Recent paper related to SE and AI
ASE(#ase)
- 2021
- Deep GUI: Black-box GUI Input Generation with Deep Learning
- DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learning
- DeepMemory: Model-based Memorization Analysis of Deep Neural Language Models
- DeepMetis: Augmenting a Deep Learning Test Set to Increase its Mutation Score
- FIGCPS: Effective Failure-inducing Input Generation for Cyber-Physical Systems with Deep Reinforcement Learning
- Automated Testing for Machine Translation via Constituency Invariance
- Efficient state synchronisation in model-based testing through reinforcement learning
- FRUGAL: Unlocking Semi-supervised Learning for Software Analytics
- On Multi-Modal Learning of Editing Source Code
-
2020
- Invited Talk: Smart Development of Mobile Apps with Deep Learning
- Hybrid Deep Neural Networks to Infer State Models of Black-Box Systems
- MARBLE: Model-Based Robustness Analysis of Stateful Deep Learning Systems
- A Deep Multitask Learning Approach for Requirements Discovery and Annotation from Open Forum
- Audee: Automated Testing for Deep Learning Frameworks
- Safety and Robustness for Deep Learning with Provable Guarantees
- When Deep Learning Meets Smart Contracts
- Problems and Opportunities in Training Deep Learning Software Systems: An Analysis of Variance
- BugPecker: Locating Faulty Methods with Deep Learning on Revision Graphs
- Cats Are Not Fish: Deep Learning Testing Calls for Out-Of-Distribution Awareness
- Towards Robust Production Machine Learning Systems: Managing Dataset Shift
- A Machine Learning based Approach to Autogenerate Diagnostic Models for CNC machines
- Emotion Detection in Roman Urdu Text using Machine Learning
- Machine Learning meets Software Performance: Optimization, Transfer Learning, and Counterfactual Causal Inference
-
2019
- A Study of Oracle Approximations in Testing Deep Learning Libraries
- An Empirical Study towards Characterizing Deep Learning Development and Deployment across Different Frameworks and Platforms
- Apricot: A Weight-Adaptation Approach to Fixing Deep Learning Models
- Property Inference for Deep Neural Networks
- Wuji: Automatic Online Combat Game Testing Using Evolutionary Deep Reinforcement Learning
- Machine Learning Based Automated Method Name Recommendation: How Far Are We
ISSTA
-
2021
- AdvDoor: Adversarial Backdoor Attack of Deep Learning System
- Deep Just-in-Time Defect Prediction: How Far Are We?
- DeepCrime: Mutation Testing of Deep Learning Systems Based on Real Faults
- DeepHyperion: Exploring the Feature Space of Deep Learning-Based Systems through Illumination Search
- Exposing Previously Undetectable Faults in Deep Neural Networks
- Predoo: Precision Testing of Deep Learning Operators
- TERA: Optimizing Stochastic Regression Tests in Machine Learning Projects
-
2020
- DeepGini: Prioritizing Massive Tests to Enhance the Robustness of Deep Neural Networks
- DeepSQLi: Deep Semantic Learning for Testing SQL Injection
- Effective White-Box Testing of Deep Neural Networks with Adaptive Neuron-Selection Strategy
- Detecting Flaky Tests in Probabilistic and Machine Learning Applications
- Detecting and Understanding Real-World Differential Performance Bugs in Machine Learning Libraries
- Higher Income, Larger Loan? Monotonicity Testing of Machine Learning Models
-
2019
- DeepHunter: A Coverage-Guided Fuzz Testing Framework for Deep Neural Networks
- Search-based Test and Improvement of Machine-Learning-Based Anomaly Detection Systems
ICSE
- 2021
- An Empirical Study on Deployment Faults of Deep Learning Based Mobile Applications
- DeepBackdoor: Black-box Backdoor Attack on Deep Learning Models through Neural Payload Injection
- DeepLV: Suggesting Log Levels Using Ordinal Based Neural Networks
- DeepLocalize: Fault Localization for Deep Neural Networks
- Graph-based Fuzz Testing for Deep Learning Inference Engines
- Measuring Discrimination to Boost Comparative Testing for Multiple Deep Learning Models
- Prioritizing Test Inputs for Deep Neural Networks via Mutation Analysis
- RobOT: Robustness-Oriented Testing for Deep Learning Systems
- Scalable Quantitative Verification For Deep Neural Networks
- Self-Checking Deep Neural Networks in Deployment
- An Empirical Study of Refactorings and Technical Debt in Machine Learning Systems
- Are Machine Learning Cloud APIs Used Correctly?
- Automatic Unit Test Generation for Machine Learning Libraries: How Far Are We?
- CURE: Code-Aware Neural Machine Translation for Automatic Program Repair
- Testing Machine Translation via Referential Transparency
- White-Box Analysis over Machine Learning: Modeling Performance of Configurable Systems
- 2020
- An Empirical Study on Program Failures of Deep Learning Jobs
- DISSECTOR: Input Validation for Deep Learning Applications by Crossing-layer Dissection
- Detection of Hidden Feature Requests from Massive Chat Messages via Deep Siamese Network
- Fuzz Testing based Data Augmentation to Improve Robustness of Deep Neural Networks
- Importance-Driven Deep Learning System Testing
- ReluDiff: Differential Verification of Deep Neural Networks
- Repairing Deep Neural Networks: Fix Patterns and Challenges
- Software Visualization and Deep Transfer Learning for Effective Software Defect Prediction
- Taxonomy of Real Faults in Deep Learning Systems
- Towards Characterizing Adversarial Defects of Deep Learning Software from the Lens of Uncertainty
- Unblind Your Apps: Predicting Natural-Language Labels for Mobile GUI Components by Deep Learning
- Automatic Testing and Improvement of Machine Translation
- Structure-Invariant Testing for Machine Translation
- 2019
- Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing
- CRADLE: Cross-Backend Validation to Detect and Localize Bugs in Deep Learning Libraries
- DeepPerf: Performance Prediction for Configurable Software with Deep Sparse Neural Network
- Guiding Deep Learning System Testing using Surprise Adequacy
- On Learning Meaningful Code Changes via Neural Machine Translation
ESEC/FSE
-
2021
- A Comprehensive Study of Deep Learning Compiler Bugs
- Exposing Numerical Bugs in Deep Learning via Gradient Back-Propagation
- Bias in Machine Learning Software: Why? How? What to Do?
- Explaining Mispredictions of Machine Learning Models using Rule Induction
- FLEX: Fixing Flaky Tests in Machine Learning Projects by Updating Assertion Bounds
- Fair Preprocessing: Towards Understanding Compositional Fairness of Data Transformers in Machine Learning Pipeline
-
2020
- A Comprehensive Study on Challenges in Deploying Deep Learning Based Software
- Correlations between Deep Neural Network Model Coverage Criteria and Model Quality
- Deep Learning Library Testing via Effective Model Generation
- DeepSearch: A Simple and Effective Blackbox Attack for Deep Neural Networks
- Dynamic Slicing for Deep Neural Networks
- Is Neuron Coverage a Meaningful Measure for Testing Deep Neural Networks?
- Model-Based Exploration of the Frontier of Behaviours for Deep Learning System Testing
- Object Detection for Graphical User Interface: Old Fashioned or Deep Learning or a Combination?
- On Decomposing a Deep Neural Network into Modules
- Do the Machine Learning Models on a Crowd Sourced Platform Exhibit Bias? An Empirical Study on Model Fairness
- Machine Translation Testing via Pathological Invariance
- Mining Assumptions for Software Components using Machine Learning
-
2019
- null
IJCAI
-
2021
- BOBCAT: Bilevel Optimization-Based Computerized Adaptive Testing
-
2020
- Metamorphic Testing and Certified Mitigation of Fairness Violations in NLP Models
AAAI
-
2021
- Group Testing on a Network
- Testing Independence between Linear Combinations for Causal Discovery
-
2020
- A MaxSAT-based Framework for Group Testing
- A New Framework for Online Testing of Heterogeneous Treatment Effect
-
2019
- On Testing of Samplers
- DeepFuzz: Automatic Generation of Syntax Valid C Programs for Fuzz Testing
NeurIPS
-
2020
- On the Value of Out-of-Distribution Testing: An Example of Goodhart's Law
- A/B Testing in Dense Large-Scale Networks: Design and Inference
-
2019
- Online Neural Connectivity Estimation with Noisy Group Testing
- Private Identity Testing for High-Dimensional Distributions
- Testing Determinantal Point Processes
ICML
-
2021
- Exploiting structured data for learning contagious diseases under incomplete testing
- Robust Testing and Estimation under Manipulation Attacks
- Active Testing: Sample-Efficient Model Evaluation
- Testing DNN-based Autonomous Driving Systems under Critical Environmental Conditions
-
2020
- Is There a Trade-Off Between Fairness and Accuracy? A Perspective Using Mismatched Hypothesis Testing
- Does the Markov Decision Process Fit the Data: Testing for the Markov Property in Sequential Decision Making
-
2019
- Conditional Independence in Testing Bayesian Networks
- Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits
