15561253
An experimental comparison of four test suite reduction techniques
As a test suite usually contains redundancy, a subset of the test suite (representative set) may still satisfy all the test objectives. As the redundancy increases the cost of executing the test suite, many test suite reduction techniques have been brought out in spite of the NP-completeness of the general problem of finding the optimal representative set of the test suite. In the literature, some experimental studies of test suite reduction techniques have already been reported, but there are still shortcomings of the studies of these techniques. This paper presents an experimental comparison of the four typical test suite reduction techniques: heuristic H, heuristic GRE, genetic algorithm-based approach and ILP-based approach. The aim of the study is to provide a guideline for choosing the appropriate test suite reduction techniques.
22235359
Towards an Optimization-Based Method for Consolidating Domain Variabilities in Domain-Specific Web Services Composition
In this paper, we put forward an automatic method of acquiring the specific system composition model from a domain composition model and requirements for the specific system in domain-specific Web services composition. This is referred to as the variability consolidation problem in this paper. To achieve this goal, we designed a language to describe domain properties for Web services composition. The basis of our approach is to transform the domain composition model and the requirements for the specific system into a mathematical optimization problem, which can be solved by existing algorithms. Thus, this method is fully automatic and not prone to human errors. Our preliminary experimental results show that our method is quite feasible for solving problems with real world sizes.
6538157
Threshold Tuning for Improved Classification Association Rule Mining
One application of Association Rule Mining (ARM) is to identify Classification Association Rules (CARs) that can be used to classify future instances from the same population as the data being mined. Most CARM methods first mine the data for candidate rules, then prune these using coverage analysis of the training data. In this paper we describe a CARM algorithm that avoids the need for coverage analysis, and a technique for tuning its threshold parameters to obtain more accurate classification. We present results to show this approach can achieve better accuracy than comparable alternatives at lower cost.
17777200
A similarity-aware approach to testing based fault localization
Debugging is a time-consuming task in software development and maintenance. To accelerate this task, several approaches have been proposed to automate fault localization. In particular, testing based fault localization (TBFL), which utilizes the testing information to localize the faults, seem to be very promising. However, the similarity between test cases in the test suite has been ignored in the research on TBFL. In this paper, we investigate this similarity issue and propose a novel approach named similarity-aware fault localization (SAFL), which can calculate the suspicion probability of each statement with little impact by the similarity issue. To address and deal with the similarity between test cases, SAFL applies the theory of fuzzy sets to remove the uneven distribution of the test cases. We also performed an experimental study for two real-world programs at different size levels to evaluate SAFL together with another two approaches to TBFL. Experimental results show that SAFL is more effective than the other two approaches when the test suites contain injected redundancy, and SAFL can achieve a competitive result with normal test suites. SAFL can also be more effective than applying test suite reduction to current approaches to TBFL.
18465833
Contract-based mutation for testing components
Testing plays an important role in the maintenance of component based software development. Test adequacy for component testing is one of the hardest issues for component testing. To tackle this problem, it is a natural idea to apply mutation testing, which is a fault-based testing method used for measuring test adequacy, for component contracts, whose aim is to improve the testability of the component. Though powerful, mutation testing is usually very computation-expensive, as many mutants need to be produced and executed in mutation testing. In this paper, we propose a contract-based mutation technique for testing components. Based on the discordance between contracts and specification, our approach employs a set of high level contract mutation operators. The experimental results show that these operators can greatly reduce the number of mutants compared with traditional mutation operators. At the same time, the contract-based mutation using our contract mutation operators can provide almost the same ability as that of using traditional mutation operators. Moreover, effective test suite can be produced to reduce the maintenance effort.
13211852
Requirements guided dynamic software clustering
In this paper, we propose a requirements guided dynamic approach to address software clustering -which aims at providing the logically meaningful and high-level decompositions of large and complex systems. In our approach, the hierarchical structure of functional requirements are constructed by a text document clustering technique named hierarchical agglomerative clustering (HAC) as a high-level skeleton to facilitate the further decomposition of source code through dynamic analysis. We also perform an experimental study based on a GNU system and present the quantitative and qualitative analysis of the experimental results.
15556637
Proximity problems on moving points
A kinetic data structure for the maintenance of a multidimensional range search tree is introduced. This structure is used as a building block to obtain kinetic data structures for two classical geometric proximity problems in arbitrary dlmensions: the first structure maintains the closest pair of a set of continuously moving points, and is provably efficient. The second structure maintains a spanning tree of the moving points whose cost remains within some prescribed factor of the minimum spanning tree.
5771208
Image annotation by large-scale content-based image retrieval
Image annotation has been an active research topic in recent years due to its potentially large impact on both image understanding and Web image search. In this paper, we target at solving the automatic image annotation problem in a novel search and mining framework. Given an uncaptioned image, first in the search stage, we perform content-based image retrieval (CBIR) facilitated by high-dimensional indexing to find a set of visually similar images from a large-scale image database. The database consists of images crawled from the World Wide Web with rich annotations, e.g. titles and surrounding text. Then in the mining stage, a search result clustering technique is utilized to find most representative keywords from the annotations of the retrieved image subset. These keywords, after salience ranking, are finally used to annotate the uncaptioned image. Based on search technologies, this framework does not impose an explicit training stage, but efficiently leverages large-scale and well-annotated images, and is potentially capable of dealing with unlimited vocabulary. Based on 2.4 million real Web images, comprehensive evaluation of image annotation on Corel and U. Washington image databases show the effectiveness and efficiency of the proposed approach.
6941919
Optimizations for Compiling Declarative Models into Boolean Formulas
Advances in SAT solver technology have enabled many automated analysis and reasoning tools to reduce their input problem to a SAT problem, and then to use an efficient SAT solver to solve the underlying analysis or reasoning problem. The solving time for SAT solvers can vary substantially for semantically identical SAT problems depending on how the problem is expressed. This property motivates the development of new optimization techniques whose goal is to produce more efficiently solvable SAT problems, thereby improving the overall performance of the analysis or reasoning tool. 
 
This paper presents our experience using several mechanical techniques that enable the Alloy Analyzer to generate optimized SAT formulas from first-order logic formulas. These techniques are inspired by similar techniques from the field of optimizing compilers, suggesting the potential presence of underlying connections between optimization problems from two very different domains. Our experimental results show that our techniques can deliver substantial performance improvement results—in some cases, they reduce the solving time by an order of magnitude.
10973415
A testbed for evaluation and analysis of stepping stone attack attribution techniques
This paper describes a testbed for experimentally evaluating stepping stone attack attribution techniques. There is a lack of comprehensive experimental evaluation of many different stepping stone attack detection schemes. Therefore, there are no objective, comparable evaluation results on the effectiveness and limitations of these schemes. In this research, we designed and built a scalable testbed environment that can evaluate all existing stepping stone attack attribution schemes reproducibly, provide a stable platform for further research on this area and be easily reconfigured, expanded, and operated with user-friendly interface. This testbed environment has been established in a dedicated stepping stone attack attribution research laboratory. An evaluation of proposed stepping stone techniques is currently underway
10515113
Validating SAT solvers using an independent resolution-based checker: practical implementations and other applications
As the use of SAT solvers as core engines in EDA applications grows, it becomes increasingly important to validate their correctness. In this paper, we describe the implementation of an independent resolution-based checking procedure that can check the validity of unsatisfiable claims produced by the SAT solver zchaff. We examine the practical implementation issues of such a checker and describe two implementations with different pros and cons. Experimental results show low overhead for the checking process. Our checker can work with many other modern SAT solvers with minor modifications, and it can provide information for debugging when checking fails. Finally we describe additional results that can be obtained by the validation process and briefly discuss their applications.