29205217
Improving the Reliability of Object-Oriented Software through Object-Level Behavioral Simulation
In this paper we propose an Object-level Behavior Simulation Model (OBSM) that simulates the behavior of each object according to the message pattern exhibited by behavioral design pattern to verify it for its correctness. The model evaluates the existing reliability of the object-oriented software and allows developer to improve it during early phases of the development.
18528442
Better Reliability Assessment and Prediction through Data Clustering
This paper presents a new approach to software reliability modeling by grouping data into clusters of homogeneous failure intensities. This series of data clusters associated with different time segments can be directly used as a piecewise linear model for reliability assessment and problem identification, which can produce meaningful results early in the testing process. The dual model fits traditional software reliability growth models (SRGMs) to these grouped data to provide long-term reliability assessments and predictions. These models were evaluated in the testing of two large software systems from IBM. Compared with existing SRGMs fitted to raw data, our models are generally more stable over time and produce more consistent and accurate reliability assessments and predictions.
35577154
Tool support for software measurement, analysis and improvement
This paper presents our strategy, implementation, and experience with tool support for software measurement, analysis, and quality improvement in a commercial software development environment. The activities that need to be supported include: 1) gathering software product and process measurements, 2) analyzing measurement data, and 3) using the results to assess and improve software quality. We employed existing internal tools, commercial off-the-shelf tools, and new tools that we developed to gather and analyze data, and presented results. These tools were tailored to fit the application environments and were integrated through common rules, multiple purpose tools, and utility programs. This approach has been used successfully in supporting software measurement and quality improvement for several large commercial software products developed in the IBM Software Solutions Toronto Laboratory.
10468208
Measurement and defect modeling for a legacy software system
This paper analyzes the quality of a large-scale legacy software system using selected metrics. Quality measurements include defect information collected during product development and in-field operation. Other software metrics include measurements on various product and process attributes, including design, size, change, and complexity. Preliminary analyses revealed the high degree of skew in our data and a weak correlation between defects and software metrics. Tree-based models were then used to uncover relationships between defects and software metrics, and to identify high-defect modules together with their associated measurement characteristics. As results presented in tree forms are natural to the decision process and are easy to understand, tree-based modeling is shown to be suitable for change solicitation and useful in guiding remedial actions for quality improvement.
5796465
A hierarchical strategy for testing Web-based applications and ensuring their reliability
After examining the specific problems of testing and quality assurance for Web-based applications, we propose a strategy by integrating existing testing techniques and reliability analyses in a hierarchical framework. This strategy combines various usage models for statistical testing to perform high level testing and to guide selective testing of critical and frequently used subparts or components using traditional coverage-based structural testing. Reliability analysis and risk identification form an integral part of this strategy to help assure and improve the overall reliability for Web-based applications. Some preliminary results are included to demonstrate the general viability and effectiveness of our approach.
14909770
Early measurement and improvement of software quality
The paper combines relevant research in software reliability engineering and software measurement to develop an integrated approach for the early measurement and improvement of software quality. Recent research in these areas is extended 1) to select appropriate software measures based on. A formal model, 2) to construct tree-based reliability models for early problem identification and quality improvement, and 3) to develop tools to support industrial applications. Initial results applying this approach to several IBM products demonstrated the applicability and effectiveness of this approach.
37244
Data Hiding in Film Grain
This paper presents a data hiding technique based on a new compression enhancement called Film Grain Technology. Film grain is a mid-frequency noise-like pattern naturally appearing in imagery captured on film. The Film Grain Technology is a method for modeling and removing the film grain, thus enhancing the compression efficiency, and then using the model parameters to create synthetic film grain at the decoder. We propose slight modifications to the decoder that enable the synthetic film grain to represent metadata available at the decoder. We examine a number of implementation approaches and report results of fidelity and robustness experiments.
4621823
On the Testable Implications of Causal Models with Hidden Variables
The validity of a causal model can be tested only if the model imposes constraints on the probability distribution that governs the generated data. In the presence of unmeasured variables, causal models may impose two types of constraints: conditional independencies, as read through the d-separation criterion, and functional constraints, for which no general criterion is available. This paper offers a systematic way of identifying functional constraints and, thus, facilitates the task of testing causal models as well as inferring such models from data.
46662719
A minutiae matching algorithm in fingerprint verification
Fingerprint matching is one of the most important problems in AFIS. In general, we use minutiae such as ridge endings and ridge bifurcation to represent a fingerprint and do fingerprint matching through minutiae matching. We propose a minutiae matching algorithm which modified Jain et al.'s algorithm (1997). Our algorithm can better distinguish two images from different fingers and is more robust to nonlinear deformation. Experiments done on a set of fingerprint images captured with an inkless scanner shows that our algorithm is fast and has high accuracy.
8746493
Fingerprint Enhancement Using Oriented Diffusion Filter
Fingerprint enhancement is a critical step in a fingerprint identification system. Recently, some anisotropic nonlinear diffusion filter is applied to the fingerprint preprocessed. Impressive results are main reason for using nonlinear diffusion filtering in image processing. Poor efficiency, especially the computational load, is the main reason for not using nonlinear diffusion filtering. In order to improve the efficiency, a novel piecewise nonlinear diffusion for fingerprint enhancement is presented. It shows anisotropic diffusion equation using diffusion tensor which continuously depends on the gradient is not necessary to smooth the fingerprint. We simplify the anisotropic nonlinear-diffusion in order to satisfy a real-time fingerprint recognition system. According to the local character of the fingerprint, the diffusion filter is steered by the orientation of ridge. Experimental results illustrate that our enhancement algorithm can satisfy the requirement of an AFIS.
393156
A general identification condition for causal effects
This paper concerns the assessment of the effects of actions or policy interventions from a combination of: (i) nonexperimental data, and (ii) substantive assumptions. The assumptions are encoded in the form of a directed acyclic graph, also called "causal graph", in which some variables are presumed to be unobserved. The paper establishes a necessary and sufficient criterion for the identifiability of the causal effects of a singleton variable on all other variables in the model, and a powerful sufficient criterion for the effects of a singleton variable on any set of variables.