4001661
Configuring common personal software: a requirements-driven approach
We investigate the personalization capabilities of common personal software systems. We use a typical e-mail client as an example of such a system, and examine the configuration screens it offers to its users. We discover that each configuration value reflects each of the ways with which the user goals can be satisfied. Thus, we construct a goal model in which alternative ways for satisfying high level goals are matched with alternative system configurations. This way, automatic configuration of the system by reasoning about the overlaying goal model can be achieved. We find that the vast majority of the configuration options that refer to system functionality can be configured using this method, facilitating thereby the personalization tasks for users with no technical background, and ensuring, at the same time, consistency and meaningfulness in the configuration result.
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.
11507388
JPT: A Java Parallelization Tool
PVM is a succesfull programming environment for distributed computing in the languages C and Fortran. Recently several implementations of PVM for Java have been added, making PVM programming accessible to the Java community. 
 
With PVM for Java however, the user still needs to partition the problem, calculate the data partitioning and program the message passing and synchronization. In this paper, JPT is introduced, a parallelization tool which generates PVM code from a serial Java program. JPT automatically detects parallel loops and generates master and slave PVM programs.
1353091
A Lightweight Approach to Semantic Web Service Synthesis
Web service technologies are becoming a new paradigm for distributed computing. With increasing number of web services available on the internet, there is an urgent need for information brokers that can autonomously integrate web services on behalf of a user. To this end, we propose web service specification, which defines what the service is but not how the service is implemented, and service synthesizer, which can dynamically synthesize the implementation of the specification from existing web services over the web.
5687277
A self-adaptive scheduling algorithm of on-demand broadcasts
In mobile wireless systems data on air can be accessed by a large number of mobile users. Many of these applications such as wireless internets and traffic information systems are pull-based, that is, they respond to on-demand user requests. In this paper, we study the scheduling problems of on-demand broadcast environments. Traditionally, the response time of the requests has been used as a performance measure. In this paper we consider the performance as the average cost of request composed of three kinds of costs—access time cost, tuning time cost, and cost of handling failure request. Our main contribution is a self-adaptive scheduling algorithm named LDFC, which computes the delay cost of data item as the priority for broadcast. It performs well compared with some previous algorithms in this context.
2820577
Localizing XML Documents through XSLT
Existing efforts on XML internationalization and localization have been focusing on the contents of XML documents instead of on the meta presentations such as tags and attributes. Although XML standard allows the use of unicode throughout a document including the meta level presentations, most tags and attributes of XML documents are still defined in English, which makes it difficult for native people to use. This paper presents a pure XSLT stylesheet to completely translate and localize XML documents into different natural languages. Furthermore, we also describe how this technique can be applied to translation problems in programming (e.g. C and Java) or documentation (e.g. LaTeX) languages when the program or the document can be converted to and from XML documents.
7413311
A fast multigrid algorithm for mesh deformation
In this paper, we present a multigrid technique for efficiently deforming large surface and volume meshes. We show that a previous least-squares formulation for distortion minimization reduces to a Laplacian system on a general graph structure for which we derive an analytic expression. We then describe an efficient multigrid algorithm for solving the relevant equations. Here we develop novel prolongation and restriction operators used in the multigrid cycles. Combined with a simple but effective graph coarsening strategy, our algorithm can outperform other multigrid solvers and the factorization stage of direct solvers in both time and memory costs for large meshes. It is demonstrated that our solver can trade off accuracy for speed to achieve greater interactivity, which is attractive for manipulating large meshes. Our multigrid solver is particularly well suited for a mesh editing environment which does not permit extensive precomputation. Experimental evidence of these advantages is provided on a number of meshes with a wide range of size. With our mesh deformation solver, we also successfully demonstrate that visually appealing mesh animations can be generated from both motion capture data and a single base mesh even when they are inconsistent.
8259100
Adapt Bagging to Nearest Neighbor Classifiers
It is well-known that in order to build a strong ensemble, the component learners should be with high diversity as well as high accuracy. If perturbing the training set can cause significant changes in the component learners constructed, then Bagging can effectively improve accuracy. However, for stable learners such as nearest neighbor classifiers, perturbing the training set can hardly produce diverse component learners, therefore Bagging does not work well. This paper adapts Bagging to nearest neighbor classifiers through injecting randomness to distance metrics. In constructing the component learners, both the training set and the distance metric employed for identifying the neighbors are perturbed. A large scale empirical study reported in this paper shows that the proposed BagInRand algorithm can effectively improve the accuracy of nearest neighbor classifiers.
5719748
Leopard: A Locality Aware Peer-to-Peer System with No Hot Spot
Recent research [7,12,2] has shown that Internet hosts can be efficiently (i.e., without excessive measurements) mapped to a virtual (Euclidean) coordinate system, where the geometric distance between any two nodes in this virtual space approximates their real IP network distance (latency). Based on this result, in this paper, we propose an alternative approach that inherently incorporates a virtual coordinate system into a P2P network. In our system, called Leopard, a node is assigned a coordinate in the so-called node geo space as it joins the network, and obtains neighbor relationships that reflects network proximity from the beginning. The object id space and the node geo space are then “weaved” together via a novel technique called geographically-scoped hashing. Through analysis and simulation, we show three major desirable properties of Leopard to exemplify the power of this paradigm shift: i) a constant routing stretch, i.e., IP level network latency of object look-up is proportional to the distance between a requesting node and the target object; ii) always locates a near-by copy when multiple copies exist; and iii) effectively handles “flash crowd” traffic with near optimal load balancing.
1347392
Explaining Low-Level Brightness-Contrast Illusions Using Disinhibition
Conventional Difference of Gaussian (DOG) filter is usually used to model the early stage of visual processing. However, convolution operation used with DOG does not explicitly account for the effects of disinhibition. Because of this, complex brightness-contrast (B-C) illusions such as the White’s effect cannot be explained using DOG filters. We discovered that a model based on lateral disinhibition in biological retinas allows us to explain subtle B-C illusions. Further, we show that a feedforward filter can be derived to achieve this operation in a single pass. The results suggest that contextual effects can be processed through recurrent disinhibition. Such a context sensitive structure might be employed to improve network robustness of visual capturing or displaying systems. Another potential application of this algorithm could be automatic detection and correction of perceived incoherences where accurate perception of intensity level is critical.
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.