270888
Performance Evaluation and Prediction for Legacy Information Systems
Database-centric information systems are critical to the operations of large organisations. In particular, they often process a large amount of data with stringent performance requirements. Currently, however, there is a lack of systematic approaches to evaluating and predicting their performance when they are subject to an exorbitant growth of workload. In this paper, we introduce such a systematic approach that combines benchmarking, production system monitoring, and performance modelling (BMM) to address this issue. The approach helps the performance analyst to understand the system's operating environment and quantify its performance characteristics under varying load conditions via monitoring and benchmarking. Based on such realistic measurements, modelling techniques are used to predict the system performance. Our experience of applying BMM to a real-world system demonstrates the capability of BMM in predicting the performance of existing and enhanced software architectures in planning for its capacity growth.
629310
Semantic and Usage Packaging for Software Components
Current models for software components have made component-based software engineering practical. However, these models are limited in the sense that their support for the specification of software components primarily deals with syntactic issues. To facilitate interoperability and proper use of software components, more comprehensive specification of these components is required. In this paper, we present an approach to software component packaging aimed at comprehensive component specification, especially its support for semantic and usage specification.
1659291
A Software Engineering Perspective for Services Security
Services are usually developed and deployed independently; and systems can be formed by composing relevant services to achieve set goals. In such an open and dynamic environment, security is of paramount importance. We have seen much work in the traditional area of information and network security, focusing on developing various security techniques. More recently, there have been efforts in integrating the security techniques into languages and infrastructural support that are used for developing services and systems. In fact, the development of services and the composition of service-based systems are software engineering activities. As such, they need to be viewed from a software engineering perspective. In this paper, we introduce an approach to services security engineering, to answer the questions like what the security properties of services and service-based systems are and how they meet the user’s security requirements. It deals with the issues of (1) security property characterisation for services, (2) compositional security analysis for service-based systems, and (3) certification of services.
1745958
Industrial Perspective on the Usefulness of Design Rationale for Software Maintenance: A Survey
Software maintenance is widely known as a problematic area that may consume up to 80% of a software project's resources. It has been claimed that providing an effective mechanism to access design rationale (DR) has great potential to improve software maintenance processes. However, we postulate that the first step towards exploring the potential of DR for improving software maintenance should be to gain a better understanding of what DR means to practitioners, how valuable they consider DR to be and how they use DR. To determine the perceived usefulness of DR, we surveyed a large number of software designers. This exploratory study has discovered that practitioners recognize the importance of DR to understand existing designs and frequently use it to reason about proposed modifications. The results of this study establish that DR is perceived by practitioners to be useful and the efforts required to capture DR for the purpose of maintenance are worthwhile. The findings allow us to identify areas of further research on DR support that have the potential to improve the maintenance process
17910560
Providing configuration management support in software engineering environments
Software configuration management (CM) is a key element of any software development project. A software engineering environment should not only provide support for software products and software processes in general, but also pay attention to high-level software engineering concepts like CM. In this paper, we present an overview of our approach to software engineering environments and demonstrate how CM can be achieved in such environments with minimal effort by codifying a CM model. Issues addressed include the structures and consistency of CM components and their relationships, the definition and activation of CM operations, and the definition of presentation views that facilitate CM activities.
3251598
TRAM: a tool for requirements and architecture management
Management of system requirements and system architectures is part of any software engineering project. But it is usually very tedious and error prone. In particular, managing the traceability between system requirements and system architectures is critical but difficult. The article introduces a tool, TRAM, for managing system requirements, system architectures and more importantly the traceability between them. Its primary design objective is "being practical" and ready for practitioners to use without much overhead. The issues discussed in the paper include an information model that underlies the capture of requirements, architectures and their traceability, a set of document templates implementing the information model, and the support tool.
2940771
Graph indexing: a frequent structure-based approach
Graph has become increasingly important in modelling complicated structures and schemaless data such as proteins, chemical compounds, and XML documents. Given a graph query, it is desirable to retrieve graphs quickly from a large database via graph-based indices. In this paper, we investigate the issues of indexing graphs and propose a novel solution by applying a graph mining technique. Different from the existing path-based methods, our approach, called gIndex, makes use of frequent substructure as the basic indexing feature. Frequent substructures are ideal candidates since they explore the intrinsic characteristics of the data and are relatively stable to database updates. To reduce the size of index structure, two techniques, size-increasing support constraint and discriminative fragments, are introduced. Our performance study shows that gIndex has 10 times smaller index size, but achieves 3--10 times better performance in comparison with a typical path-based method, GraphGrep. The gIndex approach not only provides and elegant solution to the graph indexing problem, but also demonstrates how database indexing and query processing can benefit form data mining, especially frequent pattern mining. Furthermore, the concepts developed here can be applied to indexing sequences, trees, and other complicated structures as well.
43532686
AIM: Approximate Intelligent Matching for Time Series Data
Time-series data mining presents many challenges due to the intrinsic large scale and high dimensionality of the data sets. Subsequence similarity matching has been an active research area driven by the need to analyse large data sets in the financial, biomedical and scientific databases. In this paper, we investigate an intelligent subsequence similarity matching of time series queries based on efficient graph traversal. We introduce a new problem, the approximate partial matching of a query sequence in a time series database. Our system can address such queries with high specificity and minimal time and space overhead. The performance bottleneck of the current methods were analysed and we show our method can improve the performance of the time series queries significantly. It is general and flexible enough to find the best approximate match query without specifying a tolerance Ɛ parameter.
17959434
Graph indexing based on discriminative frequent structure analysis
Graphs have become increasingly important in modelling complicated structures and schemaless data such as chemical compounds, proteins, and XML documents. Given a graph query, it is desirable to retrieve graphs quickly from a large database via indices. In this article, we investigate the issues of indexing graphs and propose a novel indexing model based on discriminative frequent structures that are identified through a graph mining process. We show that the compact index built under this model can achieve better performance in processing graph queries. Since discriminative frequent structures capture the intrinsic characteristics of the data, they are relatively stable to database updates, thus facilitating sampling-based feature extraction and incremental index maintenance. Our approach not only provides an elegant solution to the graph indexing problem, but also demonstrates how database indexing and query processing can benefit from data mining, especially frequent pattern mining. Furthermore, the concepts developed here can be generalized and applied to indexing sequences, trees, and other complicated structures as well.
15205125
Fuzzy color histogram and its use in color image retrieval
A conventional color histogram (CCH) considers neither the color similarity across different bins nor the color dissimilarity in the same bin. Therefore, it is sensitive to noisy interference such as illumination changes and quantization errors. Furthermore, CCHs large dimension or histogram bins requires large computation on histogram comparison. To address these concerns, this paper presents a new color histogram representation, called fuzzy color histogram (FCH), by considering the color similarity of each pixel's color associated to all the histogram bins through fuzzy-set membership function. A novel and fast approach for computing the membership values based on fuzzy c-means algorithm is introduced. The proposed FCH is further exploited in the application of image indexing and retrieval. Experimental results clearly show that FCH yields better retrieval results than CCH. Such computing methodology is fairly desirable for image retrieval over large image databases.
40646697
HAND: An Overlay Optimization Algorithm in Peer-to-Peer Systems
Recently, peer-to-peer (P2P) model becomes popular due to its outstanding resource sharing ability in large-scale distributed systems. However, the most popular P2P system – unstructured P2P system, suffers greatly from the mismatching between the logical overlay and physical topology. This mismatching problem causes a large volume of redundant traffic, which makes peer-to-peer system far from scalable and degrades their search efficiency dramatically. In this paper we address the mismatching problem in an unstructured P2P architecture by developing a distributed overlay optimizing algorithm – HAND (Hops Adaptive Neighbor Discovery). Through comprehensive simulations, we show that HAND significantly outperforms previous approaches, especially in large-scale P2P systems.