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Functional test generation from UI test scenarios using reinforcement learning for android applications
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-319-23820-3_24openalex-snapshot
RV-Android: Efficient Parametric Android Runtime Verification, a Brief Tutorial
inferredcites →https://doi.org/10.1007/978-3-319-89363-1_15openalex-snapshot
TCM: Test Case Mutation to Improve Crash Detection in Android
inferredcites →https://doi.org/10.1007/978-3-540-74128-2_6openalex-snapshot
Checking Liveness Properties of Concurrent Systems by Reinforcement Learning
inferredcites →https://doi.org/10.1007/978-3-642-11623-0_17openalex-snapshot
Bounded Rational Search for On-the-Fly Model Checking of LTL Properties
inferredcites →https://doi.org/10.1007/978-3-642-35632-2_11openalex-snapshot
Runtime Verification and Enforcement for Android Applications with RV-Droid
inferredcites →https://doi.org/10.1007/978-3-642-37057-1_19openalex-snapshot
A Grey-Box Approach for Automated GUI-Model Generation of Mobile Applications
inferredcites →https://doi.org/10.1016/b978-0-12-396502-8.00013-9openalex-snapshot
Introduction to Machine Learning
inferredcites →https://doi.org/10.1016/j.swevo.2018.03.011openalex-snapshot
Reinforcement learning versus evolutionary computation: A survey on hybrid algorithms
inferredcites →https://doi.org/10.1016/s0925-2312(00)00324-6openalex-snapshot
Reinforcement Learning: An Introduction
inferredcites →https://doi.org/10.1021/acscentsci.7b00492openalex-snapshot
Optimizing Chemical Reactions with Deep Reinforcement Learning
inferredcites →https://doi.org/10.1049/iet-its.2009.0070openalex-snapshot
Reinforcement learning-based multi-agent system for network traffic signal control
inferredcites →https://doi.org/10.1109/compsac.2019.00021openalex-snapshot
ParaAim: Testing Android Applications Parallel at Activity Granularity
inferredcites →https://doi.org/10.1109/icse.2019.00043openalex-snapshot
AutoTap: Synthesizing and Repairing Trigger-Action Programs Using LTL Properties
inferredcites →https://doi.org/10.1109/icst.2012.88openalex-snapshot
AutoBlackTest: Automatic Black-Box Testing of Interactive Applications
inferredcites →https://doi.org/10.1109/icst.2014.31openalex-snapshot
Automated Generation of Oracles for Testing User-Interaction Features of Mobile Apps
inferredcites →https://doi.org/10.1109/icst.2016.34openalex-snapshot
Automatically Discovering, Reporting and Reproducing Android Application Crashes
inferredcites →https://doi.org/10.1109/icst.2017.61openalex-snapshot
ADRENALIN-RV: Android Runtime Verification Using Load-Time Weaving
inferredcites →https://doi.org/10.1109/icst.2018.00020openalex-snapshot
QBE: QLearning-Based Exploration of Android Applications
inferredcites →https://doi.org/10.1109/icst.2018.00021openalex-snapshot
Automated Accessibility Testing of Mobile Apps
inferredcites →https://doi.org/10.1109/iros.2015.7354078openalex-snapshot
Correct-by-synthesis reinforcement learning with temporal logic constraints
inferredcites →https://doi.org/10.1109/ms.2014.55openalex-snapshot
MobiGUITAR: Automated Model-Based Testing of Mobile Apps
inferredcites →https://doi.org/10.1109/msr.2015.18openalex-snapshot
Mining Android App Usages for Generating Actionable GUI-Based Execution Scenarios
inferredcites →https://doi.org/10.1109/tse.2014.2323982openalex-snapshot
GreenDroid: Automated Diagnosis of Energy Inefficiency for Smartphone Applications
inferredcites →https://doi.org/10.1109/tse.2014.2372785openalex-snapshot
The Oracle Problem in Software Testing: A Survey
inferredcites →https://doi.org/10.1145/2393596.2393666openalex-snapshot
Automated concolic testing of smartphone apps
inferredcites →https://doi.org/10.1145/2491411.2491450openalex-snapshot
Dynodroid: an input generation system for Android apps
inferredcites →https://doi.org/10.1145/2509136.2509549openalex-snapshot
Targeted and depth-first exploration for systematic testing of android apps
inferredcites →https://doi.org/10.1145/2509136.2509552openalex-snapshot
Guided GUI testing of android apps with minimal restart and approximate learning
inferredcites →https://doi.org/10.1145/2544173.2509552openalex-snapshot
Guided GUI testing of android apps with minimal restart and approximate learning
inferredcites →https://doi.org/10.1145/2635868.2635896openalex-snapshot
EvoDroid: segmented evolutionary testing of Android apps
inferredcites →https://doi.org/10.1145/2884781.2884853openalex-snapshot
Reducing combinatorics in GUI testing of android applications
inferredcites →https://doi.org/10.1145/2931037.2931054openalex-snapshot
Sapienz: multi-objective automated testing for Android applications
inferredcites →https://doi.org/10.1145/3005745.3005750openalex-snapshot
Resource Management with Deep Reinforcement Learning
inferredcites →https://doi.org/10.1145/3106237.3106298openalex-snapshot
Guided, stochastic model-based GUI testing of Android apps
inferredcites →https://doi.org/10.1145/3213846.3229500openalex-snapshot
LAND: a user-friendly and customizable test generation tool for Android apps
inferredcites →https://doi.org/10.1145/3278186.3278187openalex-snapshot
Reinforcement learning for Android GUI testing
inferredcites →https://doi.org/10.1145/3278186.3278191openalex-snapshot
A reinforcement learning based approach to automated testing of Android applications
inferredcites →https://doi.org/10.4236/jdaip.2016.44014openalex-snapshot
Double Sarsa and Double Expected Sarsa with Shallow and Deep Learning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/stvr.1845openalex-snapshot
The integration of machine learning into automated test generation: A systematic mapping study
inferred← citeshttps://doi.org/10.1007/978-981-97-5937-8_27openalex-snapshot
Functional Test Generation Based on Requirements Defined at GUI Level
inferred← citeshttps://doi.org/10.1016/j.envsoft.2025.106692openalex-snapshot
A framework for the acceptance testing of geospatial search engines
inferred← citeshttps://doi.org/10.1049/sfw2.12123openalex-snapshot
A systematic mapping study for graphical user interface testing on mobile apps
inferred← citeshttps://doi.org/10.1109/access.2022.3218902openalex-snapshot
Fast Witness Generation for Readable GUI Test Scenarios via Generalized Experience Replay
inferred← citeshttps://doi.org/10.1109/apsec65559.2024.00017openalex-snapshot
A Study of Using Multimodal LLMs for Non-Crash Functional Bug Detection in Android Apps
inferred← citeshttps://doi.org/10.1109/ase56229.2023.00218openalex-snapshot
Adaptive REST API Testing with Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/icmeas58693.2023.10429864openalex-snapshot
Reinforcement Learning for Testing Android Applications: A Review
inferred← citeshttps://doi.org/10.1109/icse55347.2025.00179openalex-snapshot
A Multi-Agent Approach for REST API Testing with Semantic Graphs and LLM-Driven Inputs
inferred← citeshttps://doi.org/10.1109/icst60714.2024.00045openalex-snapshot
End-to-End RPA-Like Testing Using Reinforcement Learning
inferred← citeshttps://doi.org/10.1109/iscmi67495.2025.11358481openalex-snapshot
Advances in Automated Reinforcement Learning: A Literature Review
inferred← citeshttps://doi.org/10.1109/qrs-c63300.2024.00049openalex-snapshot
Testing and Reinforcement Learning - A Structured Literature Review
inferred← citeshttps://doi.org/10.1109/qrs57517.2022.00113openalex-snapshot
Scriptless GUI Testing on Mobile Applications
inferred← citeshttps://doi.org/10.1145/3474624.3474634openalex-snapshot
Deep Reinforcement Learning based Android Application GUI Testing
inferred← citeshttps://doi.org/10.1145/3485533openalex-snapshot
Fully automated functional fuzzing of Android apps for detecting non-crashing logic bugs
inferred← citeshttps://doi.org/10.1145/3540250.3549134openalex-snapshot
Avgust: automating usage-based test generation from videos of app executions
inferred← citeshttps://doi.org/10.1145/3597926.3598138openalex-snapshot
An Empirical Study of Functional Bugs in Android Apps
inferred← citeshttps://doi.org/10.1145/3652150openalex-snapshot
DinoDroid: Testing Android Apps Using Deep Q-Networks
inferred← citeshttps://doi.org/10.1145/3678719.3685691openalex-snapshot
Use of ChatGPT as an Assistant in the End-to-End Test Script Generation for Android Apps
inferred← citeshttps://doi.org/10.1145/3691620.3695511openalex-snapshot
DeepREST: Automated Test Case Generation for REST APIs Exploiting Deep Reinforcement Learning
inferred← citeshttps://doi.org/10.1145/3726525openalex-snapshot
GUI Test Migration via Abstraction and Concretization
inferred← citeshttps://doi.org/10.11606/t.55.2022.tde-03062022-162453openalex-snapshot
DeepRLGUIMAT: Deep Reinforcement Learning-based GUI Mobile Application Testing Approach
inferred← citeshttps://doi.org/10.2478/amns.2023.2.00787openalex-snapshot
Research on the application of ergonomics in UI interface design
inferred← citeshttps://doi.org/10.3390/app14020549openalex-snapshot
An Effective GDP-LSTM and SDQL-Based Finite State Testing of GUI
inferred← citeshttps://doi.org/10.3929/ethz-b-000512448openalex-snapshot
Fully Automated Functional Fuzzing of Android Apps for Detecting Non-crashing Logic Bugs
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