UID:
almahu_9949516202602882
Umfang:
1 online resource (344 pages)
Ausgabe:
1st ed.
ISBN:
9783031308260
Serie:
Lecture Notes in Computer Science Series ; v.13991
Anmerkung:
Intro -- ETAPS Foreword -- Preface -- Organization -- Brains on Code: Towards a Neuroscientific Foundation of Program Comprehension (Abstract of an Invited Talk) -- Contents -- Regular Contributions -- ACoRe: Automated Goal-Conflict Resolution -- 1 Introduction -- 2 Linear-Time Temporal Logic -- 2.1 Language Formalism -- 2.2 Model Counting -- 3 The Goal-Conict Resolution Problem -- 4 ACoRe: Automated Goal-Conict Resolution -- 4.1 Search Space and Initial Population -- 4.2 Multi-Objectives: Consistency, Resolution and Similarities -- 4.3 Evolutionary Operators -- 4.4 Multi-Objective Optimisation Search Algorithms -- 5 Experimental Evaluation -- 5.1 Experimental Procedure -- 6 Experimental Results -- 6.1 RQ1: E ectiveness of ACoRe -- 6.2 RQ2: Comparison with the Ground-truth -- 6.3 RQ3: Comparing the Multi-objective Optimization Algorithms -- 7 Related Work -- 8 Conclusion -- References -- A Modeling Concept for Formal Verification of OS-Based Compositional Software -- Availability of Artifacts -- 1 Introduction -- 2 Background -- 2.1 Real-Time Operating System (RTOS) -- 2.2 Uppaal -- 3 Model Design -- 3.1 Naming Convention -- 3.2 The Kernel Interface -- 3.3 The Operating System -- 3.4 Simple Application Modeling -- 4 Requirements and Verification -- 4.1 Composition Requirements -- 4.2 OS Requirements -- 4.3 Verifying the Requirements -- 4.4 OS Model Verification -- 5 Analysis and Evaluation -- 5.1 Compositional Approach to Deriving the Minimal Configuration -- 5.2 Scalability: Resource Consumption for Verification -- 5.3 Sufficiency of 4-1-2-2 Configuration for our OS Model -- 6 Related Work -- 7 Conclusions and Future Work -- References -- Compositional Automata Learning of Synchronous Systems -- 1 Introduction -- 2 Preliminaries -- 2.1 L∗ algorithm -- 3 Learning Synchronous Components Compositionally -- 3.1 Query Adapter -- 3.2 L∗ extensions.
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3.3 Correctness -- 4 Experiments -- 4.1 Random Systems -- 4.2 Realistic Systems -- 5 Related Work -- 6 Conclusion -- References -- Concolic Testing of Front-end JavaScript -- 1 Introduction -- 2 Background -- 2.1 Front-end JavaScript Testing Frameworks -- 2.2 In-situ Concolic Testing of Backend JavaScript -- 3 Approach -- 3.1 Overview -- 3.2 Concolic Testing of JS Web Function within Execution Context -- 4 Implementations -- 4.1 Implementation on Puppeteer -- 4.2 Implementation on Jest with React Testing Library -- 5 Evaluations -- 5.1 Evaluation of Puppeteer Implementation on Github Projects -- 5.2 Evaluation of Jest Implementation on Metamask -- 6 Related Work -- 7 Conclusions -- Acknowledgements. -- References -- Democratizing Quality-Based Machine Learning Development through Extended Feature Models -- 1 Introduction -- 2 Related Work -- 3 Considered Quality Attributes -- 4 Motivating Scenario -- 5 MANILA Approach -- 5.1 Extended Feature Model -- 5.2 Features Selection -- 5.3 Experiment generation -- 5.4 Experiment Execution -- 6 Proof of Concept -- 7 Threats to Validity -- 8 Conclusion and Future Work -- References -- Efficient Bounded Exhaustive Input Generation from Program APIs -- 1 Introduction -- 2 A Motivating Example -- 3 Bounded Exhaustive Generation from Program APIs -- 3.1 Scope Definition -- 3.2 State Matching -- 3.3 Builders Identification Approach -- 3.4 The BEAPI Approach -- 4 Evaluation -- 4.1 RQ1: Efficiency of Bounded Exhaustive Generation from APIs -- 4.2 RQ2: Impact of BEAPI's Optimizations -- 4.3 RQ3: Analysis of Specifications using BEAPI -- 5 Related Work -- 6 Conclusions -- Acknowledgements -- References -- Feature-Guided Analysis of Neural Networks -- 1 Introduction -- 2 Extracting Feature Representations -- 3 Feature-Guided Analyses -- 4 Case Studies -- 4.1 Center-line Tracking with TaxiNet.
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4.2 Object Detection with YOLOv4-Tiny -- 4.3 Challenges and Mitigations -- 5 Related Work -- 6 Conclusion -- References -- JavaBIP meets VerCors: Towards the Safety of Concurrent Software Systems in Java -- 1 Introduction -- 2 Related Work -- 3 JavaBIP and Verification Annotations -- 4 Architecture of Verified JavaBIP -- 5 Implementation of Verified JavaBIP -- 6 VerifyThis Casino and Verified JavaBIP -- 7 Conclusions and Future Work -- References -- Model-based Player Experience Testing with Emotion Pattern Verification -- 1 Introduction -- 2 Preliminaries -- 2.1 Computational Model of Emotions -- 2.2 Model-based Testing with EFSM -- 3 PX Testing Framework -- 4 Methodology -- 4.1 Test Suite Generation -- 4.2 Test Suite Diversity -- 4.3 Emotion Patterns' Requirements and Heat-maps -- 4.4 PX Framework Implementation -- 5 Case Study -- 5.1 Experiment Configuration -- 5.2 PX Testing Evaluation -- 5.3 Mutation Testing Evaluation -- 6 Related Work -- 7 Conclusion & -- Future work -- References -- Opportunistic Monitoring of Multithreaded Programs -- 1 Introduction -- 2 Modeling the Program Execution -- 3 Opportunistic Monitoring -- 3.1 Managing Dynamic Threads and Events -- 3.2 Scopes: Properties Over Concurrent Regions -- 3.3 Semantics for Evaluating Scopes -- 3.4 Communicating Verdicts and Monitoring -- 4 Preliminary Assessment of Overhead -- 4.1 Readers-Writers -- 4.2 Other Benchmarks -- 5 Related Work -- 6 Conclusion and Perspectives -- References -- Parallel Program Analysis via Range Splitting -- 1 Introduction -- 2 Background -- 2.1 Program Syntax and Semantics -- 2.2 Path Ordering, Execution Trees, and Ranges -- 2.3 Configurable Program Analysis -- 3 Composition of Ranged Analyses -- 3.1 Ranged Analysis -- 3.2 Range Reduction as CPA -- 3.3 Handling Underspecified Test Cases -- 4 Splitting -- 5 Implementation -- 6 Evaluation.
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6.1 Evaluation Setup -- 6.2 RQ 1: Composition of Ranged Analyses for Symbolic Execution -- 6.3 RQ 2: Composition of Ranged Analyses for Other Analyses -- 7 Related Work -- 8 Conclusion -- References -- Runtime Enforcement Using Knowledge Bases -- 1 Introduction -- 2 Preliminaries -- 3 A Scenario for Knowledge Based Guiding -- 4 Knowledge Guided Transition Systems -- 5 Well-Formedness and Optimization -- 6 (Semi-)Automatically Generated Mappings -- 7 Discussion -- 8 Related Work -- 9 Conclusion -- References -- Specification and Validation of Normative Rules for Autonomous Agents -- 1 Introduction -- 2 SLEECVAL: Notation, Components, and Architecture -- 3 Evaluation -- 4 Conclusion -- Acknowledgements -- References -- Towards Log Slicing -- 1 Introduction -- 2 Motivating Example -- 3 Log Slicing -- 4 An Illustration of Log Slicing -- 4.1 A Provisional Definition of Relevance -- 4.2 Applying Log Slicing -- 4.3 Limitations and Open Issues -- 5 Related Work -- 6 Conclusion -- Acknowledgments. -- References -- Vamos: Middleware for Best-Effort Third-Party Monitoring -- 1 Introduction -- 2 Architectural Overview -- 3 Efficient Instrumentation -- 3.1 Source Buffers and Stream Processors -- 3.2 Autodrop Buffers -- 4 Event Recognition, Ordering, and Prioritization -- 4.1 Arbiter Rules -- 4.2 Buffer Groups -- 5 Implementation -- 5.1 Source Buffers and Event Sources -- 5.2 The Vamos Compiler and the TeSSLa Connector -- 6 Evaluation -- 6.1 Scalability Tests -- 6.2 Primes -- 6.3 Bank -- 6.4 Case Study: Data Race Detection -- 7 Related Work -- 8 Conclusion -- References -- Yet Another Model! A Study on Model's Similarities for Defect and Code Smells -- 1 Introduction -- 2 Background -- 2.1 Defects -- 2.2 Code Smells -- 3 Study Design -- 3.1 Research Questions -- 3.2 Data -- 3.3 Quality Attributes -- 3.4 Machine Learning -- 4 Results -- 4.1 Predictive Capacity.
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4.2 Explaining the Models -- 5 Threats to Validity -- 6 Related Work -- 7 Conclusion -- References -- Competition Contributions -- Software Testing: 5th Comparative Evaluation: Test-Comp 2023 -- 1 Introduction -- 2 Definitions, Formats, and Rules -- 3 Categories and Scoring Schema -- 4 Reproducibility -- 5 Results and Discussion -- 6 Conclusion -- References -- FuSeBMC_IA: Interval Analysis and Methods for Test Case Generation -- 1 Introduction -- 2 Interval Analysis and Methods for Test Case Generation -- 3 Strengths andWeaknesses -- 4 Tool Setup and Configuration -- 5 Software Project -- 6 Data-Availability Statement -- Acknowledgment -- References -- Correction to: Feature-Guided Analysis of Neural Networks -- Correction to: Chapter "Feature-Guided Analysis of Neural Networks" in: L. Lambers and S. Uchitel (Eds.): Fundamental Approaches to Software Engineering, LNCS 13991, https://doi.org/10.1007/978-3-031-30826-0_7 -- Author Index.
Weitere Ausg.:
Print version: Lambers, Leen Fundamental Approaches to Software Engineering Cham : Springer International Publishing AG,c2023 ISBN 9783031308253
Sprache:
Englisch
Schlagwort(e):
Electronic books.
