3552947
An initial study of a lightweight process for change identification and regression test selection when source code is not available
Various regression test selection techniques have been developed and have shown to improve testing cost effectiveness via improving efficiency. The majority of these test selection techniques rely on access to source code for change identification. However, when new releases of COTS components are made available for integration and testing, source code is often not available to guide in regression test selection. In this paper we describe a lightweight integrated-black-box approach for component change identification (I-BACCI) process for selection of regression tests for user/glue code that uses COTS components. I-BACCI is applicable when component licensing agreements do not preclude binary code analysis. A case study of the process was conducted on an ABB product that uses a medium-scale internal ABB software component. Six releases of the component were examined to evaluate the efficacy of the proposed process. The result of the case study indicates that this process can reduce the required regression tests by 40% on average
17173349
A lightweight process for change identification and regression test selection in using COTS components
Various regression test selection techniques have been developed and have shown fault detection effectiveness. The majority of these test selection techniques rely on access to source code for change identification. However, when new releases of COTS components are made available for integration and testing, source code is often not available. In this paper, we present a lightweight integrated-black-box approach for component change identification (I-BACCI) process for selection of regression tests for user/glue code that uses COTS components. I-BACCI is applicable when component licensing agreements do not preclude analysis of the binary files. A case study of the process was conducted on an ABB product that uses a medium-scale internal ABB software component. Five releases of the component were examined to evaluate the efficacy of the proposed process. The result of the case study indicates this process can reduce the required number of regression tests by 54% on average.
9909178
On the value of static analysis for fault detection in software
No single software fault-detection technique is capable of addressing all fault-detection concerns. Similarly to software reviews and testing, static analysis tools (or automated static analysis) can be used to remove defects prior to release of a software product. To determine to what extent automated static analysis can help in the economic production of a high-quality product, we have analyzed static analysis faults and test and customer-reported failures for three large-scale industrial software systems developed at Nortel Networks. The data indicate that automated static analysis is an affordable means of software fault detection. Using the orthogonal defect classification scheme, we found that automated static analysis is effective at identifying assignment and checking faults, allowing the later software production phases to focus on more complex, functional, and algorithmic faults. A majority of the defects found by automated static analysis appear to be produced by a few key types of programmer errors and some of these types have the potential to cause security vulnerabilities. Statistical analysis results indicate the number of automated static analysis faults can be effective for identifying problem modules. Our results indicate static analysis tools are complementary to other fault-detection techniques for the economic production of a high-quality software product.
18528231
In regression testing selection when source code is not available
13903434
GERT: an empirical reliability estimation and testing feedback tool
Software testing is an integral part of the software development process. Some software developers, particularly those who use the Extreme Programming test-driven development practice, continuously write automated tests to verify their code. We present a tool to complement the feedback loops created by continuous testing. The tool combines static source code metrics with dynamic test coverage for use throughout the development phase to predict a reliability estimate based on a linear combination of these values. Implemented as an open source plug-in to the Eclipse IDE, the tool facilitates the rapid transition between unit test case completions and testing feedback. The color-coded results highlight inadequate testing efforts as well as weaknesses in overall program structure. To illustrate the tool's efficacy, we share the results of its use on university software engineering course projects.
40804986
Bounds on the Moving Control Points of Hybrid Curves
Abstract Hybrid curves provide an attractive method for approximating rational Bezier curves by polynomial Bezier curves. In this paper, several methods are provided to estimate the error bounds for the approximation to the moving control point of the hybrid curves. When the given rational Bezier curves satisfies the convergent conditions for moving control point of the hybrid curve, by these methods we can choose a hybrid curve with a certain degree such that the distance between the moving control point and a special point is less than a given error bound ϵ. So the polynomial Bezier curves to approximate the rational Bezier curve can be obtained by replacing the moving control point with the special point.
1720352
T-splines and T-NURCCs
This paper presents a generalization of non-uniform B-spline surfaces called T-splines. T-spline control grids permit T-junctions, so lines of control points need not traverse the entire control grid. T-splines support many valuable operations within a consistent framework, such as local refinement, and the merging of several B-spline surfaces that have different knot vectors into a single gap-free model. The paper focuses on T-splines of degree three, which are C2 (in the absence of multiple knots). T-NURCCs (Non-Uniform Rational Catmull-Clark Surfaces with T-junctions) are a superset of both T-splines and Catmull-Clark surfaces. Thus, a modeling program for T-NURCCs can handle any NURBS or Catmull-Clark model as special cases. T-NURCCs enable true local refinement of a Catmull-Clark-type control grid: individual control points can be inserted only where they are needed to provide additional control, or to create a smoother tessellation, and such insertions do not alter the limit surface. T-NURCCs use stationary refinement rules and are C2 except at extraordinary points and features.
21588344
The mu-basis of a rational ruled surface
Abstract The mu-basis of a planar rational curve is a polynomial ideal basis comprised of two polynomials that greatly facilitates computing the implicit equation of the curve. This paper defines a mu-basis for a rational ruled surface, and presents a simple algorithm for computing the mu-basis. The mu-basis consists of two polynomials p(x,y,z,s) and q(x,y,z,s) that are linear in x,y,z and degree μ and m−μ in s respectively, where m is the degree of the implicit equation. The implicit equation of the surface is then obtained by merely taking the resultant of p and q with respect to s . This implicitization algorithm is faster and/or more robust than previous methods.
35608544
Target curvature driven fairing algorithm for planar cubic B-spline curves
This paper presents a new algorithm for fairing planar cubic B-spline curves. Target curvature plots prescribed by designers according to design intent are used to identify bad points and bad curve segments. The corresponding control points are then modified using local constrained optimization. The objective function is a weighed combination of two components, which are associated with the fairness in the sense of energy minimization and the coherence to the original design, respectively. Hence, designers have more control over the fairing process by using appropriate weights for the two components. Several numerical examples are provided to demonstrate the effectiveness of the algorithm.
35877804
Bio-native Shape Modeling and Virtual Reality for Bio Education
Bio structural and functional research and education is playing an increasingly important role in today's post-genome era. Protein geometry and shape modeling is thus a fundamental issue for protein visualization. The number of protein structures determined by X-ray crystallography or Nuclear Magnetic Resonance (NMR) is expanding in an exponential rate. Recent technology advancement has also made it possible for the determination of larger and more complicated proteins structure. A generic and automatic shape modeling for protein structures is therefore highly desired for effective and efficient protein visualization. We propose a bio-native geometric modeling technique in this paper for constructing protein secondary structure. Our emphasis is placed on the shape compatibility with the protein conformation property. Efforts are also made to handle smooth sweeping for complex protein structures. We describe as well a Virtual Reality (VR) application for protein structure education based on our Bio-native shape modeling and visualization techniques developed in this work.