detection conditions. Their analytical results can help explain the relative effectiveness of various fault-based testing techniques previously proposed in the literature. This article extends and complements their studies by analyzing the relationships between variable and literal faults, and among literal, operator, term, and expression faults. Our analysis is more comprehensive and produces a richer set of findings that interpret previous empirical results, can be applied to the design and evaluation of test methods, and inform the way that test cases should be prioritized for earlier detection of faults. Although this work originated from the detection of faults related to specifications, our results are equally applicable to program-based predicate testing that involves logic expressions.
3035412
On the Expected Number of Failures Detected by Subdomain Testing and Random Testing
We investigate the efficacy of subdomain testing and random testing using the expected number of failures detected (the E-measure) as a measure of effectiveness. Simple as it is, the E-measure does provide a great deal of useful information about the fault detecting capability of testing strategies. With the E-measure, we obtain new characterizations of subdomain testing, including several new conditions that determine whether subdomain testing is more or less effective than random testing. Previously, the efficacy of subdomain testing strategies has been analyzed using the probability of detecting at least one failure (the P-measure) for the special case of disjoint subdomains only. On the contrary, our analysis makes use of the E-measure and considers also the general case in which subdomains may or may not overlap. Furthermore, we discover important relations between the two different measures. From these relations, we also derive corresponding characterizations of subdomain testing in terms of the P-measure.
45848865
Optimal improvement of the lower bound performance of partition testing strategies
Although partition testing strategies are intuitively more appealing than random testing, previous empirical and analytical studies show that under unfavourable circumstances partition testing can be very ineffective. The problem of maximally improving the lower bound performance of partition testing by the choice of appropriate test distributions is investigated. An algorithm that generates optimal test distributions for this purpose is proposed and analysed. Moreover, the algorithm can also serve to systematically approximate the proportional sampling strategy, which has previously been proved to be at least as good as random testing.
723568
A Bayesian Network Approach to Ontology Mapping
This paper presents our ongoing effort on developing a principled methodology for automatic ontology mapping based on BayesOWL, a probabilistic framework we developed for modeling uncertainty in semantic web. In this approach, the source and target ontologies are first translated into Bayesian networks (BN); the concept mapping between the two ontologies are treated as evidential reasoning between the two translated BNs. Probabilities needed for constructing conditional probability tables (CPT) during translation and for measuring semantic similarity during mapping are learned using text classification techniques where each concept in an ontology is associated with a set of semantically relevant text documents, which are obtained by ontology guided web mining. The basic ideas of this approach are validated by positive results from computer experiments on two small real-world ontologies.
40955801
Polarimetric SAR image segmentation using texture partitioning and statistical analysis
This paper presents a new technique for partitioning polarimetric synthetic aperture radar (POL-SAR) imagery into regions of homogeneous polarimetric backscattering properties. The method consists of two cascaded steps: an initial texture segmentation of one image derived from the POL-SAR data, and a polarimetric statistical region merging process that refines and modifies the initial segmentation. In the first stage, a morphological region-based image partitioning technique, the watershed algorithm, plays the key role. While in the second stage, the region adjacency graph and the segment dissimilarity measures derived from the Wishart model and the K distribution are applied. The overall segmentation algorithm has been tested using real 4-look POL-SAR imagery and sample results are provided in the paper. The main innovation of this work is the utilization of the K distribution in the segmentation process.
11078824
Reducing build time through precompilations for evolving large software
Large-scale legacy programs take long time to compile, thereby hampering productivity. This paper presents algorithms that reduce compilation time by analyzing syntactic dependencies in fine-grain program units, and by removing redundancies as well as false dependencies. These algorithms are combined with parallel compilation techniques (compiler farms, compiler caches), to further reduce build time. We demonstrate through experiments their effectiveness in achieving significant speedup for both fresh and incremental builds.
9459993
From goals to aspects: discovering aspects from requirements goal models
Aspect-oriented programming (AOP) has been attracting much attention in the software engineering community by advocating that programs should be structured according to programmer concerns, such as "efficient use of memory". However, like other programming paradigms in their early days, AOP hasn't addressed yet earlier phases of software development. In particular, it is still an open question how one identifies aspects early on in the software development process. This work proposes an answer to this question. Specifically, we show that aspects can be discovered during goal-oriented requirements analysis. Our proposal includes a systematic process for discovering aspects from relationships between functional and nonfunctional goals. We illustrate the proposed process with a case study adapted from the literature.
1769883
FRM based FIR filter design - the WLS approach
Frequency-response masking (FRM) technique produces a filter network which comprises several sub-filters with very sparse coefficient values. If the sub-filters are optimized separately, the overall filter network will be suboptimal. In this paper, an unconstrained weighted least squares algorithm for simultaneously optimizing the sub-filters generated by the frequency-response masking technique is presented. Simulation runs show that our proposed technique produces significant reduction in the effective filter length.