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In this paper we assess and evaluate the quality of t-way combinatorial test-suites using three different test-suite quality assessment methods. As t-way combinatorial test-suites reduce the input space of a program under test, we investigate how an increasing t affects the quality of the test-suite. There are some limitations of existing test-suite quality assessment methods e.g. the number of mutants...
In the last years, the phenomenon of electronic products passing all tests by the manufacturer but failing in the field (No Fault Found, or NFF) attracted the attention of industries and researchers. Delay faults are supposed to be among the contributors to this phenomenon. Hence, companies are increasingly adopting functional test as a final step, which is expected to detect this kind of defects...
We present two novel approaches for automated testing of models written in Alloy – a well-known declarative, first-order language that is supported by a fully automatic SAT-based analysis engine. The first approach introduces automated test generation for Alloy and is embodied by three techniques that create test suites in the traditional spirit of black-box, white-box, and mutation-based testing...
Software testing is the most widely used approach for assessing and improving software quality, but it is inherently incomplete and may not be representative of how the software is used in the field. This paper addresses the questions of to what extent tests represent how real users use software, and how to measure behavioral differences between test and field executions. We study four real-world...
Testing using architectural design models is intended to determine if the realized system meets its specification, and works as a whole in terms of computational components and their interactions. The growing complexity of embedded systems requires new techniques that are able to support testing of extra-functional requirements, like energy usage of components and systems, which is very necessary...
We present a framework for comprehensive model-based systematic design and staged verification of Human-in-the-Loop Cyber-Physical Systems (HiLCPS) to handle their inherent complexity. HiLCPS are systems where humans are in the middle of the feedback loop between their cyber and the physical components. HiLCPS designers require modern tools and simpler model-based approaches for design and verification...
A variety of fault models have been defined to capture the behaviors of commonly occurring defects and ensure a high quality of testing. When several fault models are used for test generation, it is advantageous if the existence of an undetectable fault in one model does not imply that a fault in the same component but from a different model is also undetectable. This allows a test set to cover the...
One promising way to improve the accuracy of fault localization based on statistical debugging is to increase diversity among test cases in the underlying test suite. In many practical situations, adding test cases is not a cost-free option because test oracles are developed manually or running test cases is expensive. Hence, we require to have test suites that are both diverse and small to improve...
Embedded software, such as railway, aviation, and medical devices, must provide users with safety and reliability software called safety-critical software. It is required to thoroughly analysis requirements, and to provide users with software with high quality attributes of reliability and safety as a result of clear requirement analysis. To analysis the requirements, we mainly use the white box view...
Testing becomes difficult when we cannot easily determine whether the system delivers the correct result or not. To address this issue, we have developed a framework for automated testing of NASA's DAT system using metamorphic testing principles combined with model based testing. Based on the results from using the framework to test DAT we have determined that this is a cost beneficial solution allowing...
The effective integrated approach for modeling of functional devices (FD), airborne computers and embedded systems on the devices design stage is proposed. This approach can be used at the manufacturers, which have a full production cycle, especially in the following industrial systems: instruments for onboard information processing and control, space systems, aviation systems and others. In the traditional...
Fault diagnosis methods for specified fault models might deduce wrong faults as suspicious candidate faults (misprediction). The methods might not be able to also deduce suspicious candidate faults (non-prediction). In this paper, a fault diagnosis method for a single universal logical fault model in scan testing is proposed. In the fault diagnosis method, a diagnostic fault simulation for a single...
A practical testing level 1 of the road freight operator in Thailand's logistics professional qualification system has three stations: receiving, placement, and delivery. The number of examinees and the capability of officers in each station affect the complete number of examinees in limited time and average cost per examinee. In this article, the Markov chains model is used to describe the testing...
Latent Dirichlet Allocation (LDA), is heavily cited in the machine learning literature, but its feasibility and effectiveness in information retrieval is mostly unknown. Learning to rank is useful for document retrieval, it uses feature vector to rank, but there is no feature about document topic. Our paper combines LDA and learning to rank, adds a topic feature into the feature vector of learning...
A detection of moving object using Zernike moments comes up in this paper. First of all, the Zernike moments are introduced briefly. Then the algorithm of moving object detection using the Zernike moments is elaborated, after that it presents the performance evaluation. After the testing results, we get that the Zernike moments could reduce more noise compared with the Gaussian Mixture Model [1].
Object detection is a challenging task in the field of pattern recognition. The objective of object detection is to locate the target objects in the testing images. In this paper, we use SVM trained active basis model as a sparse coding model for representing objects. The sparse coding model represents each image as the linear superposition of a small number of Gabor wavelets selected from an over-complete...
Security is often treated as secondary or a non- functional feature of software which influences the approach of vendors and developers when describing their products often in terms of what it can do (Use Cases) or offer customers. However, tides are beginning to change as more experienced customers are beginning to demand for more secure and reliable software giving priority to confidentiality, integrity...
Big data and cloud computing are the two top IT initiatives that are in the mind for industries across the globe. Both innovations keep on evolving. As a delivery model for IT services, cloud computing has the potential to enhance agility and productivity while enabling greater efficiencies and reducing costs. As a result a number of enterprises are building efficient and agile cloud environments,...
This work presents results of effectiveness analyses of using deep neural networks models for syntactic parsing of SynTagRus dataset. A set of modular neural network topologies based on composition of Stack long short-term memory layers, multilayer perceptron has been compared with widely used algorithms of classification on base of Gradient boosting trees and Support vector machine. Results allow...
Information flow control (IFC) is useful in preventing information leakage during software execution. Our survey reveals that no IFC model is applied on the entire software development process. Applying an IFC model on the entire software development process offers the following features: (1) viewpoints of all stakeholders (i.e., customers and analysts) can be included and (2) the IFC model helps...
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