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Author

Chun Cao

Bio: Chun Cao is an academic researcher from Nanjing University. The author has contributed to research in topics: Android (operating system) & Context (language use). The author has an hindex of 13, co-authored 71 publications receiving 598 citations.


Papers
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Proceedings ArticleDOI
25 May 2019
TL;DR: On 15 large, widely-used apps from the Google Play Store, APE outperforms the state-of-the-art Android GUI testing tools in terms of both testing coverage and the number of detected unique crashes.
Abstract: This paper introduces a new, fully automated model-based approach for effective testing of Android apps. Different from existing model-based approaches that guide testing with a static GUI model (i.e., the model does not evolve its abstraction during testing, and is thus often imprecise), our approach dynamically optimizes the model by leveraging the runtime information during testing. This capability of model evolution significantly improves model precision, and thus dramatically enhances the testing effectiveness compared to existing approaches, which our evaluation confirms. We have realized our technique in a practical tool, Ape. On 15 large, widely-used apps from the Google Play Store, Ape outperforms the state-of-the-art Android GUI testing tools in terms of both testing coverage and the number of detected unique crashes. To further demonstrate Ape's effectiveness and usability, we conduct another evaluation of Ape on 1,316 popular apps, where it found 537 unique crashes. Out of the 38 reported crashes, 13 have been fixed and 5 have been confirmed.

93 citations

Proceedings ArticleDOI
27 May 2019
TL;DR: The preliminary exploration shows that adversarial examples are pervasively distributed in the finely divided space defined by such coverage criteria, while available natural samples are very sparse, and as a consequence, previously reported fault-detection "capabilities" conjectured from high coverage testing are more likely due to the adversary-oriented search but not the real "high" coverage.
Abstract: There is a dramatically increasing interest in the quality assurance for DNN-based systems in the software engineering community. An emerging hot topic in this direction is structural coverage criteria for testing neural networks, which are inspired by coverage metrics used in conventional software testing. In this short paper, we argue that these criteria could be misleading because of the fundamental differences between neural networks and human written programs. Our preliminary exploration shows that (1) adversarial examples are pervasively distributed in the finely divided space defined by such coverage criteria, while available natural samples are very sparse, and as a consequence, (2) previously reported fault-detection "capabilities" conjectured from high coverage testing are more likely due to the adversary-oriented search but not the real "high" coverage.

85 citations

Proceedings ArticleDOI
Zenan Li1, Xiaoxing Ma1, Chang Xu1, Chun Cao1, Jingwei Xu1, Jian Lu1 
12 Aug 2019
TL;DR: An efficient DNN testing method based on the conditioning on the representation learned by the DNN model under testing is proposed, which requires only about a half of labeled inputs to achieve the same level of precision.
Abstract: With the increasing adoption of Deep Neural Network (DNN) models as integral parts of software systems, efficient operational testing of DNNs is much in demand to ensure these models' actual performance in field conditions. A challenge is that the testing often needs to produce precise results with a very limited budget for labeling data collected in field. Viewing software testing as a practice of reliability estimation through statistical sampling, we re-interpret the idea behind conventional structural coverages as conditioning for variance reduction. With this insight we propose an efficient DNN testing method based on the conditioning on the representation learned by the DNN model under testing. The representation is defined by the probability distribution of the output of neurons in the last hidden layer of the model. To sample from this high dimensional distribution in which the operational data are sparsely distributed, we design an algorithm leveraging cross entropy minimization. Experiments with various DNN models and datasets were conducted to evaluate the general efficiency of the approach. The results show that, compared with simple random sampling, this approach requires only about a half of labeled inputs to achieve the same level of precision.

68 citations

Journal ArticleDOI
TL;DR: A novel approach, called Adam, to assist identifying defects in the context-aware adaptation, that can effectively detect errors, identify their responsible defects in applications, and give useful hints on how these defects can be fixed.

49 citations

Journal ArticleDOI
Jian Lu1, Xiaoxing Ma1, Xianping Tao1, Chun Cao1, Yu Huang1, Ping Yu1 
TL;DR: A software-structuring model is proposed for environment-driven Internetware applications, providing an initial framework for the construction of context-aware and self-adaptive software application systems in the open network environment.
Abstract: Internetware is envisioned as a general software paradigm for the application style of resources integration and sharing in the open, dynamic and uncertain platforms such as the Internet. Continuing the agent-based Internetware model presented in a previous paper, in this paper, after an analysis of the behavioral patterns and the technical challenges of environment-driven applications, a software-structuring model is proposed for environment-driven Internetware applications. A series of explorations on the enabling techniques for the model, especially the modeling, management and utilization of context information are presented. Several prototypical systems have also been built to prove the concepts and evaluate the techniques. These research efforts make a further step toward the Internetware paradigm by providing an initial framework for the construction of context-aware and self-adaptive software application systems in the open network environment.

46 citations


Cited by
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Christopher M. Bishop1
01 Jan 2006
TL;DR: Probability distributions of linear models for regression and classification are given in this article, along with a discussion of combining models and combining models in the context of machine learning and classification.
Abstract: Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

10,141 citations

01 Jan 2007
TL;DR: A translation apparatus is provided which comprises an inputting section for inputting a source document in a natural language and a layout analyzing section for analyzing layout information.
Abstract: A translation apparatus is provided which comprises: an inputting section for inputting a source document in a natural language; a layout analyzing section for analyzing layout information including cascade information, itemization information, numbered itemization information, labeled itemization information and separator line information in the source document inputted by the inputting section and specifying a translation range on the basis of the layout information; a translation processing section for translating a source document text in the specified translation range into a second language; and an outputting section for outputting a translated text provided by the translation processing section.

740 citations

Journal Article
TL;DR: In this paper, the authors present algorithms for the automatic synthesis of real-time controllers by finding a winning strategy for certain games defined by the timed-automata of Alur and Dill.
Abstract: This paper presents algorithms for the automatic synthesis of real-time controllers by finding a winning strategy for certain games defined by the timed-automata of Alur and Dill. In such games, the outcome depends on the players' actions as well as on their timing. We believe that these results will pave the way for the application of program synthesis techniques to the construction of real-time embedded systems from their specifications.

524 citations