Automated object-flow testing of dynamic process interaction models

Simulation modeling provides powerful decision support capabilities for production planning in manufacturing systems, yet widespread adoption remains limited by significant barriers in model development and maintenance. Traditional simulation approaches require substantial expertise, time investment, and financial resources, creating accessibility challenges particularly for small and medium enterprises. Current research on automatic simulation generation overlooks the significant potential that generative AI can offer in bridging the gap between natural language expression and executable model creation. This paper presents a novel methodology integrating large language models (LLMs) with automatic simulation model generation (ASMG) to enable direct generation of executable simulation models from natural language conversations. Unlike existing ASMG approaches that require formal specifications or simulation knowledge, our framework reduces programming requirements by allowing users to create functional models through conversational interaction. Our approach leverages natural language processing capabilities to transform user requests into executable simulation models without requiring specialized programming knowledge, enhancing human–machine interaction in production planning environments. The framework implements a four-step process: user intent expression through natural language interfaces, knowledge extraction using structured templates, simulation model construction via object-oriented data-driven components, and simulation execution with comprehensive result analysis for resource utilization, bottleneck identification, and production scheduling optimization. Performance testing demonstrates successful model generation across 18 supported action types with response times ranging from 8 s for simple operations to 5 min for complete manufacturing system creation. By enabling direct conversion of natural language requests into functional simulation models, this LLM-enhanced ASMG approach represents a step toward expanding access to simulation technology for non-expert users while maintaining the analytical power needed for complex manufacturing decision support and production control.

BackgroundWe developed a Monte Carlo Markov model designed to investigate the effects of modifying cardiovascular disease (CVD) risk factors on the burden of CVD. Internal, predictive, and external validity of the model have not yet been established.MethodsThe Rotterdam Ischemic Heart Disease and Stroke Computer Simulation (RISC) model was developed using data covering 5 years of follow-up from the Rotterdam Study. To prove 1) internal and 2) predictive validity, the incidences of coronary heart disease (CHD), stroke, CVD death, and non-CVD death simulated by the model over a 13-year period were compared with those recorded for 3,478 participants in the Rotterdam Study with at least 13 years of follow-up. 3) External validity was verified using 10 years of follow-up data from the European Prospective Investigation of Cancer (EPIC)-Norfolk study of 25,492 participants, for whom CVD and non-CVD mortality was compared.ResultsAt year 5, the observed incidences (with simulated incidences in brackets) of CHD, stroke, and CVD and non-CVD mortality for the 3,478 Rotterdam Study participants were 5.30% (4.68%), 3.60% (3.23%), 4.70% (4.80%), and 7.50% (7.96%), respectively. At year 13, these percentages were 10.60% (10.91%), 9.90% (9.13%), 14.20% (15.12%), and 24.30% (23.42%). After recalibrating the model for the EPIC-Norfolk population, the 10-year observed (simulated) incidences of CVD and non-CVD mortality were 3.70% (4.95%) and 6.50% (6.29%). All observed incidences fell well within the 95% credibility intervals of the simulated incidences.ConclusionsWe have confirmed the internal, predictive, and external validity of the RISC model. These findings provide a basis for analyzing the effects of modifying cardiovascular disease risk factors on the burden of CVD with the RISC model.

Popularity of Software Defined Network (SDN) technology is spreading rapidly and corporate networks are deploying to take advantages of its features. Control & Data planes are segregated in SDN and simple forwarding devices enabled with OpenFlow protocol is used to forward data planes. The responsibility of control planes are taken by controller into SDN network. The data packets are generated by source host and forwarded to destination host by seeing destination address of such packet without validating source host address. Flow of data packets is controlled by controller setting up required flow entries into flow table of forwarding devices. Initially forwarding devices do not have any security & control and they are not able to forward traffic generated by attached hosts. Data packets of attached hosts are sent to the controller by forwarding devices for generation of control packets and setup necessary flow entries into device flow table. Source IP spoofed attacks may be setup by attacker in this situation and perform different type of attacks. There are some techniques for prevention and mitigation from such attacks. In this study, we offer an analysis of available source address validation techniques for SDN environment. The study discussed various features, limitations and gaps of source address validation solutions and provided various areas in SDN Security for future research.

In this paper we discuss validation and verification of simulation models. Four different approaches to deciding model validity are described; two different paradigms that relate validation and verification to the model development process are presented; various validation techniques are defined; conceptual model validity, model verification, operational validity, and data validity are discussed; a way to document results is given; a recommended procedure for model validation is presented; and accreditation is briefly discussed.

For the verification and validation of microscopic simulation models of pedestrian flow, we have performed experiments for different kind of facilities and sites where most conflicts and congestion happens e.g. corridors, narrow passages, and crosswalks. The validity of the model should compare the experimental conditions and simulation results with video recording carried out in the same condition like in real life e.g. pedestrian flux and density distributions. The strategy in this technique is to achieve a certain amount of accuracy required in the simulation model. This method is good at detecting the critical points in the pedestrians walking areas. For the calibration of suitable models we use the results obtained from analysing the video recordings in Hajj 2009 and these results can be used to check the design sections of pedestrian facilities and exits. As practical examples, we present the simulation of pilgrim streams on the Jamarat bridge (see Figure 5). The objectives of this study are twofold: first, to show through verification and validation that simulation tools can be used to reproduce realistic scenarios, and second, gather data for accurate predictions for designers and decision makers.

Building and delivering high-quality software is critical in software engineering and requires verification and validation processes for end-to-end testing that are reliable, robust, and deliver correct results fast. Manual testing of LLM models, while feasible, is very time-consuming and inefficient and has scalability issues depending on how big the model under test (MUT) is. Recent research and cutting-edge technology innovations in LLM models have deeply influenced software engineering. We need to integrate its impact robustly in areas of model analysis, test automation, model execution, debugging, and report generation.This paper focuses on a framework approach for automated software testing of the LLM models to reduce human interactions and has improved results in a fast, cost-efficient, and time-efficient manner for automated testing methods for industries. The proposed Automation Framework (LLMAutoE2E) leverages and integrates LLMs for testing of different LLM models (like BERT, BART, Hugging Face, and multiple models available to test) to automate the end-to-end execution lifecycle of the LLM models. By leveraging LLMs, companies and industries can generate automated test cases, automated unit test codes, automated integration and end-to-end tests, and automated reporting of the LLM model's execution results. This research emphasizes the potential of the Automation Framework (LLMAutoE2E) for LLM to automate and streamline the overall execution and result generation of the LLM models and the overall testing workflows while addressing challenges in current LLM models testing, its accuracy and scalability for deployments, and reporting. The proposed Automation Framework (LLMAutoE2E) can also automate defect analysis, which improves the software reliability by a manifold and reduces the development cycles for companies. This Research paper details the role of Automation Frameworks for LLMs and how it is transforming QA processes, key methodologies, improving reliability and efficiency, addressing current challenges like model safety, bias detection, and continuous monitoring, and future trends in AI-driven software testing.

The four most readily available tests of autocorrelation in dynamic models namely Durbin’s M test, Durbin’s H test, Breusch Godfrey test (BGF) and Ljung & Box (Q) test are compared in terms of their power for varying sample sizes, levels of autocorrelation and significance using Monte Carlo simulations in STATA. Power comparison reveals that the Durbin M test is the best option for testing the hypothesis of no autocorrelation in dynamic models for all sample sizes. Breusch Godfrey’s test has comparable and at times minutely better performance than Durbin’s M test however in small sample sizes, Durbin’s M test outperforms the Breusch Godfrey test in terms of power. The Durbin H and the Ljung & Box Q tests consistently occupy the second last and last positions respectively in terms of power performance with maximum power gap of 63 & 60% respectively from the best test (M test).

ExoHeat: A continuous heating solution for bi-directional sap flow in small-diameter plant organs demonstrated in tomato peduncles

The failure of hardware or software in the medical domain can lead to injuries and loss of life. Design errors are a major source of the defects that are introduced during the system development process. Traditional validation and verification techniques such as simulation and testing are effective methods for detecting these defects, but are seriously limited in that they cannot guarantee to find all existing defects. Formal methods provide a complementary alternative to testing and simulation, and, although we do not yet have a ‘theory of coverage’ when combining formal validation and verification techniques with testing and simulation, the combination provides better coverage than any one of them on its own. The insulin infusion pump (IIP) is a critical system that is used by millions of people around the world. IIP failures are responsible for a large number of serious illnesses and deaths. This paper presents the formalization of the glucose homeostasis mechanism that provides an environmental model for the IIP. We can then use this model to validate the appropriateness and correctness of system behaviours at an early stage of development.

To better utilize the potential of system simulation models and simulators, industrially applicable methods for Verification, Validation and Uncertainty Quantification (VV&UQ) are crucial. This paper presents an exploratory case study of VV&UQ techniques applied on models integrated in aircraft system simulators at Saab Aeronautics and in driving simulators at the Swedish National Road and Transport Research Institute (VTI). Results show that a large number of Verification and Validation (V&V) techniques are applied, some of which are promising for further development and use in simulator credibility assessment. Regarding the application of UQ, a large gap between academia and this part of industry has been identified, and simplified methods are needed. The applicability of the NASA Credibility Assessment Scale (CAS) at the studied organizations is also evaluated and it can be concluded that the CAS is considered to be a usable tool for achieving a uniform level of V&V for all models included in a simulator, although its implementation at the studied organizations requires tailoring and coordination.

Simulation models are a valuable tool for operations research (OR) as they enable the study of the behavior of complex systems. However, the effectiveness of these models depends on their accuracy and reliability. Therefore, it is important to employ verification and validation (V&V) techniques to ensure that the models adequately represent the real system. This article provides a review of V&V techniques for simulation models in operations research (OR).

Performance evaluation of framed slotted ALOHA with reservation packets and succesive interference cancelation for M2M networks

Department of Defence Architecture Framework(DoDAF) is an important method to ensure the quality of system design. One way for DoD architecture validation and assess is to transform the DoD architecture products into executable models, then the performance of DoD architecture can be tested through analyzing model execution process and result. Based on the different advantage of UML(Unified Modelling Language) and Petri nets, the paper applies some kinds of views in UML to describe the relative DoD architecture products. Considering the relationship among the products, the UML views for products are transformed into ECPN (Extended Colored Petri Nets) simulation models according to the transformation rules. So the dynamic behavior of system can be displayed by those simulation model, and whether the time-order relation, information flow and system interface is reasonable, or the system function satisfies the military requirement, and the change of system state is correct, can be checked evidently. At last, the paper gives a case in the air defense system using simulation validation method proposed by it.

A model for simulating adaptive, dynamic flows on networks: Application to petroleum infrastructure

The paper is dedicated to network development in the network economy. The current economy needs to look not only at networks with only dynamic flows and with a fixed structure, but as a dynamic system its structure evolves and changes. Structure and behaviour dynamics of network systems can be modelled as complex adaptive systems and use agent-oriented simulation to demonstrate origin, perturbation effects, and sensitivity with regard to initial conditions. Survival of firms is associated with the value of so-called fitness function. Firms whose fitness value falls below a certain threshold will be extinguished. In this way, it is possible to partially model network growth. A simulation model in SIMUL8 is proposed.