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ESA Solar Orbiter was launched from Cape Canaveral in collaboration with NASA on the February 10, 2020 to start its journey around the Sun, with the commissioning phase ending in April 2020. After commissioning, ESA set a tighter pointing requirement goal to further improve the performance in Fine Pointing Mode, in preparation of the upcoming start of Science Phase. The first part of this paper outlines the end-to-end process which allowed - in just six months – to update the Fine Pointing Mode Design, re-tune the controller with refined assumptions taken from flight data and robust methods and execute full validation of the new AOCS Software on the Avionics Test bench at Airbus Defence and Space. The second part of the paper describes the upload in flight of the new Software and the analysis of the on-orbit pointing performance, which showed a significant improvement with respect to the previous one, thus contributing to the success of the Mission's scientific goals. • Solar Orbiter Payload Instruments required a better pointing jitter performance (Relative Pointing Error) after launch • Root cause analysis on flight telemetry to identify driver contributors to pointing error • Fine Pointing Mode controller design and tuning updated with refined inputs based on flight data and with robust control methods • Controller uploaded in flight significantly improved the Spacecraft pointing performance [ABSTRACT FROM AUTHOR]

High dimensional simulation of exchangeable multivariate Bernoulli distributions is a challenging and important issue in applications, for example in credit risk models. The main contributions of this paper are, even for high dimensions, algorithms to sample from exchangeable multivariate Bernoulli distributions and to determine the distributions and the bounds of a wide class of indices and measures of probability mass functions. Unlike the algorithms present in the literature the proposed method gives the possibility to simulate also from negatively correlated distributions. Such a method is based on the geometrical structure of the class of exchangeable Bernoulli probability mass functions, which are points in a convex polytope whose extremal points are analytically known. Estimation and testing are also addressed. • We provide an algorithm for high dimension simulation, estimation and testing. • We provide an algorithm for uniform sampling, also in high dimension. • We build the sampling distribution of relevant measures across the class. • We develop an example of application in finance (credit risk models). • We develop software for simulation and testing. [ABSTRACT FROM AUTHOR]

Convolutional neural networks (CNNs) are widely adopted in safety-critical systems, including space applications and autonomous vehicles. Field-programmable gate arrays (FPGAs) based on SRAM are preferred for accelerating CNN computations due to their unique characteristics. However, the configuration memory of FPGAs is susceptible to single event effects (SEEs), which can corrupt computations and lead to misclassification of CNN outputs. In this study, we investigated the impact of SEEs on SRAM-based FPGAs with Two-Photon Absorption (TPA) laser fault injections through a comparative analysis of two popular CNN acceleration architectures: streaming architecture (SA) and single compute engine (SCE). Experimental results show that SA-based CNNs require more hardware resources but exhibit superior resilience against single event upsets (SEUs). Without any Radiation Hardened by Design (RHBD) protection, SCE has an error rate approximately twice as high as SA. To mitigate errors, the Xilinx IP core - Soft Error Mitigation (SEM) is used for error detection and correction, leading to error rate reductions of up to 50 % in both architectures. Importantly, we propose the AutoDPR-SEM (Autonomous Dynamic Partial Reconfiguration for Soft Error Mitigation) approach, which automatically reconfigures the SEM IP core when it remains idle due to uncorrectable errors. AutoDPR-SEM significantly improves CNN error rates, reducing errors by approximately 17.8 times in SCE and 14.8 times in SA. We also applied software level simulation to validate the TPA experiment, showing similar trends of the testing results across all models. In conclusion, the study confirms the feasibility of AutoDPR-SEM in both architectures, showcasing its potential to improve CNN error rates in safety-critical systems. • Implemented two FPGA-based CNN accelerator architectures: Streaming and Single Computation Engine. • Conducted sensitivity evaluations of the FPGA-based CNN accelerators using laser injection. It has been validated through software simulations. • Improved reliability of these two architectures by implementing the underlying Soft Error Mitigation (SEM) IP core. • Developed dynamic partial reconfiguration (DPR) technology to improve SEM capabilities without introducing redundancy in timing. • Validated radiation hardening using laser test and software simulation; identified SEM core with DPR is effective. [ABSTRACT FROM AUTHOR]

The rapid growth of mobile devices has ushered in an era of different device platforms. Different devices require a consistent user experience, especially with similar graphical user interfaces (GUIs). However, the different code bases of the various operating systems as well as the different GUI layouts and resolutions of the various devices pose a challenge for automated software testing. Crowdsourced software testing (CST) has emerged as a viable solution where crowdsourced workers perform tests on their own devices and provide detailed bug reports. Although CST is cost-effective, it is not very efficient and requires a large number of workers for manual testing. The potential of optimizing CST reproduction testing through computer vision remains largely untapped, especially when considering the uniformity of GUI elements on different devices. In this study, we present a novel deep learning model specifically designed to re-identify GUI elements in CST reproduction test scenarios, regardless of the underlying code changes on different devices. The model features a robust backbone network for feature extraction, an innovative attention mechanism with learnable factors to enhance the features of GUI elements and minimize interference from their backgrounds, and a classifier to determine matching labels for these elements. Our approach was validated on a large GUI element dataset containing 31,098 element images for training, 115,704 element images from real apps for testing, and 67 different background images. The results of our experiments underline the excellent accuracy of the model and the importance of each component. This work is a major step forward in improving the efficiency of reproduction testing in CST. The innovative solutions we propose could further reduce labor costs for CST platforms. • ERINet: A novel CNN model for re-identifying GUI elements across devices. • Attention mechanism with Learnable Factor enhances GUI element re-identification. • Dataset: 31,098 training, 115,704 testing GUI images, and 67 backgrounds. • Potential to revolutionize cross-device testing in crowd-sourced environments. [ABSTRACT FROM AUTHOR]

[Display omitted] • Modeling of four temperature-based properties of IL-mixture using semi-empirical correlations. • Determination semi-empirical equation coefficients for each cation-family with novel optimization algorithm. • Investigation accuracy of cubic EoS, non-cubic EoS and semi-empirical correlation on IL-mixture density. Ionic liquids are a significant type of organic salts with attractive and superior physicochemical features for employing in a number of chemical processes. Ionic liquids include one large and asymmetric cationic or anionic functional group. The properties of cationic functional group are almost similar and it is main motivation of this study. In the present investigation, we extended various semi-empirical correlations to predict some temperature-based properties of ionic liquids mixture (IL-mixture). These properties are density, viscosity, surface tension and bubble point pressure. In the case of IL-mixture density, modified Rackett equation and Taylor equation with three scenarios, modified Gardas and Coutinho equation were considered and the obtained results were compared with Peng-Robinson equation of state (EoS), Patel-Teja EoS and perturbed-chain statistical associating fluid theory EoS. In the case of IL-mixture viscosity, two types of activation energy concept models were used and also, Lee-Kesler method and modified Brock and Bird were applied to predict IL-mixture bubble point pressure and IL-mixture surface tension, respectively. A used dataset was collected from reliable literature including 2731 data points of bubble pressure (23 binary system), 4643 data points of density (102 binary system), 1011 data points of viscosity (32 binary system) and 391 data points of surface tension (16 binary system). These data relevant to 12 cation-family and 36 solvents. The all of the data was haphazardly separated in two subsets of train and test with a computer program. The obtained results indicated all used semi-empirical correlations gives the best match with corresponding experimental data and the values of statistical parameters demonstrated this hypothesis. [ABSTRACT FROM AUTHOR]

Modified Condition/Decision Coverage (MC/DC) is an important criterion to test the safety-critical applications because it generates test cases in a linear manner from N + 1 to 2 N , where N is the number of Atomic Conditions in a given predicate. It is desirable in comparison to the exponential test cases produced for Multiple Condition Coverage (MCC), i.e., 2 N. However, MCC with Short-Circuit (SC-MCC) is recommended since most of the safety-critical applications are built on the high-level languages that use Short-Circuit evaluation property. Our goal is to demonstrate that, despite the added overhead, the SC-MCC coverage-based test cases have a high error-detection probability compared to that of MC/DC. In this work, we have considered the CBMC tool to generate both the SC-MCC and MC/DC test cases for 80 RERS benchmark programs. Then, by optimizing the traditional Mutation Testing (using the GCOV tool), we computed the Mutation Score (%) to assess the quality of the generated test cases. As per the Mutation analysis, the proposed SC-MCC outperformed MC/DC for over 75% of the 80 RERS programs considered. Additionally, as per the Execution time analysis, the average total time taken to evaluate the MC/DC part of the proposed framework is 3065.98 s, whereas SC-MCC framework evaluation took 2167.70 s. This proves the efficiency of the proposed (SC-MCC) work over the traditional criterion (MC/DC) based work. [Display omitted] • Automated the test case generation based on SC-MCC using BMC. • Performed Mutation Testing to validate the quality of the generated test cases. • SC-MCC outperformed MC/DC for over 75% of the considered 80 RERS programs. • Proved that the generated SC-MCC test cases are more robust than that of MC/DC. • Recommends SC-MCC over MC/DC, especially in Safety-critical applications. [ABSTRACT FROM AUTHOR]

The cost of software testing could be reduced if faulty entities were identified prior to the testing phase, which is possible with software fault prediction (SFP). In most SFP models, machine learning (ML) methods are used, and one aspect of improving prediction accuracy with these methods is tuning their control parameters. However, parameter tuning has not been addressed properly in the field of software analytics, and the conventional methods (such as basic Differential Evolution, Random Search, and Grid Search) are either not up-to-date, or suffer from shortcomings, such as the inability to benefit from prior experience, or are overly expensive. This study aims to examine and propose parameter tuners, called DEPTs, based on different variants of Differential Evolution for SFP with the Swift-Finalize strategy (to reduce runtime), which in addition to being up-to-date, have overcome many of the challenges associated with common methods. An experimental framework was developed to compare DEPTs with three widely used parameter tuners, applied to four common data miners, on 10 open-source projects, and to evaluate the performance of DEPTs, we used eight performance measures. According to our results, the three tuners out of five DEPTs improved prediction accuracy in more than 70% of tuned cases, and occasionally, they exceeded benchmark methods by over 10% in case of G-measure. The DEPTs took reasonable amounts of time to tune parameters for SFP as well. [ABSTRACT FROM AUTHOR]

This study aims to develop a software for measuring the computed tomography (CT) number of multiple materials automatically and investigate the impact of tube voltage on the measured CT numbers. The software was specifically design to automatically measure CT number of multiple materials on images of an ACR 464 CT phantom (Gammex, Inc.). Automatic measurements were performed using the matching technique based on the centroids of the phantom and bone objects. The software was tested first on images of the phantom scanned using a GE Revolution EVO 128-slice with rotation variations from 1° to 10° to evaluate its accuracy against rotation. The software was then implemented on images of the phantom scanned with tube voltage variations of 80, 100, 120, and 140 kV. Results of automatic measurements were compared with manual measurements. Manual measurements were performed using a MicroDicom Viewer (MicroDicom Ltd, Sofia, Bulgaria). The results of the two methods were analysed using a paired t -test. The developed software is able to accurately measure the CT number of multiple materials from images reconstructed with variations of rotation and tube voltage. The results of automatic method are not significantly different from the results of manual measurements with a p -value of >0.05. This study indicated that there is a dependency between the CT number values and the tube voltage. Thus, it is recommended in the quality control (QC) program to measure the CT number of multiple materials using all tube voltages available on the CT machine. • Accuracy of CT numbers of multi-materials is the ACR phantom is important. • Automated measurement of CT numbers is more objective and observer independent. • Available automated method cannot measure CT numbers if the phantom is rotated. • The developed software successfully measures CT numbers in various rotations. • CT numbers of multi-materials depend on the tube voltage. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel bio-inspired tapered structure mimicking the hierarchical architecture of barnacle is designed. • The SEA and mean crushing force show a significant improvement as the number of substructures increases. • The mean crushing force reaches maximum value when the ratio of external to internal wall thickness is the lowest. • The theoretical model effectively predicts the mean crushing force of the proposed structure. This paper introduces a new type of energy-absorbing hierarchical tapered structure, mimicking the hierarchical architecture of barnacle. The proposed structures are designed by iteratively incorporating sub-tapered tubes at the junctions of primary ribs aiming to enhance the crashworthiness performance. The finite element models of the proposed structures are constructed in Abaqus software and validated using experimental testing. The effects of the geometrical parameters including the number of substructures and the external-to-internal wall thickness ratio on the energy absorption characteristics of the proposed structures are investigated. The results demonstrate that as the number of substructures increases, the specific energy absorption (SEA) and mean crushing force of the proposed design show a significant improvement. Specially, the SEA of the proposed structures with four substructures can reach 32.78 kJ/kg, which is 85.8 % higher than the conventional tapered tube. Additionally, decreasing the ratio of external to internal wall thickness leads to enhanced performance. After optimizing the wall thickness ratio, the maximum SEA can reach 40.87 kJ/kg, which is 26.0 % higher than that before optimization. To complement the findings, a theoretical study is presented, which exhibits excellent agreement with the numerical results, further validating the effectiveness of the proposed design. This study highlights the potential of incorporating hierarchical and tapered features into tapered structures, offering promising prospects for advancements in energy absorption technology across diverse industries. [ABSTRACT FROM AUTHOR]

In this paper, 10 corrugated-web partially encased composite (PEC) column specimens were designed, and push-out tests were performed. Taking the corrugated angle and number of studs as variables, the bond-slip mechanism and interface shear transfer of the specimens were analyzed. The results showed that the failure modes of the specimens can be divided into bond-anchoring, bond-splitting, and concrete-crushing failures. The load-slip curves of the specimens mainly showed the rising, falling, and residual stages. The influence of the corrugated angle and number of studs was studied. It was found that the greater the number of studs, the more evident the improvement in the characteristic bond strength. Characteristic load calculation formulas for the studs and physical bonding strength were obtained. A bond-slip constitutive model of the interface of the corrugated-web PEC columns, considering the influence of the corrugated angle and stud, was proposed. The ABAQUS finite element software was used to analyze the entire testing process and verify the reliability of the proposed interface bond-slip constitutive and modeling method, which could provide a basis for relevant theoretical calculations and research. • The failure mode and load-slip curves of the specimens were obtained by the test. • The entire process of interfacial shear transfer was analyzed. • The calculation formula of characteristic load and bonding strength were obtained. • The bond-slip constitutive model of corrugated-web PEC column was proposed. • The reliability of the proposed model and method was proved by numerical simulation. [ABSTRACT FROM AUTHOR]

The article presents the torchosr module – a Python package compatible with PyTorch library – offering functionality and models dedicated to Open Set Recognition in Deep Neural Networks. Included software offers two frequently used base recognition methods in the field and a set of functions for handling datasets, enabling the generation of derived datasets, where some classes are considered unknown and used only in the testing process. Code base is enhanced with a set of helper functions, facilitating model validation process. The main goal of the proposal is to simplify and promote the correct experimental evaluation, where experiments are carried out on a large number of derivative sets with various Openness , related to the cardinality of known and unknown classes, and class-to-category assignments. The authors hope that methods available in the package will become a source of a correct and open-source implementation of the relevant baseline and state-of-the-art solutions in the domain. [ABSTRACT FROM AUTHOR]

• The matt black coated aluminium sheet is covered above the cooking pot, to reduce the top heat losses in box-type solar cooker. • Box-type solar cooker assisted with heat storage material are in need of additional reflector. • Ideal time is utilized to store the heat in portable marble pieces for evening cooking in box-type solar cooker. • Portable heat storage material opted instead of integrating inside a box-type solar cooker. The thermal performance of the current box-type solar cooker is limited, and no provision for evening cooking, which could increase its dependability and attract more consumers. The thermal performance and evening cooking capabilities can be enhanced by employing the waste marble pieces as integrated or portable heat storage material. Also, suggested using a matt black coated aluminium sheet placed additionally below the glass cover to reduce the top heat losses. In this work, two arrangements were proposed: (I) a cooking load with heat storage but no aluminum sheet, and (II) a cooking load with both aluminum sheet and heat storage. The scope of improvement is evaluated using the COMSOL Multiphysics 6.0 software tool and experimental testing conducted in an outdoor environment. The cooking times for arrangements I and II are evaluated experimentally as 154–155 min and 175–176 min respectively, corresponding cooking power are measured as 56.62 W and 48.21 W, respectively and the corresponding thermal efficiencies are 25.79 % and 31.19 %, respectively. The optimal time for heating various weights of marble pieces is investigated using an aluminum sheet cover since the thermal performance and temperature availability till late evening are relatively low. The proposed solar cooker has a payback period of 1.24 years. It is concluded that installing a single solar cooker for two members of a family reduces a total of 148.3 kg of carbon dioxide annually. [ABSTRACT FROM AUTHOR]

Heterocyclic compounds have been shown to be potential chemotherapeutic agents, especially the benzimidazole derivatives studied in this work. The ultimate goal in the search for biologically active and effective molecules is to commercialize a product whose stability must be reliable. Therefore, in the development of drugs, forced degradation experiments are performed under the environmental conditions to which they are subjected during transportation and storage to ensure quality and safety before marketing. Hydrolytic, thermal, photolytic, and degradation in the presence of hydrogen peroxide are experimental stress tests to which the newly synthesized compounds were subjected to gain insight into the degradation pathways of the analytes. Degradation of two benzimidazole derivatives was observed under all applied conditions while the major impact showed photolysis with ten and four degradation products, respectively. In total, eighteen major degradation products were detected and identified using high-resolution mass spectrometry. Computer models in the TEST program were applied to the proposed structures to evaluate the bioaccumulation factor, toxicity, and mutagenicity of the analyzed compounds, while density functional theory analysis (DFT) revealed factors affecting the vulnerability of systems towards exceeding acidic/basic conditions and H 2 O 2. [Display omitted] • Stability of benzimidazo[1,2- a ]quinolines was determined by forced degradation tests. • Degradation was observed in all applied experiments; photolysis the most pronounced. • UHPLC-QTOF was used to define degradation pathways of benzimidazole derivatives. • Computational models were used for the toxicity evaluation. • DFT calculations characterized the stability of N–C bonds of the aniline environment. [ABSTRACT FROM AUTHOR]

Regular language inference, initiated by Angluin, has many developments, including applications in software engineering and testing. However, the capability of finite automata to model the system data is quite limited and, in many cases, extended finite state machine formalisms, that combine the system control with data structures, are used instead. The application of Angluin-style inference algorithms to extended state machines would involve constructing a minimal deterministic extended finite state machine consistent with a deterministic 3-valued deterministic finite automaton. In addition to the usual, accepting and rejecting, states of finite automaton, a 3-valued deterministic finite automaton may have "don't care" states; the sequences of inputs that reach such states may be considered as accepted or rejected, as is convenient. The aforementioned construction reduces to finding a minimal deterministic finite automaton consistent with a 3-valued deterministic finite automaton, that preserves the deterministic nature of the extended model that also handles the data structure associated with it. This paper investigates fundamental properties of extended finite state machines in relation to Angluin's language inference problem and provides an inference algorithm for such models. [ABSTRACT FROM AUTHOR]

• The developed automatic calibration tool enables the calibration of multiple parameters simultaneously. • The improved DLL for the Storm Water Management Model decreases the time of calibration. • Levenberg-Marquardt optimization algorithm using limited minimal step decreases optimization time. The objective of this paper is to introduce an enhanced automatic calibration toolbox for the Storm Water Management Model (SWMM5), one of the most widely used softwares for simulating urban stormwater systems. Within the process of accurately modelling urban runoff and drainage, proper calibration is the most time-intensive sub-task. Thus, a toolbox is developed that eliminates the need to manually re-read input files for each parameter change made during calibration. The Excel-based toolbox written in Visual Basic for Applications (VBA) makes use of a Dynamic-link library (DLL), which has been extended with several new functions. The functionality of the automatic calibration toolbox has been increased by adding new groundwater-related parameters to the DLL. In this article the authors successfully tested automatic calibration toolbox performance test cases, based on example input files provided by SWMM5 developers. The first test case was chosen to demonstrate the program's ability to calibrate using measurements from the conduits, and the second one to demonstrate the performance of using measurements from nodes. [ABSTRACT FROM AUTHOR]

Fuzzing refers to a collection of software testing methodologies that have been specifically developed to automatically detect implementation bugs, and is utilized by developers as a means of evaluating the security and stability of applications. Unfortunately, hacker can also exploit fuzzing techniques to crash bugs, and analyze zero-day vulnerabilities from it to carry out cyber attacks. As a result, researchers make use of anti-fuzzing technologies to slow down and frustrate these malicious aggressors. However, the main aim of these methods is to design a source-level defense strategy, which means this work requires not only the source codes but also considering the programming language. This restricts users from protecting the released binary executable they do not own from malicious analysis. In this paper, we perform a systematic analysis of software protection techniques and design a novel s elf-injection based a nti- f uzzing te chniques, called SAFTE. Different from the former research, SAFTE proposes a new way to hide the feedback or crash-related information by the means of dynamic loading and execution. First, a memory block is allocated, followed by the duplication of the image that is stored in the.data into the allocated local memory. Second, the memory is altered to enable execution permissions, thereby facilitating the execution of the image that is stored in the memory. As a consequence of this approach, let the operational and procedural status of the program is hidden, thereby precluding the fuzzer from obtaining accurate feedback or crash-related information. Therefore, it makes the fuzzer completely useless. Our evaluation on popular fuzzers demonstrates that SAFTE is capable of obviating the majority of extant fuzzers, and exhibits higher efficacy in comparison to the most advanced anti-fuzzing techniques presently available. Meanwhile, the size of the program is better than the other methods(size:18048KB,average run time per run:0.056ms), which was modified by SATFE only increases no more than 85% and the running time only increases 30%. [ABSTRACT FROM AUTHOR]

Though Deep Neural Networks (DNNs) have been widely deployed and achieved great success in many domains, they have severe safety and reliability concerns. To provide testing evidence for DNNs' reliable behaviors, various coverage testing techniques inspired by traditional software testing have been proposed. However, the coverage criteria in these techniques are either not fine enough to capture subtle behaviors of DNNs, or too time-consuming to be applied on large-scale DNNs. In this paper, we propose a coverage testing framework named HashC, which makes mainstream coverage criteria (e.g., NC and KMNC) much finer. Meanwhile, HashC reduces the time complexity of combinatorial coverage testing from polynomial time to linear time. We also develop the corresponding test sample selection method. Our experiments show that, (1) the existing mainstream coverage criteria are becoming finer after being equipped with HashC, (2) HashC greatly accelerates combinatorial coverage testing and can handle the testing of large-scale DNNs. [ABSTRACT FROM AUTHOR]

The core/shell magnetic covalent organic framework doped with gold nanoparticles (MCOF-AuNPs) was prepared by a facile two-step in situ synthesis strategy to achieve high emission. The fluorescence emission was enhanced and overcame the aggregation-induced quenching of COF after the introduction of Fe 3 O 4 and AuNPs. Interestingly, the emission can be quenched by Fe3+ ions. MCOF-AuNPs combined with a specific aptamer (apt-MCOF-AuNPs) can capture Salmonella typhimurium selectively, and Fe3+-induced fluorescence quenching was inhibited based on the competitive binding of Fe3+ ions. A fluorescent assay strategy was constructed with excellent specificity and sensitivity. The detection limit is as low as 4 CFU/mL within 33 min. Furthermore, we developed smartphone-based software as an image reader and analyzer to determine S. typhimurium by capturing the change in fluorescence lightness, which can be assisted for point-of-care testing. Collectively, this innovative design showed a promising on-site detection approach for S. typhimurium. • A fluorescence sensor for S. typhimurium using magnetic COF doped with AuNPs. • A dual-functional high fluorescence emissive biosensor. • The whole detection procedure was achieved within 33 min, and the LOD is 4 CFU/mL. • The development of APP based on the HSV model to assay fluorescence lightness. [ABSTRACT FROM AUTHOR]

The need for appropriate standards to calibrate ion arrival times in traveling wave ion mobility (TWIM) remains an issue for collision cross section (CCS) measurements, particularly in the case of multiply charged anions due to the scarcity of calibrants in the negative ion mode. In order to circumvent constraints raised for standards in the conventional power law calibration, the new approach recently implemented in the IMSCal software (Anal. Chem. 93 (2021) 3542–3550) has been evaluated here to derive CCS of multiply charged anions measured by TWIM. The mathematical model developed in IMSCal to describe ion motion in the TWIM cell was trained with different combinations of phosphoric acid clusters and deprotonated polyalanine standards and performance of so-obtained calibrations was evaluated for multiply deprotonated oligothymidine 10mers used as control analytes. Although optimal composition of the calibrant set could not be fully rationalized, one mandatory condition for best CCS accuracy is to include standards of different charge states to properly model the effects of radial distribution of ions in the TWIM cell. Further improvement of calibration robustness requires that one of these charge states equals that of the analytes to account for the effects of velocity relaxation also incorporated in the IMSCal model. Doing so, experimental CCS values could be readily obtained with relative error below ±5% for anions of charge state up to 6–. [Display omitted] • The IMSCal software was tested for determine CCS of multiply charged anions. • High CCS accuracy could be achieved with low constraints on standards. • Selected combination of charge states advantageously replaces large series of calibrants. • CCS could be determined for oligothymidines with up to 6 deprotonated units. [ABSTRACT FROM AUTHOR]

• Vulnerability assessment of preliminary spacecraft designs. • Implementation of fully probabilistic approach using the concept of vulnerable zones. • Use of Boolean geometry operations to model internal components and debris ejecta interactions. The space environment around the Earth is populated by more than 130 million objects of 1 mm in size and larger, and future predictions shows that this amount is destined to increase, even if mitigation measures are implemented at a far better rate than today. These objects can hit and damage a spacecraft or its components. It is thus necessary to assess the risk level for a satellite during its mission lifetime. Few software packages perform this analysis, and most of them employ time-consuming ray-tracing methodology, where particles are randomly sampled from relevant distributions. In addition, they tend not to consider the risk associated with the secondary debris clouds. The paper presents the development of a vulnerability assessment model, which relies on a fully statistical procedure: the debris fluxes are directly used combining them with the concept of vulnerable zone, avoiding the random sampling the debris fluxes. A novel methodology is presented to predict damage on internal components. It models the interaction between the components and the secondary debris cloud through basic geometrical operations, considering mutual shielding and shadowing between internal components. The methodologies are tested against state-of-the-art software for relevant test cases, comparing results on external structures and internal components. [ABSTRACT FROM AUTHOR]

Introduction: Predicting outcome after cardiac arrest is challenging. We previously tested group-based trajectory modeling (GBTM) for prognostication based on baseline characteristics and quantitative electroencephalographic (EEG) trajectories. Here, we describe implementation of this method in a freely available software package and test its performance against alternative options.Methods: We included comatose patients admitted to a single center after resuscitation from cardiac arrest from April 2010 to April 2019 who underwent ≥6 h of EEG monitoring. We abstracted clinical information from our prospective registry and summarized suppression ratio in 48 hourly epochs. We tested three classes of longitudinal models: frequentist, statistically based GBTMs; non-parametric (i.e. machine learning) k-means models; and Bayesian regression. Our primary outcome of interest was discharge CPC 1-3 (vs unconsciousness or death). We compared sensitivity for detecting poor outcome at a false positive rate (FPR) <1%.Results: Of 1,010 included subjects, 250 (25%) were awake and alive at hospital discharge. GBTM and k-means derived trajectories, group sizes and group-specific outcomes were comparable. Conditional on an FPR < 1%, GBTMs yielded optimal sensitivity (38%) over 48 h. More sensitive methods had 2-3 % FPRs.Conclusion: We explored fundamentally different tools for patient-level predictions based on longitudinal and time-invariant patient data. Of the evaluated methods, GBTM resulted in optimal sensitivity while maintaining a false positive rate <1%. The provided code and software of this method provides an easy-to-use implementation for outcome prediction based on GBTMs. [ABSTRACT FROM AUTHOR]

Covering arrays are generalizations of orthogonal arrays that have been widely studied and are used in software testing. The probabilistic method has been employed to derive upper bounds on the sizes of minimum covering arrays and give asymptotic upper bounds that are logarithmic on the number of columns of the array. This corresponds to test suites with a desired level of coverage of the parameter space where we guarantee the number of test cases is logarithmic on the number of parameters of the system. In this paper, we study variable strength covering arrays, a generalization of covering arrays that uses a hypergraph to specify the sets of columns where coverage is required; (standard) covering arrays are the special case where coverage is required for all sets of columns of a fixed size t , its strength. We use the probabilistic method to obtain upper bounds on the number of rows of a variable strength covering array, given in terms of parameters of the hypergraph. We then compare this upper bound with another one given by a density-based greedy algorithm on different types of hypergraph such as t -designs, cyclic consecutive hypergraphs, planar triangulation hypergraphs, and a more specific hypergraph given by a clique of higher strength on top of a "base strength". The conclusions are dependent on the class of hypergraph, and we discuss specific characteristics of the hypergraphs which are more amenable to using different versions of the Lovász local lemma. [ABSTRACT FROM AUTHOR]

Ensuring traceability of both field experimental data and laboratory sampling data for a reproducible research remains a challenge nowadays. Between the time when geolocalized specimens are taken, and the time the resulting data ends up in analysis published within a study, many manual operations take place that are prone to generate errors. The French nodes of the European Long-Term Socio-Ecological Research Infrastructure called "Zones Ateliers" propose a solution as generic as possible to this problem of monitoring of the samples and the data associated with them. Compared to existing solutions such as Laboratory Information Management Systems, we target a robust solution for labelling adapted to outdoor working conditions, with the management of storages and movements of samples. We designed and realized a software package tested from end to end, using open source licenses and cheap hardware, including small printers (mobile or not) and Raspberry Pis. This system provides sufficient flexibility so that it can facilitate working with a wide variety of existing protocols. One of the most interesting feature consists to record all contextual data associated with the samples, which constitute important parameters of the subsequent analyses. Furthermore, not only traceability is thus guaranteed, but also we can expect a reduced handling times and an increased streamlining of the storage of samples that will improve the return on investment. [ABSTRACT FROM AUTHOR]

Software test is an important activity in life cycle of software development. If quality of generated test cases is high, number of detected errors before system dissemination would be significant and costs will be decreased. In recent years, different methods have been presented for test cases generation. One of the methods of test cases generation is using UML (unified modeling language) diagrams. Using UML diagrams for test cases generation and applying them in first stages of software development, leads to decrease in costs and efforts. In this paper, first some methods of test cases generation from Communication diagram, Sequence diagram, Activity diagram, State diagram, Class diagram and combination of some diagrams have been explained. Next, Communication diagram, Sequence diagram, Use Case diagram, Activity diagram, State diagram and Class diagram in test cases generation for different part of a system have been compared. Finally, UML diagrams have been applied for case study on depression on internet addiction estimation. • Software test is an important activity in life cycle of software development. • Different methods have been presented for test cases generation. • One of the methods of test cases generation is using UML diagrams. • Case study on depression on internet addiction estimation. [ABSTRACT FROM AUTHOR]

Advanced diagnostic algorithms and high-fidelity simulation models improve the accuracy of model-based gas path fault diagnosis for gas turbines (GTs). But simultaneously, it becomes difficult in real-time applications due to the increased calculation amount. To improve the diagnosis speed, this study adopts the surrogate method to realize the real-time gas path fault diagnosis of GTs under transient operating conditions. First, the component level model (CLM) is built and verified. Subsequently, the surrogate model is established by combining the artificial neural network (ANN) and the necessary physical model. The constructed surrogate model can almost entirely reproduce the simulation results of CLM under the whole operation conditions. Finally, the real-time fault diagnosis system combines the surrogate model and the unscented Kalman filter (UKF). The results show that the surrogate model-based fault diagnosis system has the same accuracy as the CLM-based system. At the same time, the calculation speed is increased by nearly 50 times, which meets the real-time requirements of fault diagnosis. • The gas turbine model is validated using commercial software and test data. • The surrogate model combines the artificial neural network and the necessary physical model. • Fault diagnosis is successfully implemented under transient operating conditions. • The proposed method can increase the fault diagnosis speed by nearly 50 times. [ABSTRACT FROM AUTHOR]

• A dosage optimization model for ozone-UV-chlorine disinfection was developed. • Enhancement coefficients were introduced to quantify the synergistic effects. • Software was developed to simulate and optimize synergistic disinfection process. • Synergistic disinfection with optimal dosage and minimized cost can be achieved. The ozone-ultraviolet (UV)-chlorine process is a highly effective method of disinfection in water reuse system, but currently still lacks precise quantification and accurate control. It is difficult to determine the dosage of each disinfectant because of the complex interactions that occur between disinfection units and the complicated mathematical calculation required. In this study, we proposed a dosage optimization model for ozone-UV-chlorine synergistic disinfection process. The model was able to identify the cost-effective doses of the disinfectants under the constraints of microbial inactivation, decolorization, and residual chlorine retention requirements. Specifically, the simulation of microbial inactivation rates during synergistic disinfection process was accomplished through quantification of the synergistic effects between disinfection units and the introduction of enhancement coefficients. In order to solve this optimization model rapidly and automatically, a MATLAB-based software program with graphical user interface was developed. This software consisted of calibration unit, prediction unit, assessment unit, and optimization unit, and was able to simulate synergistic ozone-UV-chlorine process and identify the optimal dose of ozone, UV, and chlorine. Validation experiments revealed good agreements between the experimental data and the results calculated by the developed software. The developed software is believed to help the water reclamation plants improve disinfection efficiency and reduce the operational costs of synergistic disinfection processes. [Display omitted] [ABSTRACT FROM AUTHOR]

While checking functional correctness for automated driving is often achieved through vast amounts of automated and manual field testing, automating specification verification is essential for developing and releasing fully self-driving vehicles. This paper presents an automatic bounded model checking approach for functional specifications over longitudinal vehicle controller implementations. The proposed method checks the actual embedded program, rather than an extracted abstract model. The specification is converted into a monitor that is interleaved with the execution of the program over a finite time horizon in closed-loop simulation. A decomposition is proposed to tackle the verification complexity. This allows verifying the program for whole parameter sets using a software model checker as opposed to testing only individual samples. The approach is capable of identifying functional flaws in several exemplary longitudinal controllers with variable complexity. • Platform-independent verification of adaptive cruise controller implementations. • Verifying requirements for the closed-loop behavior using bounded model checking. • Utilizing specification decomposition to reduce verification complexity. [ABSTRACT FROM AUTHOR]

Renewable energy has attained enormous attention in recent years due to the exhaustion of many energy resources, and the pollution caused by fossil fuels. However, the adoption of renewable energy sources (RESs) is a complicated process influenced by multifarious factors. This study aims to investigate factors influencing the adoption of RESs by the Palestinian industrial and commercial sectors and their effect of this adoption on sustainable performance, besides examining if the government plays a role in moderating the relationship between the adoption of RESs and such sustainable performance. To this end, a quantitative method was used to collect data through questionnaires from 100 top managers in the Palestinian commercial and industrial sectors. The data analysis was conducted using the Smart PLS software to test the formulated hypotheses. The findings support the positive relationship between the adoption of RESs and sustainable performance. There is also a positive relationship between the adoption of RESs and the government's role. However, the relationship between the government's role and sustainable performance is not established, but the government's role is found to be a moderator between adopting RESs and sustainable performance. [ABSTRACT FROM AUTHOR]

Legacy protection schemes face numerous challenges with the emergence of microgrids. Due to the complex controls, the fault responses in microgrids differ from conventional behaviour and vary with the operation mode. In this paper, a differential protection scheme based on fundamental frequency superimposed current phasors is proposed for microgrid feeders. The phasors are extracted using dq components instead of conventional Fourier algorithms. The performance of proposed method is tested for different fault scenarios by carrying out simulations in MATLAB/SIMULINK software. The results confirm that internal faults are detected in a few milliseconds. At the same time, the scheme remains insensitive to external faults with CT saturation and other system disturbances. The proposed scheme is unaffected by the microgrid mode of operation, direction of power flow and DG type. [ABSTRACT FROM AUTHOR]

This paper concerns the systematic testing of robotic control software based on state-based models. We focus on cyclic systems that typically receive inputs (values from sensors), perform computations, produce outputs (sent to actuators) and possibly change state. We provide a testing theory for such cyclic systems where time can be represented and probabilities are used to quantify non-deterministic choices, making it possible to model probabilistic algorithms. In addition, refusals , the inability of a system to perform a set of actions, are taken into account. We consider several possible testing scenarios. For example, a tester might only be able to passively observe a sequence of events and so cannot check probabilities, while in another scenario a tester might be able to repeatedly apply a test case and so estimate the probabilities of sequences of events. These different testing scenarios lead to a range of implementation relations (notions of correctness). As a consequence, this paper provides formal definitions of implementation relations that can form the basis of sound automated testing in a range of testing scenarios. We also validate the implementation relations by showing how observers can be used to provide an alternative but equivalent characterisation. • Systematic testing of robotic control software based on state-based models. • Motivated by the RoboChart and RoboSim notations for modelling robotic software. • Testing theory for cyclic systems with discrete time, probabilities and refusals. • Defining 15 implementation relations and analysing the relations among them. • Alternative characterisations of these implementation relations using observers. [ABSTRACT FROM AUTHOR]

Software testing is the most used technique for quality assurance in industry. However, in computer science education software testing is still treated as a second-class citizen and students are unable to test their software well enough. One reason for this is that teaching the subject of software testing is difficult as it is a complex intellectual activity for which students need to allocate multiple cognitive resources at the same time. A myriad of primary and secondary studies have tried to solve this problem in education, however still with very limited results. Before we can design interventions to improve our pedagogical approaches, we need to gain more in-depth understanding and recognition of sensemaking as it is happening when students design test cases. An initial exploratory study identified four different sensemaking approaches used by students while creating test models. In this paper we present a follow-up study with 50 students from a large university in Spain. The used methodology was based on the previous study with the improvements that originated from its evaluation. We asked the participants to create a test model based on a description of a test problem using a specialized web-based tool for modeling test cases. We measured how well these models fit the test problem, the sensemaking process that students went through when creating the models, and the students' perception of the modeling task. The participants received no compensation for their efforts, and we scheduled the experiment during a regular class. Apart from the created models and their metadata, we also collected recordings of the students' computer screens made during the experiment and used a questionnaire to study their perspectives on the assignment. All the collected textual, graphical, and video data was analyzed using an iterative inductive analysis process to allow new information about the different sensemaking approaches to emerge. We gained better insights into the sensemaking processes of students while modeling test cases for a problem. The results enabled us to refine our previous findings, and we identified new sensemaking approaches. Based on these results, we can further investigate ways to influence the sensemaking process in education, the possible misconceptions that have a negative influence on it, and the desired mental model we want our students to have to design test cases. [ABSTRACT FROM AUTHOR]

• Generated suitability maps for LID allocation was evaluated successfully. • 49% of the catchment area was identified as high potential for implementing LID. • Maximum suitable location for LID implementation ranged between 10 and 47% in Watermaelbeek. • Maximum flow and total volume reduced by 21 and 8% for the most cost-optimized scenario. Nowadays there is a need to overcome the effects caused by rapid urbanization with more innovative methods. Recently, source control approaches, known as Low Impact Development (LID), are being used by urban planners to cope with water-related problems due to their cost-effectiveness and reliability. To do this, allocation of LID techniques in most suitable locations is done by introducing a new modeling tool called LID locator to the WetSpa-Urban software package and tested in the Watermaelbeek catchment situated in the Brussels capital region. In the first step, almost half of the catchment is eliminated from the implementation of LIDs by considering only pixels with high runoff. Also, by considering the sewer network behavior, the total area of high potential pixels for implementing LID is reduced to the range of 37% and 10% of the entire area of the catchment for different scenarios. In the next step, the selected area is further eliminated by use of suitable location algorithm based on size and other installation limitation of each type of LID. Then, the results are used as an input for the newly developed cost-optimization tool. In the end, the best scenario (10-year design storm with the current state of sewer network) is selected based on their performance in surface runoff volume reduction and the total cost. As a result, maximum flow and total volume at the outlet is reduced by 21 and 8% for the most cost-optimized scenario in January and February 2015. In addition to considering sewer network performance, land characteristics and LID installation limits for LID implementation, producing maps indicating the most cost-efficient locations and combinations for LIDs and visualizing them through the GUI make this tool a user-friendly product. This tool was applied to this case study in Brussels however it is applicable for other urban catchments. [ABSTRACT FROM AUTHOR]

With the rapid development of quantum computer, the encryption schemes in low key space are facing a huge security threat. The chaotic-based image encryption schemes use the initial values of the systems as the key, so the key spaces are often unchanged, which provide a way for the cracker to perform an exhaustive attack. This paper proposes an image encryption scheme based on generalized Mandelbrot-Julia (M-J) set. The key space of the scheme is not only large, but also dynamically changeable. To verify the feasibility of the generalized M-J set in the encryption scheme we use the simplest two rounds XOR encryption algorithm. We get the key by using environmental noise and SHA-512. The use of one-time keys not only improves the security of the algorithm, but also weakens the difficulty of transmitting many secret keys. Simulation results show that the key space of the our scheme can reach to 23250, which is far more than the most schemes. In order to verify the security of the encryption scheme, we have made corresponding security analysis for many attack methods. The results show that all the performance indexes satisfy the image encryption secure performance test standards. Finally, we tested the randomness of the generalized M-J set using the NIST randomness test software. Various analyses show that the encryption scheme is safe, and the generalized M-J set is an excellent system that can be applied in cryptography. [ABSTRACT FROM AUTHOR]

Detecting workflow difference is meaningful for many applications, e.g., in-vehicle system testing. However, current workflow difference detection methods stress on structural differences while ignoring the behavioral aspects of the workflow models. Due to the large number of possible behaviors for a workflow model, it is challenging to detect the behavioral difference. To address this problem, this paper introduces the idea of basis path testing from the software testing field, and presents an efficient method for detecting the workflow difference in terms of their behaviors. First, we compute the cyclomatic complexity according to the number of nodes and arcs in the workflow model. Then, based on the cyclomatic complexity we design an algorithm that can retrieve the basis paths from a tree structure converted from the workflow model. At last, the Kuhn–Munkres (KM) algorithm is used to map the independent paths from two workflow models and generate the optimal mapping that the overall distance is the minimum. The experimental evaluation shows that our proposed method has been proved feasible in terms of both efficiency and effectiveness. [ABSTRACT FROM AUTHOR]

Abstract Models are extensively used in many areas of software engineering to represent the behaviour of software systems at different levels of abstraction. Because of the involvement of different stakeholders in constructing these models and their independent evolution, inconsistencies might occur between the models. It is thus crucial to detect these inconsistencies at early phases of the software development process, and especially as soon as refined models deviate from their abstract counterparts. In this article, we introduce a containment checking approach to verify whether a certain low-level behaviour model, typically created by refining and enhancing a high-level model, still is consistent with the specification provided in its high-level counterpart. We interpret the containment checking problem as a model checking problem, which has not received special treatment in the literature so far. Because the containment checking is based on model checking, it requires both formal consistency constraints and specifications of these models. Unfortunately, creating formal consistency constraints and specifications is currently done manually, and therefore, labour-intensive and error prone. To alleviate this issue, we define and develop a fully automated transformation of behaviour models into formal specifications and properties. The generated formal specifications and properties can directly be used by existing model checkers for detecting any discrepancy between the input models and yield corresponding counterexamples. Moreover, our approach can provide the developers more informative and comprehensive feedback regarding the inconsistency issues, and therefore, help them to efficiently identify and resolve the problems. The evaluation of various scenarios from industrial case studies demonstrates that the proposed approach efficiently translates the behaviour models into formal specifications and properties. Highlights • Containment checking of software behaviour models at different abstraction levels. • Automated transformation of models into LTL formulas and formal SMV descriptions. • Counterexample interpretation for resolving the inconsistencies between models. • Applicability and feasibility of the approach for realistically sized models. • Performance evaluation in a typical developer's working environment. [ABSTRACT FROM AUTHOR]

Highlights • Use of a low cost hardware for the implementation of the AdSPAR in hardware in the loop (HIL) real time digital simulations. • Identification of misoperations that could not be identified when just the software tests were implemented. • Tests of oscillograms of actual events. It includes voltage transformer harmonic attenuation and distortion. • The new adaptive protection algorithm was coded in a low-cost commercial hardware, emulating the new relay prototype. • Robustness of proposed algorithm based on low-order voltage harmonic content was proved. Abstract This study describes the hardware implementation of a fast adaptive single-phase auto reclosing algorithm based on voltage harmonic content measurement. The proposed algorithm classifies the fault type, preventing reclosing onto permanent fault, and identifies the arc extinction instant, adjusting dead-time to implement reclosing with granted success. The hardware was connected to the Real Time Digital Simulator (RTDS) to perform tests in hardware-in-the-loop (HIL) with a protective relay. The studied system is based on a 500 kV transmission line of the Brazilian electrical power system and eventually real case oscillograms were tested. The algorithm performance was validated with previous software development. However, in the present document we highlight the importance to implement hardware test, as operational limits can only be identified in this last testing stage. Robustness of proposed algorithm based on low-order voltage harmonic content was proved with oscillograms' tests. [ABSTRACT FROM AUTHOR]

• A custom made measurement system for on-line testing of electromechanical relays. • Measurement of essential magnetic and contact properties in less than two seconds. • Measurement algorithms based on simultaneous waveform generation and acquisition. • The comprehensive relay test software application. An automatic measurement system has been developed for high-speed testing of the most important magnetic and contact properties for elementary monostable and bistable miniature electromechanical relays. The system design is based on the virtual instrumentation approach, which is a combination of software and hardware. The comprehensive test application was developed using the LabVIEW graphical programming environment, while the used hardware is based on commercial measurement equipment and a custom developed device. The presented measurement methods are based on simultaneous generation and acquisition of analog and digital waveforms with the high-speed data acquisition device. The implemented automatic relay measurement system was validated metrologically and tested successfully with all supported relay types. The results show that the developed system is capable of performing accurate measurements of the coil resistance, contact resistance, time parameters, and operate/release values in less than two seconds. [ABSTRACT FROM AUTHOR]

• A novel involute gear coordinate system is introduced. • General definitions and mathematical calculation methods are provided. • They allow 3D coordinates to be evaluated in conventional evaluation cross sections. • The definitions and formulas presented complete existing standards and guidelines. • They provide clear instructions required for handling a gear as a full 3D object. The definition of 3D workpiece coordinates for cylindrical involute gears, together with their formal relation to conventional cross sections, are prerequisites for an unambiguous and thus reliable evaluation of 3D measurement data. Both will be described in this article, as no corresponding information is currently available in national or international standards and guidelines. The definitions and calculation methods presented here are part of reference algorithms used by the Physikalisch-Technische Bundesanstalt (PTB), the national metrology institute of Germany, to certify gear evaluation software. [ABSTRACT FROM AUTHOR]

Highlights • A new atomic class-association rule mining is built for software defect prediction. • Redundant pruning is done using the relation between metrics in feature atomic rules. • The algorithm is used to 15 commonly-available datasets from the MDP and PROMISE repository. • The comparative experiments are performed in other well-known classifiers. Abstract To ensure the rational allocation of software testing resources and reduce costs, software defect prediction has drawn notable attention to many “white-box” and “black-box” classification algorithms. Although there have been lots of studies on using software product metrics to identify defect-prone modules, defect prediction algorithms are still worth exploring. For instance, it is not easy to directly implement the Apriori algorithm to classify defect-prone modules across a skewed dataset. Therefore, we propose a novel supervised approach for software defect prediction based on atomic class-association rule mining (ACAR). It holds the characteristics of only one feature of the antecedent and a unique class label of the consequent, which is a specific kind of association rules that explores the relationship between attributes and categories. It holds the characteristics of only one feature of the antecedent and a unique class label of the consequent, which is a specific kind of association rules that explores the relationship between attributes and categories. Such association patterns can provide meaningful knowledge that can be easily understood by software engineers. A new software defect prediction model infrastructure based on association rules is employed to improve the prediction of defect-prone modules, which is divided into data preprocessing, rule model building and performance evaluation. Moreover, ACAR can achieve a satisfactory classification performance compared with other seven benchmark learners (the extension of classification based on associations (CBA2), Support Vector Machine, Naive Bayesian, Decision Tree, OneR, K-nearest Neighbors and RIPPER) on NASA MDP and PROMISE datasets. In light of software defect associative prediction, a comparative experiment between ACAR and CBA2 is discussed in details. It is demonstrated that ACAR is better than CBA2 in terms of AUC, G-mean, Balance, and understandability. In addition, the average AUC of ACAR is increased by 2.9% compared with CBA2, which can reach 81.1%. [ABSTRACT FROM AUTHOR]

Mutation is a systematic technique to create variants of a seed artefact by means of mutation operators. It has many applications in computer science, like software testing, automatic exercise generation and design space exploration. Typically, mutation frameworks are developed ad-hoc by implementing mutation operators and their application strategies from scratch, using general-purpose programming languages. However, this is costly and error-prone. To improve this situation, we propose Wodel : a domain-specific language and tool for model-based mutation that is independent of the domain meta-model. Wodel enables the rapid development and application of model mutations. It provides built-in advanced functionalities like automatic generation of seed models, and static and dynamic metrics of operator coverage and applicability. It offers extension points, e.g., to post-process mutants and describe domain-specific equivalence criteria. As an example, we illustrate the usage of Wodel for the mutation of security policies, and present an empirical evaluation of its expressiveness. [ABSTRACT FROM AUTHOR]

Verification of functional and performance requirements in both government and commercial space programs is a challenging task. Nowadays, spacecraft can be regarded as complex systems, and demanding quality requirements have to be fulfilled. Verification activities are performed in different steps and by means of various test environments/spacecraft models. This paper presents a cross-model verification approach for space projects and shows its application to the Electrical Power Subsystem. Functional and performance requirements of such subsystem are verified on the spacecraft Engineering Model by reusing test cases and corresponding test scripts from the On-Board Software testing campaign. This can be achieved thanks to the above-mentioned cross-model verification approach. In particular, test cases can be conceived and implemented by means of an XML-based test procedure language, independently from the underlying test environment. [ABSTRACT FROM AUTHOR]

[Display omitted] • Quantum computers' noise and errors are exploitable resulting in security breaches. • Current stability and security approaches can provide a quantum security model. • The static analysis would be essential in ensuring security of quantum software. Quantum computing is no longer a promise of the future but a rapidly evolving reality. Advances in quantum hardware are making it possible to make tangible a computational reality that until now was only theoretical. The proof of this is that development languages and platforms are appearing that bring physical principles closer to developers, making it feasible to begin to propose, in different areas of society, solutions to problems that until now were unsolvable. However, security vulnerabilities are also emerging that could hinder the progress of quantum computing, as well as its transition and development in industry. For this reason, this article proposes a review of some of the first artefacts that are emerging in the field of quantum computing. From this analysis, we begin to identify possible security issues that could become potential vulnerabilities in the quantum software of tomorrow. Likewise, and following the experience in classical software development, the testing technique is analysed as a possible candidate for improving security in quantum software development. Following the principles of Quantum Software Engineering, we are aware of the lack of tools, techniques and knowledge necessary to guarantee the development of quantum software in the immediate future. Therefore, this article aims to offer some first clues on what would be a roadmap to guarantee secure quantum software development. [ABSTRACT FROM AUTHOR]