Multi-focus image fusion is a technique that combines multiple out-of-focus images to enhance the overall image quality. It has gained significant attention in recent years, thanks to the advancements in deep learning...
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Exploratory data analysis (EDA) is usually human-in-the-loop and time tedious since identifying insights that show interesting characteristics and trends in data is laborious. Insight discovery helps users gain struct...
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ISBN:
(数字)9798331529024
ISBN:
(纸本)9798331529031
Exploratory data analysis (EDA) is usually human-in-the-loop and time tedious since identifying insights that show interesting characteristics and trends in data is laborious. Insight discovery helps users gain structured knowledge when understanding the dataset by categorizing interesting characteristics and trends into commonnesses and exceptions. However, existing insight discovery methods cannot interact with users when discovering insights. More importantly, the efficiency of insight discovery for these methods is low. In this paper, we propose a framework that supports and accelerates interactive insight discovery. We first divide the dataset into multiple subsets, and precompute the pattern snippets that include the distribution characteristics of subsets. Considering efficiency, we only pre-compute for subsets that cannot be further split. Then we design a novel cube structure, called InsightCube, to store precomputed pattern snippets. In order to accelerate insight discovery, we reuse the precomputed pattern snippets stored in InsightCube to infer the pattern of subsets that cannot be split. Furthermore, during insight discovery, we propose pruning strategies to accelerate the pattern inference for subsets that can be split. Experimental results on real-world datasets show that InsightCube improves the insight discovery efficiency by up to $2.5 \times$ compared to the state-of-the-art insight discovery method.
GUI-based software is often developed a complicated test script with existing traditional automation softwaretesting tools. The software automated test development technology consequently carried out some study of ex...
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This paper introduces strategies to detect software bugs in earlier life cycle stage in order to improve test efficiency. Static analysis tool is one of the effective methods to reveal software bugs during software de...
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This paper introduces strategies to detect software bugs in earlier life cycle stage in order to improve test efficiency. Static analysis tool is one of the effective methods to reveal software bugs during software development. Three popular static analysis tools are introduced, two of which, PolySpace and Splint, are compared with each other by analyzing a set of test cases generatedd by the authors. PolySpace can reveal 60% bugs with 100% R/W ratio (ratio of real bugs and total warnings), while Splint reveal 73.3% bugs with 44% R/W ratio. And they are good at finding different categories of bugs. Two strategies are concluded to improve test efficiency, under the guideline that static analysis tools should be used in finding different categories of bugs according to their features. The first one aims at finding bugs as many as possible, while the second concentrates to reduce the average time on bug revelation. Experimental data shows the first strategy can find 100% bugs with 60% R/W ratio, the second one find 80% bugs with 66.7% R/W ratio. Experiment results prove that these two strategies can improve the test efficiency in both fault coverage and testing time.
In recent years, microservice architectures have benefited from low coupling and high cohesion characteristics, allowing flexible on-demand deployment of complex applications and simplifying the difficulty of developi...
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With the rapid development of the network technology, intelligent device and mobile applications has been the developed fastly. The mobile device will increasingly widely used even replace the traditional computer, th...
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This paper studies the software scenario testing, which is commonly used in black-box testing at present. In the paper, the workflow model based on task-driven, which is very common in scenario testing, is analyzed. A...
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This paper studies the software scenario testing, which is commonly used in black-box testing at present. In the paper, the workflow model based on task-driven, which is very common in scenario testing, is analyzed. According to test adequacy criteria in scenario testing, the model is designed to correspond test cases in the light of logic block(LB). The final test cases that conform to the test adequacy criteria can be obtained through test case combination and test case reduction. In the last part of the paper, example of actual workflow is to design the efficient test case. Therefore the method is proved to be effective.
Before autonomous driving vehicles are commercialized, they need to undergo a series of rigorous tests. This paper first proposes the general process of autonomous driving system testing, and then summarizes the resea...
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In recent years, microservice architecture (MSA) has become popular. Emerging from the agile community, MSA implies a number of small, independently deployable microservices. They are characterized by low coupling, hi...
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As a graphical and mathematical modeling tool, CPN (Colored Petri Net) is often used to describe the transition of states for an information system. The advantage of CPN model is that the model can be simulated dynami...
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