# AI Testing Call For Papers **URL:** \ **Category:** Archive\ **Created:** [8 November 2018 18:09 UTC](https://club.ministryoftesting.com/t/ai-testing-call-for-papers/19973 "2018-11-08T18:09:18Z")\ **Posts on this page:** 1\ **Page:** 1
**Author:** ![savyasachi](https://avatars.discourse-cdn.com/v4/letter/s/b5e925/32.png) [@savyasachi](https://club.ministryoftesting.com/u/savyasachi)\ **Post date:** [8 November 2018 18:09 UTC](https://club.ministryoftesting.com/t/ai-testing-call-for-papers/19973/1 "2018-11-08T18:09:18Z")
IEEE AI Tests invites papers of original research on AI testing and reports of the best practices in the industry as well as the challenges in practice and research. Testing AI applications Methodologies for testing, verification and validation of AI applications Process models for testing AI applications and quality assurance activities and procedures Quality models of AI applications and quality attributes of AI applications, such as correctness, reliability, safety, security, accuracy, precision, comprehensibility, explainability, etc Whole lifecycle of AI applications, including analysis, esign, development, deployment, operation and evolution Techniques for testing AI applications Test case design, test data generation, test prioritization, test reduction, etc Metrics and measurements of the adequacy of testing AI applications Test oracle for checking the correctness of AI application on test cases Tools and environment for automated and semi-automated software testing AI applications for various testing activities and management of testing resources Specific concerns of software testing with various specific types of AI technologies Statistical machine learning and data mining Symbolic machine learning, decision trees and random forests, reinforcement learning Evolutionary methods and Genetic algorithms Multi-agent systems Heuristic search algorithms Cognitive computing Knowledge management, expert systems Automatic reasoning and theorem proving Constraint Programming and Constraint Optimization Metaprogramming, high-order functions, high-order logic Programming by example, programming synthesis, etc Specific concerns of software testing for various types of AI applications Computer vision and object recognition in image, audio and video Personalized recommendation systems, and business intelligence Driverless vehicles and autonomous robotics Intelligent diagnostic systems Decision-making support systems Prediction and forecast systems Smart cities, smart home, healthcare, and medicine, etc Natural language processing, and intelligent human machine interactions, etc Applications of AI techniques to software testing Machine learning applications to software testing, such as test case generation, test effectiveness prediction and optimization, test adequacy improvement, test cost reduction, etc Constraint Programming for test case generation and test suite reduction Constraint Scheduling and Optimization for test case prioritization and test execution scheduling Multi-agent systems for testing and test services Crowdsourcing and swarm intelligence in software testing Genetic algorithms, search-based techniques and heuristics to optimization of testing Knowledge-based and expert systems for software testing Data quality checking for AI applications Testing and quality assurance for unstructured training data Automatic validation tool for training unstructured data and big data Large-scale unstructured data quality certification Follow the link if anyone has an interesting submission: [IEEE AI Tests Conference 2021](http://www.ieeeaitests.com/html/callForPapers.html)