Paper 1: Automated Test Input Generation for Android: Towards Getting There in an Industrial Case (ICSE'17)
Paper 2: Automated Concolic Testing of Smartphone Apps (FSE'12)
Paper 3: PATDroid: Permission-Aware GUI Testing of Android (FSE'17)
paper 4: Guided, Stochastic Model-Based GUI Testing of Android Apps (FSE'17)
paper 5: Rousillon: Scraping Distributed Hierarchical Web Data (UIST'16)
paper 6: SUGILITE: Creating Multimodal Smartphone Automation by Demonstration (CHI'17)
paper 7: Monkey See, Monkey Do: Effective Generation of GUI Tests with Inferred Macro Events (ISSTA'16)
paper 8: DetReduce: Minimizing Android GUI Test Suites for Regression Testing (ICSE'18)
paper 9: Minimizing GUI Event Traces (FSE'16)
paper 10: Towards the Use of the Readily Available Tests from the Release Pipeline as Performance Tests. Are We There Yet? (ICSE'20)
paper 11: TCM: Test Case Mutation to Improve Crash Detection in Android (FASE'18)
paper 12: Crash Reproduction via Test Case Mutation (FSE'15)
paper 13: Practical GUI Testing of Android Applications via Model Abstraction and Refinement (ICSE'19)
paper 14: Efficiently Manifesting Asynchronous Programming Errors in Android Apps (ASE'18)
paper 15: Systematic Execution of Android Test Suites in Adverse Conditions (ISSTA'15)
paper 16: Leveraging Existing Tests in Automated Test Generation for Web Applications (ASE'14)
paper 17: Automated Generation of Oracles for Testing User-interaction Features of Mobile Apps (STVR'14)
paper 18: AIMDROID: Activity-Insulated Multi-level Automated Testing for Android Applications (ICSME'17)
paper 19: Crowd Intelligence Enhances Automated Mobile Testing (ASE'17)
paper 20: Finding Resume and Restart Errors in Android Applications (OOPSLA'16)
paper 21: Automated Model-Based Android GUI Testing using Multi-level GUI Comparison Criteria (ASE'16)
paper 22: EHBDroid: Beyond GUI Testing for Android Applications (ASE'17)
paper 23: Data Loss Detector: Automatically Revealing Data Loss Bugs in Android Apps (ISSTA'20)
paper 24: Reducing combinatorics in GUI testing of android applications (ICSE'16)
paper 25: Automated Testing with Targeted Event Sequence Generation (ISSTA'16)
paper 26: PUMA: Programmable UI-Automation for Large-Scale Dynamic Analysis of Mobile Apps (MobiSys‘14)
paper 27: QBE: qlearning-based exploration of Android applications (ICST'18)
paper 28: Automatically Discovering, Reporting and Reproducing Android Application Crashes (ICST'16)
paper 29: A Grey-box Approach for Automated GUI-Model Generation of Mobile Applications (FASE'13)
paper 30: Synthesizing Highly Expressive SQL Queries from Input-Output Examples (pldi'17) （It is not finished yet）
paper 31: FrAngel: Component-Based Synthesis with Control Structures (POPL'19) （It is not finished yet）
paper 32: Test-Driven Synthesis (PLDI'14) (It is not finished yet）
paper 33: Synthesizing Programs That Expose Performance Bottlenecks (CGO'18)
paper 34: Efficiently, Effectively Detecting Mobile App Bugs with AppDoctor (EuroSys'14)
paper 35: Caiipa: Automated Large-scale Mobile App Testing through Contextual Fuzzing (MobiCom’14)
paper 36: Using Frugal User Feedback with Closeness Analysis on Code to Improve IR-Based Traceability Recovery (ICPC'19)
paper 37: A Guided Genetic Algorithm for Automated Crash Reproduction (ICSE'17)
paper 38: Systematically Testing Background Services of Mobile Apps (ASE'17)
paper 39: Towards Model Checking Android Applications (TSE'18)
paper 40: Oracle-guided component-based program synthesis (ICSE'10)
paper 41: Translating Video Recordings of Mobile App Usages into Replayable Scenarios (ICSE'20)
paper 42: Revealing Injection Vulnerabilities by Leveraging Existing Tests (ICSE'20)
paper 54: Debugging Inputs （ICSE"20）
-------performance papers
paper 43: Identifying Software Performance Changes across Variants and Versions (ASE'2020)
paper 44: CP-Detector: Using Configuration-Related Performance Properties to Expose Performance Bugs (ASE'2020)
paper 45: Mastering Uncertainty in Performance Estimations of Configurable Software Systems (ASE'2020)
paper 45: Understanding Performance Concerns in the API Documentation of Data Science Libraries (ASE'2020)
paper 45: PerfCI: A Toolchain for Automated Performance Testing during Continuous Integration of Python Projects (ASE'2020)
paper 52: PerfLearner: Learning from Bug Reports to Understand and Generate Performance Test Frames (ASE'18)
---------android papers paper 46: Demystifying Diehard Android Apps(ASE'2020)
paper 47: UI Obfuscation and Its Effects on Automated UI Analysis for Android Apps(ASE'2020)
paper 48: ER Catcher: A Static Analysis Framework for Accurate and Scalable Event-Race Detection in Android(ASE'2020)
paper 49: Automated Third-Party Library Detection for Android Applications: Are We There Yet?(ASE'2020)
paper 50: Test Automation in Open-Source Android Apps: A Large-Scale Empirical Study(ASE'2020)
paper 51: A Framework for Automated Test Mocking of Mobile Apps(ASE'2020)
paper 53: Discovering UI Display Issues with Visual Understanding(ASE'20)