Fundamental Approaches to Software Engineering : : 26th International Conference, FASE 2023, Held As Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2023, Paris, France, April 22-27, 2023, Proceedings.

Fundamental Approaches to Software Engineering : : 26th International Conference, FASE 2023, Held As Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2023, Paris, France, April 22-27, 2023, Proceedings.

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Bibliographic Details
Superior document:Lecture Notes in Computer Science Series ; v.13991
:
Lambers, Leen.
TeilnehmendeR:
Uchitel, Sebastián.
Place / Publishing House:Cham : : Springer International Publishing AG,, 2023.
©2023.
Year of Publication:2023
Edition:1st ed.
Language:English
Series:Lecture Notes in Computer Science Series
Online Access:
Physical Description:1 online resource (344 pages)
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Table of Contents:
  • 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.
  • 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.
  • 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 &amp
  • 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.
  • 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.
  • 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.

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