31408844
A component-based software configuration management model and its supporting system
Software configuration management (SCM) is an important key technology in software development. Component-based software development (CBSD) is an emerging paradigm in software development. However, to apply CBSD effectively in real world practice, supporting SCM in CBSD needs to be further investigated. In this paper, the objects that need to be managed in CBSD is analyzed and a component-based SCM model is presented. In this model, components, as the integral logical constituents in a system, are managed as the basic configuration items in SCM, and the relationships between/among components are defined and maintained. Based on this model, a configuration management system is implemented.
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.
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.
19304521
Applying OO Metrics to Assess UML Meta-models
UML has been coming of age through more than seven years development, in which there are not only minor revision like from UML 1.1 to UML 1.2, but also significant improvement like final adoption of UML 2.0 submissions. However there is so far lack of an objective assessment to UML meta-models, which can be used to control and predict the evolution of the UML. In this paper we regard UML meta-models as the equivalent of Object-Oriented (OO) design models. Therefore, we can adapt OO design metrics and criteria as a method to assess UML meta-models. Our method conducts the assessment of stability and design quality to UML meta-models in versions of 1.1, 1.3, 1.4 (with Action Semantics), 1.5, and 2.0. Based on the results we analyze the evolution of the UML versions and provide the applicability suggestions to the method.
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.
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.
6781663
Parallel Image Matrix Compression for Face Recognition
The canonical face recognition algorithm Eigenface and Fisherface are both based on one dimensional vector representation. However, with the high feature dimensions and the small training data, face recognition often suffers from the curse of dimension and the small sample problem. Recent research [4] shows that face recognition based on direct 2D matrix representation, i.e. 2DPCA, obtains better performance than that based on traditional vector representation. However, there are three questions left unresolved in the 2DPCA algorithm: I ) what is the meaning of the eigenvalue and eigenvector of the covariance matrix in 2DPCA; 2) why 2DPCA can outperform Eigenface; and 3) how to reduce the dimension after 2DPCA directly. In this paper, we analyze 2DPCA in a different view and proof that is 2DPCA actually a "localized" PCA with each row vector of an image as object. With this explanation, we discover the intrinsic reason that 2DPCA can outperform Eigenface is because fewer feature dimensions and more samples are used in 2DPCA when compared with Eigenface. To further reduce the dimension after 2DPCA, a two-stage strategy, namely parallel image matrix compression (PIMC), is proposed to compress the image matrix redundancy, which exists among row vectors and column vectors. The exhaustive experiment results demonstrate that PIMC is superior to 2DPCA and Eigenface, and PIMC+LDA outperforms 2DPC+LDA and Fisherface.
46728562
Membership Portal and Service Provisioning System for an Infrastructure of Hubs: Managed E-Hub
The goal of Managed e-Hub research prototype is to build a common infrastructure of hubs so that businesses can develop B2B exchanges meeting their business needs based on it. In this paper, an open and extensible framework for Managed e-Hub is presented and the hub fundamental services are discussed in detail as well. The service provisioning system of Managed e-Hub not only provides a way of integrating other services into the hub by means of service on-boarding and subscription, but also provisions these services with their required provisioning information.
36054855
MQML-Message Queuing Markup Language
Message Queuing allows applications to use components that communicate with one another using queued messages. In this paper, we propose a Message Queuing Markup Language (MQML), which is an XML based markup language designed to describe e-business applications and enterprise integration. The MQML language is extensible. The detailed description of the MQML is presented in this paper. An research prototype is given to validate the effectiveness and value of our proposed MQML for enterprise integration.
22470543
A Weighted Technique in Heuristic Search
As shown in [1], we examine search as a statistic sampling process. Based on some statistical inference method the probability that a subtree in search tree contains the goal can be decided. Thus some weight is in tentionaly added to the evaluation function of those nodes which are unlikely in the solution path so that the search will concentrate on the most promising path. It results in a new weighted algorithm-WSA. 
 
Tn a uniform m-ary tree, we show that a goal can be found by WSA in the polynomial time, although the computational complexity of A (or A*) may be O(e) for searching the same space. Where N is the depth at which the goal is located.
8187115
Modeling location management in wireless networks with generally distributed parameters
In the wireless mobile networks, location update (LU) and paging are two basic operations in the framework of mobility management. The trade-off analysis between LU and paging is traditionally performed under the assumption that the key variables follow exponential distribution. However, recent work showed that such assumptions may be incorrect. In this paper, by introducing the concept of LU inter-arrival time and additionally relaxing the assumptions for the inter-service time, cell residence time and LU inter-arrival time, we present an analytical technique to develop the closed-form formula for the signaling cost applicable to different location management schemes. Specifically, the result is applied to the static scheme and the dynamic movement-based scheme to demonstrate the general applicability. Illustrative numerical examples are given to compare the location management scheme performance based on the cell characteristics.