Search-Based Software Engineering: 14th International Symposium, SSBSE 2022, Singapore, November 17–18, 2022, Proceedings

Description

This book constitutes the proceedings of the 14th International Symposium on Search-Based Software Engineering, SSBSE 2022, which was held in Singapore, in November 2022. The 6 regular papers, the NIER and RENE tracks as well as the Challenge Track that were included in this volume were carefully reviewed and selected from 15 submissions. The papers deal with novel ideas and applications of search-based software engineering, focusing on engineering challenges and the application of automated approaches and optimization techniques from AI and machine learning research. Preface Preface Organization Keynotes Applications of Search-based Software Testing to Trustworthy Artificial Intelligence Genetic Improvement of Software Tutorial Methodology and Guidelines for Evaluating Multi-Objective Search-Based Software Engineering Contents Research Papers Search-Based Test Suite Generation for Rust 1 Introduction 2 Background 2.1 The RUST Programming Language 2.2 Test Generation for Rust 2.3 Search-Based Unit Test Generation 3 Search-Based Unit Test Generation for Rust 3.1 Encoding 3.2 Implementation 4 Evaluation 4.1 Experimental Setup 4.2 Results 5 Conclusions References An Empirical Comparison of EvoSuite and DSpot for Improving Developer-Written Test Suites with Respect to Mutation Score 1 Introduction 2 Background 3 Modifications Made to EvoSuite—EvoSuiteAmp 4 Empirical Study 4.1 Experimental Procedure 4.2 Threats to Validity 5 Results 5.1 Discussion 6 Related Work 7 Conclusions and Future Work References Efficient Fairness Testing Through Hash-Based Sampling 1 Introduction 2 Background 2.1 Individual Fairness Testing 2.2 Verification Based Testing (Vbt) 2.3 Hash-Based Sampling 3 Proposed Method 3.1 Basic Method (Basic Vbt-X) 3.2 Enhancement (Vbt-X) 4 Evaluation 4.1 Experimental Setup 4.2 Results 5 Related Work 6 Validity Threats 7 Conclusion and Future Work References Improving Search-Based Android Test Generation Using Surrogate Models 1 Introduction 2 Background 2.1 Automated Android Testing 2.2 Surrogate Models 2.3 Android GUI Models 3 Android Testing with Surrogate Models 3.1 Search-Based Android Testing: MATE 3.2 Surrogate Model for Android GUIs 3.3 Test Execution with a Surrogate Model 4 Evaluation 4.1 Experimental Setup 4.2 Experiments 4.3 RQ1: State Equivalence Levels 4.4 RQ2: Effects on App Restarts 4.5 RQ3: Effects on Tests and Coverage 5 Related Work 5.1 State Equivalence 5.2 Surrogate Models in Automated Testing 6 Conclusions References Guess What: Test Case Generation for Javascript with Unsupervised Probabilistic Type Inference 1 Introduction 2 Background and Related Work 3 Approach 3.1 Phase 1: Static Analysis 3.2 Phase 2: Unsupervised Static Type Inference 3.3 Phase 3: Test Case Generation 4 Empirical Study 5 Results 6 Threats to Validity 7 Conclusion and Future Work References EvoAttack: An Evolutionary Search-Based Adversarial Attack for Object Detection Models 1 Introduction 2 Background 2.1 Adversarial Examples 2.2 Adversarial Examples for Object Detection Algorithms 2.3 Related Work 3 Methodology 3.1 Object Detection Benchmark Datasets 3.2 Evolutionary Search-Based Approach 3.3 Adaptive Mutation Scheme 4 Empirical Studies 4.1 Experimental Setup for Evolutionary Search-Based Approaches 4.2 E1: Demonstration of the Adaptive Mutation Operator 4.3 E2: Demonstration that EvoAttack is Model Agnostic 4.4 E3: Demonstration that EvoAttack is Data Agnostic 4.5 Threats to Validity 5 Conclusion References NIER and RENE Tracks Applying Combinatorial Testing to Verification-Based Fairness Testing 1 Introduction 2 Preliminary 2.1 Verification Based Testing 2.2 Combinatorial t-Way Testing (CT) 3 Proposed Approach: VBT-CT 4 Experiments 5 Related Work 6 Discussion and Future Work References Challenge Track Multi-objective Genetic Improvement: A Case Study with EvoSuite 1 Introduction 2 Background 3 Approach 4 Methodology 5 Results and Discussion 6 Conclusion References Author Index