Runtime Enforcement of Memory Safety for the C Programming Language

Memory access violations are a leading source of unreliability in C programs. Although the low-level features of the C programming language, like unchecked pointer arithmetic and explicit memory management, make it a desirable language for many programming tasks, their use often results in hard-to-detect memory errors. As evidence of this problem, a variety of methods exist for retrofitting C with software checks to detect memory errors at runtime. However, these techniques generally suffer from one or more practical drawbacks that have thus far limited their adoption. These weaknesses include the inability to detect all spatial and temporal violations, the use of incompatible metadata, the need for manual code modifications, and the tremendous runtime cost of providing complete safety. This dissertation introduces MemSafe, a compiler analysis and transformation for ensuring the memory safety of C programs at runtime while avoiding the above drawbacks. MemSafe makes several novel contributions that improve upon previous work and lower the runtime cost of achieving memory safety. These include (1) a method for modeling temporal errors as spatial errors, (2) a hybrid metadata representation that combines the most salient features of both object- and pointer-based approaches, and (3) a data-flow representation that simplifies optimizations for removing unneeded checks and unused metadata. Experimental results indicate that MemSafe is capable of detecting memory safety violations in real-world programs with lower runtime overhead than previous methods. Results show that MemSafe detects all known memory errors in multiple versions of two large and widely-used open source applications as well as six programs from a benchmark suite specifically designed for the evaluation of error detection tools. MemSafe enforces complete safety with an average overhead of 88% on 30 widely-used performance evaluation benchmarks. In comparison with previous work, MemSafe's average runtime overhead for one common benchmark suite (29%) is a fraction of that associated with the previous technique (133%) that, until now, had the lowest overhead among all existing complete and automatic methods that are capable of detecting both spatial and temporal violations

Reflections on reflection: blogging in undergraduate design studios

In this paper we describe our experiences introducing weblogs as an online design journal into two design-based IT degrees. We introduced weblogs to support reflection by the students within a studio process. We view this introduction as successful and we have continued using blogs in the subsequent academic year, although we have made some changes to take account of problems with scale, sophistication and effort

In Situ Framework for Coupling Simulation and Machine Learning with Application to CFD

Recent years have seen many successful applications of machine learning (ML) to facilitate fluid dynamic computations. As simulations grow, generating new training datasets for traditional offline learning creates I/O and storage bottlenecks. Additionally, performing inference at runtime requires non-trivial coupling of ML framework libraries with simulation codes. This work offers a solution to both limitations by simplifying this coupling and enabling in situ training and inference workflows on heterogeneous clusters. Leveraging SmartSim, the presented framework deploys a database to store data and ML models in memory, thus circumventing the file system. On the Polaris supercomputer, we demonstrate perfect scaling efficiency to the full machine size of the data transfer and inference costs thanks to a novel co-located deployment of the database. Moreover, we train an autoencoder in situ from a turbulent flow simulation, showing that the framework overhead is negligible relative to a solver time step and training epoch

Factors that influence clinicians’ decisions to offer intravenous alteplase in acute ischemic stroke patients with uncertain treatment indication:Results of a discrete choice experiment

Background: Treatment with intravenous alteplase for eligible patients with acute ischemic stroke is underused, with variation in treatment rates across the UK. This study sought to elucidate factors influencing variation in clinicians’ decision-making about this thrombolytic treatment. Methods: A discrete choice experiment using hypothetical patient vignettes framed around areas of clinical uncertainty was conducted with UK-based clinicians. Mixed logit regression analyses were conducted on the data. Results: A total of 138 clinicians completed the discrete choice experiment. Seven patient factors were individually predictive of increased likelihood of immediately offering IV alteplase (compared to reference levels in brackets): stroke onset time 2 h 30 min [50 min]; pre-stroke dependency mRS 3 [mRS 4]; systolic blood pressure 185 mm/Hg [140 mm/Hg]; stroke severity scores of NIHSS 5 without aphasia, NIHSS 14 and NIHSS 23 [NIHSS 2 without aphasia]; age 85 [68]; Afro-Caribbean [white]. Factors predictive of withholding treatment with IV alteplase were: age 95 [68]; stroke onset time of 4 h 15 min [50 min]; severe dementia [no memory problems]; SBP 200 mm/Hg [140 mm/Hg]. Three clinician-related factors were predictive of an increased likelihood of offering IV alteplase (perceived robustness of the evidence for IV alteplase; thrombolyzing more patients in the past 12 months; and high discomfort with uncertainty) and one with a decreased likelihood (high clinician comfort with treating patients outside the licensing criteria). Conclusions: Both patient- and clinician-related factors have a major influence on the use of alteplase to treat patients with acute ischemic stroke. Clinicians’ views of the evidence, comfort with uncertainty and treating patients outside the license criteria are important factors to address in programs that seek to reduce variation in care quality regarding treatment with IV alteplase. Further research is needed to further understand the differences in clinical decision-making about treating patients with acute ischemic stroke with IV alteplase

Proteomic signatures for identification of impaired glucose tolerance

The implementation of recommendations for type 2 diabetes (T2D) screening and diagnosis focuses on the measurement of glycated hemoglobin (HbA1c) and fasting glucose. This approach leaves a large number of individuals with isolated impaired glucose tolerance (iIGT), who are only detectable through oral glucose tolerance tests (OGTTs), at risk of diabetes and its severe complications. We applied machine learning to the proteomic profiles of a single fasted sample from 11,546 participants of the Fenland study to test discrimination of iIGT defined using the gold-standard OGTTs. We observed significantly improved discriminative performance by adding only three proteins (RTN4R, CBPM and GHR) to the best clinical model (AUROC = 0.80 (95% confidence interval: 0.79–0.86), P = 0.004), which we validated in an external cohort. Increased plasma levels of these candidate proteins were associated with an increased risk for future T2D in an independent cohort and were also increased in individuals genetically susceptible to impaired glucose homeostasis and T2D. Assessment of a limited number of proteins can identify individuals likely to be missed by current diagnostic strategies and at high risk of T2D and its complications

The Pattern of AQP4 Expression in the Ageing Human Brain and in Cerebral Amyloid Angiopathy

In the absence of lymphatics, fluid and solutes such as amyloid-β (Aβ) are eliminated from the brain along basement membranes in the walls of cerebral capillaries and arteries-the Intramural Peri-Arterial Drainage (IPAD) pathway. IPAD fails with age and insoluble Aβ is deposited as plaques in the brain and in IPAD pathways as cerebral amyloid angiopathy (CAA); fluid accumulates in the white matter as reflected by hyperintensities (WMH) on MRI. Within the brain, fluid uptake by astrocytes is regulated by aquaporin 4 (AQP4). We test the hypothesis that expression of astrocytic AQP4 increases in grey matter and decreases in white matter with onset of CAA. AQP4 expression was quantitated by immunocytochemistry and confocal microscopy in post-mortem occipital grey and white matter from young and old non-demented human brains, in CAA and in WMH. Results: AQP4 expression tended to increase with normal ageing but AQP4 expression in severe CAA was significantly reduced when compared to moderate CAA (p = 0.018). AQP4 expression tended to decline in the white matter with CAA and WMH, both of which are associated with impaired IPAD. Adjusting the level of AQP4 activity may be a valid therapeutic target for restoring homoeostasis in the brain as IPAD fails with age and CAA.</p

Factors that influence variation in clinical decision-making about thrombolysis in the treatment of acute ischaemic stroke: results of a discrete choice experiment

Background: Intravenous thrombolysis for patients with acute ischaemic stroke is underused (only 80% of eligible patients receive it) and there is variation in its use across the UK. Previously, variation might have been explained by structural differences; however, continuing variation may reflect differences in clinical decision-making regarding the eligibility of patients for treatment. This variation in decision-making could lead to the underuse, or result in inappropriate use, of thrombolysis. Objectives: To identify the factors which contribute to variation in, and influence, clinicians’ decision-making about treating ischaemic stroke patients with intravenous thrombolysis. Methods: A discrete choice experiment (DCE) using hypothetical patient vignettes framed around areas of clinical uncertainty was conducted to better understand the influence of patient-related and clinician-related factors on clinical decision-making. An online DCE was developed following an iterative five-stage design process. UK-based clinicians involved in final decision-making about thrombolysis were invited to take part via national professional bodies of relevant medical specialties. Mixed-logit regression analyses were conducted. Results: A total of 138 clinicians responded and opted to offer thrombolysis in 31.4% of cases. Seven patient factors were individually predictive of the increased likelihood of offering thrombolysis (compared with reference levels in brackets): stroke onset time of 2 hours 30 minutes (50 minutes); pre-stroke dependency modified Rankin Scale score (mRS) of 3 (mRS4); systolic blood pressure (SBP) of 185 mmHg (140 mmHg); stroke severity scores of National Institutes of Health Stroke Scale (NIHSS) 5 without aphasia, NIHSS 14 and NIHSS 23 (NIHSS 2 without aphasia); age 85 years (65 years); and Afro-Caribbean (white). Factors predictive of not offering thrombolysis were age 95 years; stroke onset time of 4 hours 15 minutes; severe dementia (no memory problems); and SBP of 200 mmHg. Three clinician-related factors were predictive of an increased likelihood of offering thrombolysis (perceived robustness of the evidence for thrombolysis; thrombolysing more patients in the past 12 months; and high discomfort with uncertainty) and one factor was predictive of a decreased likelihood of offering treatment (clinicians’ being comfortable treating patients outside the licensing criteria). Limitations: We anticipated a sample size of 150–200. Nonetheless, the final sample of 138 is good considering that the total population of eligible UK clinicians is relatively small. Furthermore, data from the Royal College of Physicians suggest that our sample is representative of clinicians involved in decision-making about thrombolysis. Conclusions: There was considerable heterogeneity among respondents in thrombolysis decision-making, indicating that clinicians differ in their thresholds for treatment across a number of patient-related factors. Respondents were significantly more likely to treat 85-year-old patients than patients aged 68 years and this probably reflects acceptance of data from Third International Stroke Trial that report benefit for patients aged > 80 years. That respondents were more likely to offer thrombolysis to patients with severe stroke than to patients with mild stroke may indicate uncertainty/concern about the risk/benefit balance in treatment of minor stroke. Findings will be disseminated via peer-review publication and presentation at national/international conferences, and will be linked to training/continuing professional development (CPD) programmes. Future work: The nature of DCE design means that only a subset of potentially influential factors could be explored. Factors not explored in this study warrant future research. Training/CPD should address the impact of non-medical influences on decision-making using evidence-based strategies. Funding: The National Institute for Health Research Health Services and Delivery Research programme