IFIP-ICTSS is a well-established conference where researchers, developers, testers, and users from industry get together to present and discuss the most recent innovations, experiences and open challenges related to testing software and systems and measuring software quality. 

Topics of interest include, but are not limited to:

    Aspects of testing: test derivation, test selection, test generation, test coverage, test concretization, test implementation and execution, test result analysis, test oracle, verdict computation, test management, active testing and passive testing, monitoring and runtime verification.
    Testing new technologies: this year we encourage submissions focused on testing Large Language Models (LLMs), audit machine learning systems (especially for applications to health) and Quantum systems (programs, computers, and simulators).
    Diversity on testing: diverse generation, selecting diverse test suites, foundations of testing and diversity, applications of entropy and Kolmogorov complexity on test suite diversity.
    Theoretical approaches: formalisms (such as automata, state machines, process algebra, logics, Markov-chains…), testing frameworks, results for compositionality, refinement, soundness and completeness, addressing complex systems, heterogeneous or hybrid systems.
    Modelling languages (such as UML, MATLAB, Simulink, Modelica…) and associated tooling for model-based testing: test generation from models, model-based oracles. Scalability, traceability, quantification issues. Automated support of any parts of the testing activities, testing processes, test-driven development, sound metrics and measurements.
    Testing of quality aspects: Functional, interoperability, unit, integration, performance, load, conformance, non-regression, reliability, robustness.
    Security Testing: methodologies and techniques for continuous security assessment, security monitoring, security review, penetration testing, verification of certification compliance; automation of security testing processes.
    Cross domains and combination of techniques: using other techniques such as proof, model-checking, symbolic execution, abstract interpretation, static analysis, simulation, model learning, machine learning, expert systems, neural networks, genetic algorithms… to improve quality and reduce the effort in testing processes.
    Application aspects and case studies: Communicating systems such as cyberphysical systems, systems of systems, embedded systems, web services systems, smart grids, cloud computing systems, business information systems, real-time systems, distributed and concurrent systems. Case studies and industrial applications involving qualified empirical evaluations.