FSE 2024
121 papers
- "The Law Doesn't Work Like a Computer": Exploring Software Licensing Issues Faced by Legal Practitioners
- A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-Based Anomaly Detection Techniques
- A Deep Dive into Large Language Models for Automated Bug Localization and Repair
- A Miss Is as Good as A Mile: Metamorphic Testing for Deep Learning Operators
- A Quantitative and Qualitative Evaluation of LLM-Based Explainable Fault Localization
- A Transferability Study of Interpolation-Based Hardware Model Checking for Software Verification
- A Weak Supervision-Based Approach to Improve Chatbots for Code Repositories
- AI-Assisted Code Authoring at Scale: Fine-Tuning, Deploying, and Mixed Methods Evaluation
- AROMA: Automatic Reproduction of Maven Artifacts
- Abstraction-Aware Inference of Metamorphic Relations
- Active Monitoring Mechanism for Control-Based Self-Adaptive Systems
- Adapting Multi-objectivized Software Configuration Tuning
- An Analysis of the Costs and Benefits of Autocomplete in IDEs
- An Empirical Study on Code Review Activity Prediction and Its Impact in Practice
- An Empirical Study on Focal Methods in Deep-Learning-Based Approaches for Assertion Generation
- Analyzing Quantum Programs with LintQ: A Static Analysis Framework for Qiskit
- Are Human Rules Necessary? Generating Reusable APIs with CoT Reasoning and In-Context Learning
- BARO: Robust Root Cause Analysis for Microservices via Multivariate Bayesian Online Change Point Detection
- BRF: Fuzzing the eBPF Runtime
- Beyond Code Generation: An Observational Study of ChatGPT Usage in Software Engineering Practice
- Bin2Summary: Beyond Function Name Prediction in Stripped Binaries with Functionality-Specific Code Embeddings
- Bloat beneath Python's Scales: A Fine-Grained Inter-Project Dependency Analysis
- Bounding Random Test Set Size with Computational Learning Theory
- CC2Vec: Combining Typed Tokens with Contrastive Learning for Effective Code Clone Detection
- CORE: Resolving Code Quality Issues using LLMs
- COSTELLO: Contrastive Testing for Embedding-Based Large Language Model as a Service Embeddings
- Can GPT-4 Replicate Empirical Software Engineering Research?
- Can Large Language Models Transform Natural Language Intent into Formal Method Postconditions?
- ChangeRCA: Finding Root Causes from Software Changes in Large Online Systems
- Characterizing Python Library Migrations
- ClarifyGPT: A Framework for Enhancing LLM-Based Code Generation via Requirements Clarification
- Code-Aware Prompting: A Study of Coverage-Guided Test Generation in Regression Setting using LLM
- CodeArt: Better Code Models by Attention Regularization When Symbols Are Lacking
- CodePlan: Repository-Level Coding using LLMs and Planning
- Component Security Ten Years Later: An Empirical Study of Cross-Layer Threats in Real-World Mobile Applications
- CrossCert: A Cross-Checking Detection Approach to Patch Robustness Certification for Deep Learning Models
- Cut to the Chase: An Error-Oriented Approach to Detect Error-Handling Bugs
- DAInfer: Inferring API Aliasing Specifications from Library Documentation via Neurosymbolic Optimization
- DTD: Comprehensive and Scalable Testing for Debuggers
- DeSQL: Interactive Debugging of SQL in Data-Intensive Scalable Computing
- DeciX: Explain Deep Learning Based Code Generation Applications
- Decomposing Software Verification using Distributed Summary Synthesis
- Demystifying Invariant Effectiveness for Securing Smart Contracts
- Dependency-Induced Waste in Continuous Integration: An Empirical Study of Unused Dependencies in the npm Ecosystem
- Detecting, Creating, Repairing, and Understanding Indivisible Multi-Hunk Bugs
- DiffCoder: Enhancing Large Language Model on API Invocation via Analogical Code Exercises
- Do Large Language Models Pay Similar Attention Like Human Programmers When Generating Code?
- Do Words Have Power? Understanding and Fostering Civility in Code Review Discussion
- DyPyBench: A Benchmark of Executable Python Software
- Effective Teaching through Code Reviews: Patterns and Anti-patterns
- Efficiently Detecting Reentrancy Vulnerabilities in Complex Smart Contracts
- Enhancing Code Understanding for Impact Analysis by Combining Transformers and Program Dependence Graphs
- Enhancing Function Name Prediction using Votes-Based Name Tokenization and Multi-task Learning
- Evaluating Directed Fuzzers: Are We Heading in the Right Direction?
- Evaluating and Improving ChatGPT for Unit Test Generation
- Evolutionary Multi-objective Optimization for Contextual Adversarial Example Generation
- Exploring and Unleashing the Power of Large Language Models in Automated Code Translation
- EyeTrans: Merging Human and Machine Attention for Neural Code Summarization
- Fast Graph Simplification for Path-Sensitive Typestate Analysis through Tempo-Spatial Multi-Point Slicing
- FeatMaker: Automated Feature Engineering for Search Strategy of Symbolic Execution
- Finding and Understanding Defects in Static Analyzers by Constructing Automated Oracles
- Generative AI for Pull Request Descriptions: Adoption, Impact, and Developer Interventions
- Glitch Tokens in Large Language Models: Categorization Taxonomy and Effective Detection
- Go Static: Contextualized Logging Statement Generation
- Harnessing Neuron Stability to Improve DNN Verification
- How Does Simulation-Based Testing for Self-Driving Cars Match Human Perception?
- How to Gain Commit Rights in Modern Top Open Source Communities?
- IRCoCo: Immediate Rewards-Guided Deep Reinforcement Learning for Code Completion
- Improving the Learning of Code Review Successive Tasks with Cross-Task Knowledge Distillation
- Investigating Documented Privacy Changes in Android OS
- JIT-Smart: A Multi-task Learning Framework for Just-in-Time Defect Prediction and Localization
- Java JIT Testing with Template Extraction
- LILAC: Log Parsing using LLMs with Adaptive Parsing Cache
- Learning to Detect and Localize Multilingual Bugs
- Less Cybersickness, Please: Demystifying and Detecting Stereoscopic Visual Inconsistencies in Virtual Reality Apps
- LogSD: Detecting Anomalies from System Logs through Self-Supervised Learning and Frequency-Based Masking
- MTAS: A Reference-Free Approach for Evaluating Abstractive Summarization Systems
- Maximizing Patch Coverage for Testing of Highly-Configurable Software without Exploding Build Times
- Metamorphic Testing of Secure Multi-party Computation (MPC) Compilers
- Mining Action Rules for Defect Reduction Planning
- MirrorFair: Fixing Fairness Bugs in Machine Learning Software via Counterfactual Predictions
- Misconfiguration Software Testing for Failure Emergence in Autonomous Driving Systems
- Mobile Bug Report Reproduction via Global Search on the App UI Model
- Natural Is the Best: Model-Agnostic Code Simplification for Pre-trained Large Language Models
- Natural Symbolic Execution-Based Testing for Big Data Analytics
- On Reducing Undesirable Behavior in Deep-Reinforcement-Learning-Based Software
- On the Contents and Utility of IoT Cybersecurity Guidelines
- Only diff Is Not Enough: Generating Commit Messages Leveraging Reasoning and Action of Large Language Model
- PBE-Based Selective Abstraction and Refinement for Efficient Property Falsification of Embedded Software
- PPM: Automated Generation of Diverse Programming Problems for Benchmarking Code Generation Models
- Partial Solution Based Constraint Solving Cache in Symbolic Execution
- Predicting Code Comprehension: A Novel Approach to Align Human Gaze with Code using Deep Neural Networks
- Predicting Configuration Performance in Multiple Environments with Sequential Meta-Learning
- Predicting Failures of Autoscaling Distributed Applications
- Predictive Program Slicing via Execution Knowledge-Guided Dynamic Dependence Learning
- ProveNFix: Temporal Property-Guided Program Repair
- PyRadar: Towards Automatically Retrieving and Validating Source Code Repository Information for PyPI Packages
- R2I: A Relative Readability Metric for Decompiled Code
- RavenBuild: Context, Relevance, and Dependency Aware Build Outcome Prediction
- Refactoring to Pythonic Idioms: A Hybrid Knowledge-Driven Approach Leveraging Large Language Models
- Revealing Software Development Work Patterns with PR-Issue Graph Topologies
- Rocks Coding, Not Development: A Human-Centric, Experimental Evaluation of LLM-Supported SE Tasks
- Semi-supervised Crowdsourced Test Report Clustering via Screenshot-Text Binding Rules
- Shadows in the Interface: A Comprehensive Study on Dark Patterns
- Sharing Software-Evolution Datasets: Practices, Challenges, and Recommendations
- SimLLM: Calculating Semantic Similarity in Code Summaries using a Large Language Model-Based Approach
- SmartAxe: Detecting Cross-Chain Vulnerabilities in Bridge Smart Contracts via Fine-Grained Static Analysis
- State Reconciliation Defects in Infrastructure as Code
- Static Application Security Testing (SAST) Tools for Smart Contracts: How Far Are We?
- Syntax Is All You Need: A Universal-Language Approach to Mutant Generation
- TIPS: Tracking Integer-Pointer Value Flows for C++ Member Function Pointers
- Towards AI-Assisted Synthesis of Verified Dafny Methods
- Towards Better Graph Neural Network-Based Fault Localization through Enhanced Code Representation
- Towards Efficient Build Ordering for Incremental Builds with Multiple Configurations
- Towards Efficient Verification of Constant-Time Cryptographic Implementations
- TraStrainer: Adaptive Sampling for Distributed Traces with System Runtime State
- Understanding Developers' Discussions and Perceptions on Non-functional Requirements: The Case of the Spring Ecosystem
- Understanding and Detecting Annotation-Induced Faults of Static Analyzers
- Understanding the Impact of APIs Behavioral Breaking Changes on Client Applications
- Unprecedented Code Change Automation: The Fusion of LLMs and Transformation by Example
- Your Code Secret Belongs to Me: Neural Code Completion Tools Can Memorize Hard-Coded Credentials