37559798
Measurement and continuous improvement of software reliability throughout software life-cycle
Abstract Software reliability is one of the most important aspects of software quality. However, most of the existing techniques focus on the system testing and other late stages of development life-cycle. Therefore, they are not effective for early problem identification and reliability improvement. This paper describes our recent work in establishing predictive linkage between software reliability and other entities that we can measure and control early in the development cycle, and using such predictive relations to drive continuous reliability improvement.
18396642
Defect handling in medium and large open source projects
Open source projects have resulted in numerous high-quality, widely used products. Understanding the defect-handling strategies such projects employ can help us use the publicly accessible defect data from these projects to provide valuable quality-improvement feedback and to better understand the defect characteristics for a wider variety of software products. We conducted a survey to understand defect handling in selected open source projects and compared the particular approaches taken in different projects. We focused on defect handling instead of the broader quality assurance activities other researchers have previously reported. Our results provided quantitative evidence about the current practice of defect handling in an important subset of open source projects.
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.
16987100
Measuring Prime Program Complexity
Abstract This paper uses the prime program decomposition of a program as the basis for a measure that closely correlates with our intuitive notion of program complexity. This measure is based upon the information theory ideas of randomness and entropy such that results about structured programming, data abstractions, and other programming paradigms can be stated in quantitative terms, and empirical means can be used to validate the assumptions used to develop the model. As a graph-based model, it can be applied to several graphical examples as extensions not otherwise available to source-code based models. This paper introduces the measure, derives several properties for it, and gives some simple examples to demonstrate that the measure is a plausible approximation of our notions concerning structured programming.
8007887
An application of decision theory for the evaluation of software prototypes
Abstract There is a need to quantify management decision making in software development. To this end, this article presents an application of concepts from economic decision theory to an aspect of this problem currently under study by many in the software engineering community—how to prototype a design and evaluate the effectiveness of this prototype. The role of prototyping as an experimental tool is analyzed and techniques for defining what to prototype and when it is cost effective are introduced. We demonstrate some of these decision theory techniques to define a model that management can use to select solutions from a set of alternative designs.
41698948
An Integrated Approach to Test Tracking and Analysis
This paper presents an integrated approach to test tracking and analysis in a commercial software development environment. Our approach includes measurement gathering, graphical test activity and defect tracking, overall quality assessment using various reliability growth models, and identification of problematic areas and risk management using tree-based modeling. Various existing software tools have been adapted and integrated to support our analysis and modeling. This approach has been used in the testing of several large commercial software products and demonstrated to be effective and efficient under our environment.
31563264
Fingerprint Minutiae Matching with Orientation and Ridge
An important step in automatic fingerprint identification system (AFIS) is fingerprint matching. The task of fingerprint matching is to verify whether two fingerprints are coming from same finger. In this paper we detail and discuss the fingerprint matching algorithm. A minutia matching algorithm is proposed which modified the algorithm presented by Jain et al. In this algorithm, in order to reduce the effect of noise and false minutiae, block orientation and ridge information are introduced into the minutiae-based matching algorithm in a simple but reliable way. Ridge information which is some sampled points in the ridge are used to align two fingerprints, in order to avoid misalign two fingerprints, we use block orientation to correct the ridge alignment. Experiments on the database FVC2002 show the performance.
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.
34795143
Automatic Fingerprint Identification Using Cluster Algorithm
2612233
Fingerprint enhancement with dyadic scale-space
Fingerprint enhancement is a critical step in automatic fingerprint verification system. Most of the existing enhancement uses a set of contextual filters to enhance fingerprint. The main drawback of these methods is these contextual filters based on the local information of the fingerprint, such as ridge width, orientation, curvature etc. This information is unreliable in the areas corrupted by the noise. This paper introduces the scale space theory in the computer vision to enhance the fingerprint. In the enhancement process, decompose fingerprint into a series of images and organize the images by courser to finer scheme. Thus a globe and integrate interpretation is available and it enables us to get rid of the influence of noise to the largest extent. Experiments show our algorithm is fast and improve the performance of fingerprint verification system.
622959
Markov Chain Monte Carlo Super-Resolution Image Reconstruction with Simultaneous Adaptation of the Prior Image Model
In our recent work, the Markov chain Monte Carlo (MCMC) technique has been successfully exploited and shown as an effective approach to perform super-resolution image reconstruction. However, one major challenge lies at the selection of the hyperparameter of the prior image model, which affects the degree of regularity imposed by the prior image model, and consequently, the quality of the estimated high-resolution image. To tackle this challenge, in this paper, we propose a novel approach to automatically adapt the model’s hyperparameter during the MCMC process, rather than the exhaustive, off-line search. Experimental results presented show that the proposed hyperparameter adaptation method yields extremely close performance to that of the optimal prior image model case.