Description |
1 online resource (xiv, 297 pages) : illustrations (some color) |
Series |
Lecture notes in computer science ; 11812 |
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LNCS sublibrary. SL 2, Programming and software engineering |
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Lecture notes in computer science ; 11812.
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LNCS sublibrary. SL 2, Programming and software engineering.
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Contents |
Intro; Preface; Organization; Keynotes; Intelligence Testing of Autonomous Software Systems; Testing Human-Centric Cyber-Physical Systems; Contents; Test and Artificial Intelligence; Learning a Behavior Model of Hybrid Systems Through Combining Model-Based Testing and Machine Learning; 1 Introduction; 2 Preliminaries; 2.1 Active Automata Learning; 3 Methodology; 3.1 Testing Process; 3.2 Learning a Recurrent Neural Network Behavior Model; 4 Experimental Evaluations; 4.1 Predicting Crashes with RNNs; 4.2 Evaluation of the Detected Crash Times; 5 Related Work; 6 Future Work and Conclusion |
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Generating Biased Dataset for Metamorphic Testing of Machine Learning Programs1 Introduction; 2 Machine Learning Software; 3 Dataset Diversity in Testing; 4 Generating Distorted Dataset; 5 A Case Study; 5.1 Machine Learning Classifier for MNIST; 5.2 Metamorphic Testing with Distorted Dataset; 5.3 Degrees of Distortion; 6 Related Work and Discussion; 7 Concluding Remarks; References; Test Case Generation; Combining Model Refinement and Test Generation for Conformance Testing of the IEEE PHD Protocol Using Abstract State Machines; 1 Introduction; 2 Background; 2.1 ASM and the Asmeta Framework |
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2.2 ASM Refinement2.3 IEEE 11073 PHD Communication Model; 3 Conformance Testing with Model Refinements; 4 Application to the PHD Communication Module; 4.1 Test Execution and Coverage Information; 4.2 First ASM: Ground Model; 4.3 First Refinement: PHD Configuration Management; 4.4 Second Refinement: Error Management; 4.5 Third Refinement: Protocol and Configuration Management; 5 Process Evaluation; 5.1 RQ1: How Does Refinement Influence Coverage?; 5.2 RQ2: Comparing Between Coverage Criteria; 5.3 RQ3: Faults Found; 6 Related Work; 7 Conclusion; References |
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Evaluating the Complexity of Deriving Adaptive Homing, Synchronizing and Distinguishing Sequences for Nondeterministic FSMs1 Introduction; 2 Preliminaries; 3 Deriving Homing and Distinguishing Test Cases; 4 Deriving Synchronizing Test Cases; 5 Related Work; 6 Conclusion; References; Multiple Mutation Testing for Timed Finite State Machine with Timed Guards and Timeouts; 1 Introduction; 2 Preliminaries; 2.1 Timed FSM with Timed Guards and Timeouts; 2.2 Mutants and Fault Model; 3 Revealing Combs for Characterizing Detected Mutants; 4 Distinguishing Automaton and Revealing Combs |
Summary |
This book constitutes the refereed proceedings of the 31st IFIP WG 6.1 International Conference on Testing Software and Systems, ICTSS 2019, held in Paris, France, in October 2019. The 14 regular papers and 3 short papers presented were carefully reviewed and selected from 30 submissions. This year also included an additional industrial paper. ICTSS is a series of international conferences addressing the conceptual, theoretic, and practical problems of testing software systems, including communication protocols, services, distributed platforms, middleware, embedded and cyber-physical systems, and security infrastructures. -- Provided by publisher |
Notes |
International conference proceedings |
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Includes author index |
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Online resource; title from PDF title page (SpringerLink, viewed October 15, 2019) |
Subject |
Computer software -- Testing -- Congresses
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Software engineering -- Congresses
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Computer software -- Testing
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Software engineering
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Genre/Form |
Electronic books
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proceedings (reports)
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Conference papers and proceedings
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Conference papers and proceedings.
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Actes de congrès.
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Form |
Electronic book
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Author |
Gaston, Christophe, editor.
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Kosmatov, Nikolai, editor.
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Le Gall, Pascale, editor
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ISBN |
9783030312800 |
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3030312801 |
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3030312798 |
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9783030312794 |
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9783030312817 |
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303031281X |
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