1503756
Using Bayesian belief networks for change impact analysis in architecture design
Research into design rationale in the past has focused on argumentation-based design deliberations. These approaches cannot be used to support change impact analysis effectively because the dependency between design elements and decisions are not well represented and cannot be quantified. Without such knowledge, designers and architects cannot easily assess how changing requirements and design decisions may affect the system. In this article, we introduce the Architecture Rationale and Element Linkage (AREL) model to represent the causal relationships between architecture design elements and decisions. We apply Bayesian Belief Networks (BBN) to AREL, to capture the probabilistic causal relationships between design elements and decisions. We employ three different BBN-based reasoning methods to analyse design change impact: predictive reasoning, diagnostic reasoning and combined reasoning. We illustrate the application of the BBN modelling and change impact analysis methods by using a partial design of a real-world cheque image processing system. To support its implementation, we have developed a practical, integrated tool set for the architects to use.
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.
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.
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.
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.
15503890
Provide privacy for mobile P2P systems
Nowadays privacy and anonymity have become an increasing requirement in wireless networks. However, current mobile peer-to-peer architectures have not taken into account anonymity, especially the mutual anonymity between two nodes. In this paper, we propose a mutual anonymity protocol, called secret-sharing-based mutual anonymity protocol (SMA), for mobile P2P networks. Our simulation results show that SMA achieves mutual anonymity in mobile P2P networks with a low cryptography processing overhead.
6059661
Mining frequent patterns without candidate generation
Mining frequent patterns in transaction databases, time-series databases, and many other kinds of databases has been studied popularly in data mining research. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist prolific patterns and/or long patterns.
In this study, we propose a novel frequent pattern tree (FP-tree) structure, which is an extended prefix-tree structure for storing compressed, crucial information about frequent patterns, and develop an efficient FP-tree-based mining method, FP-growth, for mining the complete set of frequent patterns by pattern fragment growth. Efficiency of mining is achieved with three techniques: (1) a large database is compressed into a highly condensed, much smaller data structure, which avoids costly, repeated database scans, (2) our FP-tree-based mining adopts a pattern fragment growth method to avoid the costly generation of a large number of candidate sets, and (3) a partitioning-based, divide-and-conquer method is used to decompose the mining task into a set of smaller tasks for mining confined patterns in conditional databases, which dramatically reduces the search space. Our performance study shows that the FP-growth method is efficient and scalable for mining both long and short frequent patterns, and is about an order of magnitude faster than the Apriori algorithm and also faster than some recently reported new frequent pattern mining methods.
2286606
Scene-Level Analysis for Tennis Sports Video using Weighted Linear Combination of Visual Cues
We present a scene-level analysis system that takes TV broadcasted tennis footage as input and produces a behavior analysis of the moving-players in the scene. To achieve this functionality, our algorithm relies on two modular blocks. The first one detects and tracks a number of key objects in the image domain, like moving-players and the playing-field. Afterwards, a camera-calibration algorithm is applied that uses the lines of the court as a reference and transforms image coordinates to physical positions to compute the camera parameters. The second block firstly models several important events of a tennis game, such as service and net-approach, based on four real-world visual features provided by the first block. This paper proposes a new improved model, since it weights the importance of each visual cue to different events, rather than providing a simple combination of these four visual cues as was done in previous work. Based on the new model, we can accurately determine what kind of event the current input frame belongs to. Furthermore, we detect the start time and end time of each event using a simple but efficient temporal filter. Our proposed system is capable of classifying each tennis play into three semantic categories, which are popular and familiar to most viewers. This paper presents details of the system, together with results on a number of tennis video sequences.
15256739
Performance prediction for individual recognition by gait
Existing gait recognition approaches do not give their theoretical or experimental performance predictions. Therefore, the discriminating power of gait as a feature for human recognition cannot be evaluated. In this paper, we first propose a kinematic-based approach to recognize human by gait. The proposed approach estimates 3D human walking parameters by performing a least squares fit of the 3D kinematic model to the 2D silhouette extracted from a monocular image sequence. Next, a Bayesian-based statistical analysis is performed to evaluate the discriminating power of extracted stationary gait features. Through probabilistic simulation, we not only predict the probability of correct recognition (PCR) with regard to different within-class feature variance, but also obtain the upper bound on PCR with regard to different human silhouette resolution. In addition, the maximum number of people in a database is obtained given the allowable error rate. This is extremely important for gait recognition in large databases.
18395453
Content-Based Model Template Adaptation and Real-Time System for Behavior Interpretation in Sports Video
In this paper, we present a real-time sports analysis system, which not only recognizes the semantic events, but also concludes the behavior, like player's tactics. To this end, we propose an advanced multiple-player tracking algorithm, which addresses two improvements on practical problems: (1) updating of the player template so that it remains a good model over time, and (2) adaptive scaling of the template size depending on the player motion. In this algorithm, we obtain the initial locations of players in the first frame. The tracking is performed by considering both the kinematic constraints of the player and the color distribution of appearance, thereby achieving promising results. We demonstrate the performance of the proposed system by evaluating it for double tennis matches where the player count and the resulting occlusions are challenging.