Test Scheduling Research Articles

Optimization of Software Test Scheduling under Development of Modular Software Systems

Software testing and debugging is a crucial part of the software development process since defective software not only incurs customer dissatisfaction but also might incur legal issues. However, the managers of a software development company cannot arbitrarily prolong their software debugging period due to their software testing budget and opportunity in the market. Accordingly, in order to propose an advantageous testing project, the managers should be aware of the influence of the testing project on cost, quality, and time to make the best decision. In this study, a new software reliability growth model (SRGM) with consideration of the testing staff’s learning effect is proposed to achieve better prediction. The methods of estimating the model’s parameters and the symmetric confidence intervals are also proposed in the study. Moreover, in the past, most of the SRGMs focused on a single software system. However, in practice, some software systems were developed using modular-based system engineering approaches. Therefore, traditional software testing work can be changed to multiple modular testing work in this scenario. Therefore, the manager can use this to dispatch multiple staff groups to perform the individual testing work simultaneously. The study proposes two mathematical programming models to handle the scheduling of modular testing work. Additionally, the design of a computerized decision support system is also proposed in the study for the application in practice.

Aligning staff schedules, testing, and isolation reduces the risk of COVID-19 outbreaks in carceral and other congregate settings: A simulation study.

COVID-19 outbreaks in congregate settings remain a serious threat to the health of disproportionately affected populations such as people experiencing incarceration or homelessness, the elderly, and essential workers. An individual-based model accounting for individual infectiousness over time, staff work schedules, and testing and isolation schedules was developed to simulate community transmission of SARS-CoV-2 to staff in a congregate facility and subsequent transmission within the facility that could cause an outbreak. Systematic testing strategies in which staff are tested on the first day of their workweek were found to prevent up to 16% more infections than testing strategies unrelated to staff schedules. Testing staff at the beginning of their workweek, implementing timely isolation following testing, limiting test turnaround time, and increasing test frequency in high transmission scenarios can supplement additional mitigation measures to aid outbreak prevention in congregate settings.

ASSESSMENT OF BUILDING MAINTENANCE PRACTICE IN UNIVERSITY OF JOS, NIGERIA

The research was aimed at assessing the building maintenance practice in university of Jos, with a view of improving the maintenance practice in the university, for efficiency and effective performance of the university buildings. The study adopt a quantitative research approach. The research used a close-ended questionnaire instrument to collect pertinent information and or/data. A total of one hundred and eleven (111) questionnaire was administered to the responded, out of which, ninety two (92) was retrieved and adopted for the study. The research used simple random sampling to arrive at the sampling size. The research data was analyzed descriptively using SPSS. The findings show that the maintenance practices in university of Jos are; preventive maintenance, plan maintenance, corrective maintenance, emergency maintenance, avoidance maintenance, as well as scheduled maintenance are all practice in university of Jos. Condition base maintenance, unplanned maintenance as well as, and predictable maintenance and running maintenance are not practiced at the University of Jos. Base on the findings from the above research, the study hereby recommended that; Unplanned maintenance should be incorporated in the maintenance practice of the university to enable part of the buildings and or its components get repairs or fix when it breaks down. Running maintenance should be as well slated among the maintenance practices in universities, as it helps maintenance staff to carry out maintenance when the need arises to restore deteriorating surfaces and or wall in the university buildings in enhances its efficiency and performance. Condition-based maintenance should also be incorporated among maintenance practices in the university in other to enable the maintenance personnel of the university conduct monitoring of equipment performance in the building and or assets management with visual inspections, scheduled tests as well as sensor devices to determine the most efficient time to perform maintenance. Predictable maintenance practice (PdM) also should be included on the types of maintenance practices in the university. Since it’s a techniques that uses data analysis tools and techniques to detect anomalies, it would assist the maintenance professionals in maintenance operation and possible detect defects.

Effective Scheduling of Multi-Load Automated Guided Vehicle in Spinning Mill: A Case Study

In the Flexible Manufacturing System (FMS), where material processing is carried out in the form of tasks from one department to another, the use of Automated Guided Vehicles (AGVs) is significant. The application of multiple-load AGVs can be understood to boost FMS throughput by multiple orders of magnitude. For the transportation of materials and items inside a warehouse or manufacturing plant, an AGV, a mobile robot, offers extraordinary industrial capabilities. The technique of allocating AGVs to tasks while taking into account the cost and time of operations is known as AGV scheduling. Most research has exclusively addressed single-objective optimization, whereas multi-objective scheduling of AGVs is a complex combinatorial process without a single solution, in contrast to single-objective scheduling. This paper presents the integrated Local Search Probability-based Memetic Water Cycle (LSPM-WC) algorithm using a spinning mill as a case study. The scheduling model’s goal is to maximize machine efficiency. The scheduling of the statistical tests demonstrated the applicability of the proposed model in lowering the makespan and fitness values. The mean AGV operating efficiency was higher than the other estimated models, and the LSPM-WC surpassed the different algorithms to produce the best result.

Energy efficient non-preemptive scheduling of imprecise mixed-criticality real-time tasks

Previous studies focus on the classical mixed-criticality task model with preemptive dynamic priority scheduling in which all low-criticality (LO) tasks are dropped in the high-criticality mode (HI-mode). This paper focuses on the imprecise mixed-criticality (IMC) tasks model in which LO tasks reduce their execution budgets instead of being dropped. So far, the energy minimization problem of non-preemptive dynamic priority scheduling has received little attention. In this paper, we first develop schedulability tests of non-preemptive earliest deadline first with virtual deadline (NP-EDFVD) for IMC tasks, which is the first attempt for non-preemptive dynamic priority scheduling in single processor IMC systems. Subsequently, the uniform single speed (USS) algorithm based on the schedulability tests of NP-EDFVD is proposed to reduce energy consumption while protecting the IMC correctness. Finally, the experimental results show that the USS algorithm saves an average of 25.62% energy compared to NP-EDFVD.

An improved parameter identification method considering multi-timescale characteristics of lithium-ion batteries

To monitor and predict battery states, a battery model with accurate model parameters is important to battery management systems (BMS). However, for multi-timescale dynamic characteristics, the precision and adaptability of parameter identification of the Li-ion battery model is unsatisfactory up to now. In this paper, an improved parameter identification algorithm is proposed combining fixed memory recursive least squares (FMRLS) and fading extended Kalman filter (FEKF) which are used to obtain the fast dynamic (FD) and slow dynamic (SD) parameters of equivalent circuit model (ECM) respectively. Open-circuit voltage (OCV) is identified as a component of the SD part because of its slow dynamic nature in this algorithm. Federal urban driving schedule (FUDS) and dynamic stress test (DST) tests with different initial state of charge (SOC) and temperatures were employed for verifications, and the results show that the algorithm can track the battery terminal voltage in time and the root mean square error (RMSE) is as low as 1 mV. Meanwhile, the results reveal that the advanced SOC-OCV tests can be avoided indeed, and model parameters identified by this algorithm have good robustness in different temperatures and high consistency in different operating conditions which are significantly better than conventional algorithms.

Fine-Grained Runtime Monitoring of Real-Time Embedded Systems

Dynamically ensuring the correctness of the functional behavior of a real-time embedded system is tedious, especially in the autonomous domain. Even though the current real-time task model provides sufficient information to perform basic schedulability tests, it is inadequate to be used in runtime monitoring to assert and guarantee the correctness of a system under hardware/software malfunctions or malicious cyber attacks. In this article, we present a runtime monitoring approach based on a fine-grained model of real-time tasks.

Abstract IA016: The DCIS: A biological challenge and clinical dilemma

Abstract Currently, one of the most challenging problems in oncology is predicting more precisely whether lesions that are detected by sensitive screening tests are indolent (hence, not requiring extensive treatment) or progressive and potentially life-threatening. For example, the increase in breast cancer “incidence” observed over the last 20 years is largely attributable to increased detection of ductal carcinoma in situ (DCIS) and stage I disease by imaging. Despite the increase in early-stage disease, the rates of advanced stage disease have changed only minimally, and the rate of metastatic disease has been virtually unchanged. Conversely, all screening tests miss some life-threatening cancers, known as “interval cancers,” that are diagnosed between scheduled screening tests. Breast cancer best illustrates the problem of interval cancers. It is known that more-aggressive types of breast cancer are more likely to be missed by screening; the cancer grows so quickly it becomes symptomatic after a normal screening test. For example, interval-detected breast cancers are 1.8 to 2.6-fold more likely to be estrogen receptor (ER) negative compared to screen-detected tumors, are likely to be diagnosed at a more advanced stage and are faster growing on average than screen-detected cancers. Relatively little is known about the molecular and cellular differences between screen- detected lesions and interval tumors which might be used to distinguish among the two types of lesions and potentially point to more effective strategies and targets for intervention. The National Cancer Institute has established programs to identify cellular and molecular characteristics that distinguish progressive from non-progressive lesions. Recent progress in this direction will be discussed by the speaker. Citation Format: Sudhir Srivastava. The DCIS: A biological challenge and clinical dilemma [abstract]. In: Proceedings of the AACR Special Conference on Rethinking DCIS: An Opportunity for Prevention?; 2022 Sep 8-11; Philadelphia, PA. Philadelphia (PA): AACR; Can Prev Res 2022;15(12 Suppl_1): Abstract nr IA016.

Online Model Parameter and State of Charge Estimation of Li-Ion Battery Using Unscented Kalman Filter Considering Effects of Temperatures and C-Rates

This paper proposed a technique for online modeling and state of charge (SoC) estimation of Li-ion batteries considering the effects of operating temperatures and C-rates. The proposed battery model, which is updated in real-time, is incorporated with the unscented Kalman filter (UKF) for accurate and online SoC estimation. In the proposed technique, Thevenin-based equivalent circuit model of Li-ion battery is used. Each of the RC networks of the Thevenin model is represented as a first-order linear time-invariant (LTI) system. The offline RC parameters are extracted as the parameters of the first-order LTI system using the final value theorem. Then the offline RC parameters are converted to the online model parameters compensating the effects of operating temperatures and C-rates. Finally, the UKF technique is augmented with the proposed online battery model for higher accurate and online SoC estimation. An experimental setup has been developed in the LabVIEW platform to validate the proposed battery model and apply it for online SoC estimation. The proposed online battery model and UKF are developed in Matlab and then integrated with the LabVIEW program using the Matlab-LabVIEW interface called Math Script. The proposed technique has been rigorously validated in the laboratory under hybrid pulse power characterization (HPPC) and federal urban driving schedule (FUDS) tests under wide range of varying operating temperatures and C-rates. In the HPPC test, the SoC estimated using the proposed technique has a maximum absolute relative percentage error (ARPE) of less than 2%, whereas the battery model that does not account for temperature and C-rate effects has a maximum ARPE of 8.79 percent, which is 4.30 times higher than the proposed technique. The proposed approach yielded mean ARPE of 0.30%, 1.02%, and 0.81% in the FUDS test at 25 °C, 0 °C, and 40 °C, respectively, which is performed in dynamic identical C-rates. Furthermore, higher accuracy and effectiveness of the proposed technique have been validated under the presence of white and coloured measurement noises.

Early stage internal short circuit fault diagnosis for lithium-ion batteries based on local-outlier detection

Internal short circuit (ISC) is considered to be one of the main causes of battery thermal runaway, which is a critical obstacle to the application of lithium-ion batteries for energy storage. Aiming at inconspicuous characteristics and slow detection speed of early stage ISC faults, this paper proposes a fast diagnostic method for ISC based on local-gravitation outlier detection. In the serial battery module, the cell terminal voltages are normalized to characterize voltage trends that are more sensitive to faults than voltage magnitudes, which improves the speed of fault diagnosis. The normalized voltages are then evaluated by a local gravity outlier detection algorithm to detect faults, by which the anomalies caused by the faults are amplified to achieve the ability to diagnose early ISC faults. The performance of the method is validated under the Urban Dynamometer Driving Schedule test, where several sets of experimental results for ISC faults of varying severity showed that the proposed method could detect them accurately and rapidly even when the fault characteristics are not obvious.

Reading Teachers: Reading Strategies Employed in Teaching Reading in Grade School

The purpose of the study. The aims of this research are to determine the teachers' reading style, determine their reading speed, and determine which reading methods are the teachers' strengths and weaknesses utilizing a thorough evaluation of reading techniques from Hawker Brownlow Education. This study utilized the comprehensive assessment of reading strategies from Hawker Brownlow Education. This material is composed of four series of tests namely, Reading Comprehension 1- Historical Fiction, Reading Comprehension 2- History Article, Reading Comprehension 3- Kate Wrote About a Special Zoo, and Reading Comprehension 4- Email written by Carl with different reading passages using the same 12 reading strategies. It is found that readers can effectively comprehend when they use the following strategies namely, finding word meaning in context, understanding sequence, and making predictions. Therefore, the four series of assessments, show that there are varied ways of comprehending a material that might directly influence the duration and time limit allocated in reading and answering the material, the recurring events of the same material used, and the scheduling of reading comprehension tests.

More Stable Memory Retention of Novel Words Learned from Fast Mapping than from Explicit Encoding.

There is a heated debate on a learning paradigm known as "fast mapping" for its early neocortical dependence and retained memory over time for amnesic patients with hippocampal system damage. Whether the fast mapping allows hippocampus independent learning and induces rapid integration is poorly understood. The present study aims to investigate the effect of fast mapping on very long-term retention, which to our knowledge has not been previously explored. We tested memory retention ranging from 10min to 1.5 years, for novel word-object associations learned from fast mapping or explicit encoding procedures. The three-alternative forced choice recognition task was employed to assess memory performance. Besides the slight adjustment of the testing schedule, other settings remained the same in Experiment 2 to replicate and verify the findings of Experiment 1. Results showed that overall memory retrieval performance was higher after explicit encoding as compared to fast mapping. However, retrieval performance after explicit encoding dropped after 1.5 years, but remained stable in the fast mapping condition. Furthermore, matching the semantic category of the known and the novel items during the fast mapping paradigm might affect long-term retention. These results suggest that fast mapping creates more stable long-term memory representations as compared to the explicit encoding strategy.

Regular Testing of HIV and Sexually Transmitted Infections With Self-Collected Samples From Multiple Anatomic Sites to Monitor Sexual Health in Men Who Have Sex With Men: Longitudinal Study.

Regular HIV and sexually transmitted infection (STI) testing for men who have sex with men (MSM) is an important means of infection prevention, the adoption of which remains suboptimal in the community. On the hypothesis that engagement plays an important role in sexual health monitoring, this study aimed to pilot-test internet-based HIV and STI testing with self-sampling to enhance engagement of MSM with regular testing. This 1-year cohort study was conducted on HIV-negative MSM aged 18 years or older. A designated website was set up to enable participants to make appointments for baseline and follow-up visits at 3-monthly intervals. On-site blood sampling was performed for HIV and syphilis tests, along with self-collection of pharyngeal swabs, rectal swabs, and urine samples for Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) testing. Full engagement, as defined by having made at least 3 visits over a 6-12 months' follow-up period, was compared with partial engagement in the bivariable logistic regression model. Between August 2019 and October 2020, 204 MSM were recruited, after the exclusion of 2 baseline HIV-positive MSM. The majority (189/204, 92.7%) were Chinese, the median age was 31 (IQR 26-39) years, and 58.0% (116/200) had experience with pre-exposure prophylaxis (PrEP) at baseline. Full engagement (146/204, 71.6%) was associated with incident STI during the follow-ups (odds ratio [OR] 4.23, 95% CI 1.63-10.94), seeking a medical referral after STI detection (OR 10.25, 95% CI 3.25-29.79), and a synchronized schedule of HIV and STI testing with PrEP visits (OR 51.85, 95% CI 19.30-139.34). No incident HIV was detected in the follow-up period. At baseline, the overall STI (CT, NG, or syphilis) prevalence was 30%, with CT at 18%, NG at 13%, and syphilis at 5%. During follow-up, the incidences were 59.08/100 person-years (py) for any STI, 33.05/100 py for CT, 29.86/100 py for NG, and 10.4/100 py for syphilis. The detection rates of CT and NG in urine samples were lower than with pharyngeal swabs and rectal swabs. The scores for convenience, confidence of correct sampling, and accuracy of self-sampling were high (7 to 8 out of 10). Both baseline prevalence and incidence of STI were high among MSM engaged in regular testing. A high degree of engagement in regular STI and HIV testing was positively associated with incident STI, history of health-seeking behaviors, and perceived convenience of self-sampling. Self-sampling could be introduced as a means of enhancing engagement in regular HIV and STI testing.

DDEL-11. DETERMINING THE DOSE OF REGADENOSON MOST LIKELY TO TRANSIENTLY ALTER THE INTEGRITY OF THE BLOOD-BRAIN BARRIER IN PATIENTS WITH GLIOMAS

Abstract BACKGROUND The blood brain barrier (BBB) is a major obstacle to the delivery of chemotherapy to the CNS. Regadenoson is an FDA approved adenosine A2 agonist used for cardiac stress tests. In murine models, it transiently increases BBB permeability to a 70KD dextran. This multi-institutional, NIH funded, Adult Brain Tumor Consortium trial was designed to discover a dose of regadenoson that substantially increases vascular permeability in normal appearing white matter (NAWM) where drug delivery is particularly challenging. METHODS Adults ages 18-45 with supratentorial gliomas at low-risk for regadenoson complications were recruited (n = 7). One patient was treated at each of seven dose levels (from 0.05 to 1.4 mg) that are known to be safe in humans. The primary outcome measure is change in vascular permeability via dynamic contrast enhanced (DCE) perfusion MRI estimates of Ktrans. The primary outcome measure was a 10-fold higher Ktrans in NAWM than reported in literature (Ktrans > 0.04 min-1). Contrast-enhanced T1 subtraction map estimates of change in contrast enhancement and other measurements in normal brain and non-enhancing tumor were quantified. RESULTS Ktrans measures in NAWM averaged 1.13x10-3 ± 0.44x10-3 (SEM) min-1, lower than the target of 0.04 min-1. Normalized, contrast enhanced T1-weighted MR signal intensity in NAWM increased an average of 74.0 ± 22.4% min-1 (SEM) min-1, which was significantly higher than zero (P = 0.0163). Data available from this limited sample failed to meet the target goal in Ktrans increase or change in contrast enhancing signal intensity. CONCLUSION Administration of regadenoson at seven different doses did not significantly elevate Ktrans for gadolinium in NAWM. This data suggests that single doses of regadenoson are unlikely to substantially increase the delivery of therapeutic agents in non-enhancing brain tissue. This trial design is appropriate for further human testing of other regadenoson schedules and other novel approaches aimed at transiently modifying BBB permeability.

Elite collaborative search algorithm and its application in power generation scheduling optimization of cascade reservoirs

The joint optimization scheduling model of cascade reservoirs has the characteristics of high dimensionality, dynamic, nonlinear, multivariate, and strong constraint. Around its solution problem, this paper carries out the research of the efficient model solution method based on the group intelligent optimization algorithm. Firstly, given the defect of the standard collaborative search algorithm that it is easy to falls into local optimization and weakening of global search ability in the later stage, three efficient improvement strategies are proposed through parameter randomization, elite reinforcement learning, and elite help learning. And based on this, an elite collaborative search algorithm (ECSA) coupled with the three improvement strategies is established, which enhances the ability of individuals to search globally and jump out of local optimality, and it has strong robustness and optimization ability. Secondly, taking six cascade power stations in the Yalong River Basin as an example, the power generation dispatching model of cascade reservoirs considering various constraints such as reservoir discharge flow and water level restriction are constructed, and six typical runoff scenarios are selected, and the joint power generation scheduling test is carried out by using five algorithms, i.e., ECSA, CSA, PSO, GWO, and WOA. Finally, through the comparison of the scheduling results, it is found that compared with the other algorithms, the solution obtained by the proposed ECSA in this paper can effectively improve the overall power generation of the basin and the efficiency of water resource utilization in river basins. Taking the normal year as an example, compared with the CSA、PSO、GWO，and WOA method, the average annual increase of power generation by the ECSA method is 32, 4778, 4153, and 2288 million kWh respectively.

Pre- and post-simulations of shake-table tests on a stone masonry building aggregate using finite-discrete elements

This work presents the simulations of the non-linear dynamic response of a three-dimensional finite-discrete element model. The model simulates a half-scale masonry building aggregate tested on a shake table by other Authors. The aggregate is made of two un-connected building units having different heights and slightly different wall thicknesses. The floors are made of timber beams and boards. The modelling approach accounts jointly for in-plane and out-of-plane responses, which can be expected given the high flexibility of the floors, and for the separation between the two building units. The simulations are related both to the blind predictions, according to a scheduled testing sequence, and to the post-dictions according to the actual testing sequence and some model calibrations. The prediction model overestimates displacements, underestimates base shear and fairly predicts the damage pattern of comparable experimental runs. The use of the recorded shake table motion improves the accuracy of the post-diction simulations, while still delivering beam unseating. A higher Young’s modulus of the blocks improves markedly the predictions. The strengthening intervention with steel angles connecting floors to walls is only approximately modelled and does not improve the outcomes of the simulations. In summary, the adopted modelling approach is capable of accounting for the pounding between the two building units, predicting the most significant damage as well as estimating approximate average of peak values of base shear and displacements, while individual time histories are less accurately estimated.

Enhanced schedulability tests for real-time regularity-based virtualized systems with dependent and self-suspension tasks

Enhanced schedulability tests for real-time regularity-based virtualized systems with dependent and self-suspension tasks

ODP372 A Rare Case Of Cornelia de Lange Syndrome With Hyperinsulinism And Hypopituitarism

Abstract Background Cornelia de Lange syndrome (CdLS) is characterized by slow growth with short stature, intellectual disability with developmental delays, distinctive facial features, and limb defects. Various genetic mutations have been associated with CdLS, with approximately 60% of cases having a mutation in the NIPBL gene. There are few published reports of endocrine disorders in individuals affected by CdLS. Clinical Case A four month old female was admitted for hypoglycemic seizures. She had previously undergone workup for CHARGE syndrome. Physical exam was remarkable for acrocephaly, malar hypoplasia, hypertelorism with downslanting eyes, hirsutism, and bradydactyly. During her hospitalization, she remained persistently hypoglycemic despite repeated dextrose boluses, prompting a scheduled fasting test. Results indicated severe hypoglycemia (37 mg/dL) with inappropriate suppression of beta-hydroxybutyrate (0. 08 mmol/L) and negative urine ketones. Her glucagon stimulation test result showed an exaggerated increase of the glucose greater than 30 mg/dL after glucagon administration (glucose was 31 mg/dL at the start of the test; peak glucose was 77 mg/dL after receiving 0. 03 mg/kg of glucagon), indicating excessive glycogen stores. These findings were consistent with hyperinsulinism. Furthermore, she was found to have an undetectable cortisol (<1. 0 ug/dL) with hypoglycemia, prompting a low dose ACTH stimulation test with results consistent with central adrenal insufficiency (baseline ACTH: <5 pg/mL, baseline cortisol: <1. 0 ug/dL, peak cortisol after receiving 10 micrograms of cosyntropin was 1.1 ug/dL). Additional evaluation revealed a low free T4 (0.5 ng/dL). Interestingly, the initial TSH was 6.46 uIU/mL, which later became undetectable (<0. 05 uIU/mL), consistent with central hypothyroidism. Ultimately, a brain MRI showed sella turcica hypoplasia with absence of the dorsum sella as well as corpus callosum hypoplasia and a thin pituitary infundibulum. The child was treated with diazoxide, hydrocortisone, and levothyroxine with improvement in clinical course. Genetic testing eventually confirmed CdLS, showing a heterozygous variant mutation (c.8077_8079dupGAC: p. D2693dup) in exon 47 of NIPBL gene, classified as autosomal dominant. Conclusion There are very few clinical reports that mention either hyperinsulinism or hypopituitarism in an individual affected by CdLS. This patient is a rare documented case of CdLS presenting with both hyperinsulinism and hypopituitarism. Further understanding of the different genetic mutations seen with CdLS could help identify atypical forms of CdLS associated with endocrinopathies and more clearly direct unifying treatment. Presentation: No date and time listed

Towards a Tractable Exact Test for Global Multiprocessor Fixed Priority Scheduling

Scheduling algorithms are called “global” if they can migrate tasks between cores. Global scheduling algorithms are the de-facto standard practice for general purpose Operating Systems, to balance the workload between cores. However, the exact schedulability analysis of real-time applications for these algorithms is proven to be weakly NP-hard. Despite such a hardness, the research community keeps investigating the methods for an exact schedulability analysis for its relevance and to tightly estimate the execution requirements of real-time systems. Due to the NP-hardness, the available exact tests are very time and memory demanding even for sets of a few tasks. On another hand, the available sufficient tests are very pessimistic, despite consuming less resources. Motivated by these observations, we propose an exact schedulability test for constrained-deadline sporadic tasks under global multiprocessor fixed-priority scheduling scheduler, which is significantly faster and consumes less memory, compared to any other available exact test. To derive a faster test, we exploit the idea of a state-space pruning, aiming at reducing the number of feasible system states to be examined by the test. The resulted test is multiple orders of magnitude faster with respect to other state-of-the-art exact tests. Our C++ implementation is publicly available.

A security-aware hardware scheduler for modern multi-core systems with hard real-time constraints

In this paper, we propose an online security-aware hardware scheduler, the so-called Secure And Fast hardware Scheduler (SAFAS), for real-time task scheduling in multi-core systems in the presence of schedule-based side-channel attacks. To avoid such attacks and ensure that all tasks meet their deadlines, SAFAS schedules critical tasks and their replicas using a hardware-based strict Least Slack Time first (LST) algorithm independently while it independently schedules the non-critical tasks using a hardware-based EDF algorithm. SAFAS enhances the system performance and reduces the chance of side-channel attacks due to the different processing cores allocated to each task in each scheduling interval. The hardware scheduler operates independently and in parallel with the multi-core system and hides the scheduling characteristics from adversaries. The software-based Earliest Deadline First (EDF) algorithm is also used for schedulability tests and feasibility analysis of hard real-time periodic tasks to maximize the number of tasks scheduled successfully in the multi-core system. SAFAS has been synthesized and simulated on a Xilinx Vivado 2018.2 and implemented on a Spartan-7 FPGA chip. Our experimental results indicate that SAFAS increases the performance of the system by 4.8 times as compared to previous state-of-the-art hardware schedulers while guaranteeing that all critical tasks and their replicas meet their deadlines.