Fuzzing Deep-Learning Libraries via Automated Relational API Inference

A growing body of research has been dedicated to DL model testing. However, there is still limited work on testing DL libraries, which serve as the foundations for building, training, and running DL models. Prior work on fuzzing DL libraries can only generate tests for APIs which have been invoked by documentation examples, developer tests, or DL models, leaving a large number of APIs untested. In this paper, we propose DeepREL, the first approach to automatically inferring relational APIs for more effective DL library fuzzing. Our basic hypothesis is that for a DL library under test, there may exist a number of APIs sharing similar input parameters and outputs; in this way, we can easily "borrow" test inputs from invoked APIs to test other relational APIs. Furthermore, we formalize the notion of value equivalence and status equivalence for relational APIs to serve as the oracle for effective bug finding. We have implemented DeepREL as a fully automated end-to-end relational API inference and fuzzing technique for DL libraries, which 1) automatically infers potential API relations based on API syntactic or semantic information, 2) synthesizes concrete test programs for invoking relational APIs, 3) validates the inferred relational APIs via representative test inputs, and finally 4) performs fuzzing on the verified relational APIs to find potential inconsistencies. Our evaluation on two of the most popular DL libraries, PyTorch and TensorFlow, demonstrates that DeepREL can cover 157% more APIs than state-of-the-art FreeFuzz. To date, DeepREL has detected 162 bugs in total, with 106 already confirmed by the developers as previously unknown bugs. Surprisingly, DeepREL has detected 13.5% of the high-priority bugs for the entire PyTorch issue-tracking system in a three-month period. Also, besides the 162 code bugs, we have also detected 14 documentation bugs (all confirmed).Comment: Accepted at ESEC/FSE 202

White-box Compiler Fuzzing Empowered by Large Language Models

Compiler correctness is crucial, as miscompilation falsifying the program behaviors can lead to serious consequences. In the literature, fuzzing has been extensively studied to uncover compiler defects. However, compiler fuzzing remains challenging: Existing arts focus on black- and grey-box fuzzing, which generates tests without sufficient understanding of internal compiler behaviors. As such, they often fail to construct programs to exercise conditions of intricate optimizations. Meanwhile, traditional white-box techniques are computationally inapplicable to the giant codebase of compilers. Recent advances demonstrate that Large Language Models (LLMs) excel in code generation/understanding tasks and have achieved state-of-the-art performance in black-box fuzzing. Nonetheless, prompting LLMs with compiler source-code information remains a missing piece of research in compiler testing. To this end, we propose WhiteFox, the first white-box compiler fuzzer using LLMs with source-code information to test compiler optimization. WhiteFox adopts a dual-model framework: (i) an analysis LLM examines the low-level optimization source code and produces requirements on the high-level test programs that can trigger the optimization; (ii) a generation LLM produces test programs based on the summarized requirements. Additionally, optimization-triggering tests are used as feedback to further enhance the test generation on the fly. Our evaluation on four popular compilers shows that WhiteFox can generate high-quality tests to exercise deep optimizations requiring intricate conditions, practicing up to 80 more optimizations than state-of-the-art fuzzers. To date, WhiteFox has found in total 96 bugs, with 80 confirmed as previously unknown and 51 already fixed. Beyond compiler testing, WhiteFox can also be adapted for white-box fuzzing of other complex, real-world software systems in general

Salivary signatures of oral-brain communication in sleep bruxers

IntroductionMicrobiota and their interaction with hosts have been of great interest in brain research in recent years. However, the role of oral microbiota in mental illness and the underlying mechanism of oral-brain communication remains elusive. Sleep bruxism (SB) is an oral parafunctional activity related to the nervous system and is considered a risk factor for harmful clinical consequences and severe systemic conditions. Exploring the connection between oral microbiota and sleep bruxism may deepen our understanding of the complex relationship between oral-brain axis and provide insights for treatment.MethodsIn this study, salivary samples were collected from 22 individuals with SB and 21 healthy controls, and metagenomics with metabolomics was performed. Nonparametric Wilcoxon test were applied for the statistical analysis between the two groups. Microbial dysbiosis and altered oral metabolites were found in the SB individuals.ResultsThe characteristic metabolite N-acetylglucosamine (GlcNAc) (VIP=8.4823, P<0.05) was correlated to a statistically lower Streptococcus mitis level in SB individuals. Salivary IFN-g level and IFN-g/IL-4 ratio were detected with significant changes in a chip assay. Amino acid metabolism pathways were upregulated, and the pathway with the largest number of differentially expressed genes is related to amino-tRNA charging pathway, while the most significantly enriched pathway is related to arginine biosynthesis. Neurotransmitter-associated pathways with glutamatergic and GABAergic synapses and cardiovascular system-related pathways were enriched in the SB group.DiscussionThese results indicate a possible neuroimmune regulatory network of oral-brain communication in SB, which helps explain the mechanism of the oral microbiome with the host in sleep bruxers and provides a reference for early clinical and therapeutic intervention to improve the diagnosis and treatment of SB and similar diseases

The late Eocene rise of SE Tibet formed an Asian ‘Mediterranean’ climate

Southeastern (SE) Tibet forms the transition zone between the high interior Tibetan Plateau and the lowlands of southwest China. So understanding the elevation history of SE Tibet, a biodiversity hotspot, enlightens our understanding of the interactions between tectonics, monsoon dynamics and biodiversity. Here we reconstruct the uplift history of the Markam Basin, SE Tibet, during the middle−late Eocene based on U − Pb dating, plant fossil assemblages, and stable and clumped isotope analyses. Our results suggest that the floor of the Markam Basin was at an elevation of 2.6 ± 0.9 km between 42 Ma and 39 Ma, where the mean annual air temperature (MAAT) was 13.2 ± 2.4 °C. The basin then rose rapidly to 3.8 (+0.6/−0.8) km before 36 Ma. Integrated with existing paleoelevation data, we propose that the high plateau boundary (∼3.0 km) of SE Tibet formed during the late Eocene. Numerical climate modeling with realistic paleo-landscapes shows that with the rise of SE Tibet, a Mediterranean-like climate developed in the region characterized by bi-modal precipitation with two wet seasons in boreal spring and autumn. The high topographic relief of SE Tibet, coupled with this distinctive Mediterranean-like climate system, helped develop the high biodiversity of the Hengduan Mountains

The rise and demise of the Paleogene Central Tibetan Valley

Reconstructing the Paleogene topography and climate of central Tibet informs understanding of collisional tectonic mechanisms and their links to climate and biodiversity. Radiometric dates of volcanic/sedimentary rocks and paleotemperatures based on clumped isotopes within ancient soil carbonate nodules from the Lunpola Basin, part of an east-west trending band of basins in central Tibet and now at 4.7 km, suggest that the basin rose from 4.0 km by 29 Ma. The height change is quantified using the rates at which wet-bulb temperatures ( ) decline at land surfaces as those surface rise. In this case, fell from ~8°C at ~38 Ma to ~1°C at 29 Ma, suggesting at least ~2.0 km of surface uplift in ~10 Ma under warm Eocene to Oligocene conditions. These results confirm that a Paleogene Central Tibetan Valley transformed to a plateau before the Neogene

A distinctive Eocene Asian monsoon and modern biodiversity resulted from the rise of eastern Tibet

The uplift of eastern Tibet, Asian monsoon development and the evolution of globally significant Asian biodiversity are all linked, but in obscure ways. Sedimentology, geochronology, clumped isotope thermometry, and fossil leaf-derived numerical climate data from the Relu Basin, eastern Tibet, show at ∼50–45 Ma the basin was a hot (mean annual air temperature, MAAT, ∼27 °C) dry desert at low-elevation of 0.6 ± 0.6 km. Rapid basin rise to 2.0 ± 0.9 km at 45–42 Ma and to 2.9 ± 0.9 km at 42–40 Ma, with MAATs of ∼20 and ∼16 °C, respectively, accompanied seasonally varying increased annual precipitation to >1500 mm. From ∼39 to 34 Ma, the basin attained 3.5 ± 1.0 km, near its present-day elevation (∼3.7 km), and MAAT cooled to ∼6 °C. Numerically-modelled Asian monsoon strength increased significantly when this Eocene uplift of eastern Tibet was incorporated. The simulation/proxy congruence points to a distinctive Eocene Asian monsoon, quite unlike that seen today, in that it featured bimodal precipitation and a winter-wet regime, and this enhanced biodiversity modernisation across eastern Asia. The Paleogene biodiversity of Asia evolved under a continually modifying monsoon influence, with the modern Asian monsoon system being unique to the present and a product of a long gradual development in the context of an ever-changing Earth system

Für | For Manfred from his Students

Dieses Buch enthält Beiträge von Personen, die ihre Magister- oder Doktorarbeit unter der Betreuung von Manfred Krifka geschrieben haben. Es ist als kleines Abschiedsgeschenk für Manfred Krifka zum Ende seiner Amtszeit als Direktor des Leibniz-Zentrums für Allgemeine Sprachwissenschaft gedacht. Die Herausgeberin und der Herausgeber haben Beiträge zu sprachwissenschaftlichen und nicht-sprachwissenschaftlichen Themen in einer Vielzahl von Genres gesammelt. Diese Vielfalt spiegelt die Interessen und Forschungsthemen von Manfred Krifka wider. Sie spiegelt auch die Vielfalt der Menschen wider, denen Manfred Krifka geholfen hat

Study on Misalignment Angle Compensation during Scale Factor Matching for Two Pairs of Accelerometers in a Gravity Gradient Instrument

A method for automatic compensation of misalignment angles during matching the scale factors of two pairs of the accelerometers in developing the rotating accelerometer gravity gradient instrument (GGI) is proposed and demonstrated in this paper. The purpose of automatic scale factor matching of the four accelerometers in GGI is to suppress the common mode acceleration of the moving-based platforms. However, taking the full model equation of the accelerometer into consideration, the other two orthogonal axes which is the pendulous axis and the output axis, will also sense the common mode acceleration and reduce the suppression performance. The coefficients from the two axes to the output are δO and δP respectively, called the misalignment angles. The angle δO, coupling with the acceleration along the pendulous axis perpendicular to the rotational plane, will not be modulated by the rotation and gives little contribution to the scale factors matching. On the other hand, because of coupling with the acceleration along the centripetal direction in the rotating plane, the angle δP would produce a component with 90 degrees phase delay relative to the scale factor component. Hence, the δP component coincides exactly with the sensitive direction of the orthogonal accelerometers. To improve the common mode acceleration rejection, the misalignment angle δP is compensated by injecting a trimming current, which is proportional to the output of an orthogonal accelerometer, into the torque coil of the accelerometer during the scale factor matching. The experimental results show that the common linear acceleration suppression achieved three orders after the scale factors balance and five orders after the misalignment angles compensation, which is almost down to the noise level of the used accelerometers of 1~2 × 10−7 g/√Hz (1 g ≈ 9.8 m/s2)

Scale Factor Calibration for a Rotating Accelerometer Gravity Gradiometer

Rotating Accelerometer Gravity Gradiometers (RAGGs) play a significant role in applications such as resource exploration and gravity aided navigation. Scale factor calibration is an essential procedure for RAGG instruments before being used. In this paper, we propose a calibration system for a gravity gradiometer to obtain the scale factor effectively, even when there are mass disturbance surroundings. In this system, four metal spring-based accelerometers with a good consistency are orthogonally assembled onto a rotary table to measure the spatial variation of the gravity gradient. By changing the approaching pattern of the reference gravity gradient excitation object, the calibration results are generated. Experimental results show that the proposed method can efficiently and repetitively detect a gravity gradient excitation mass weighing 260 kg within a range of 1.6 m and the scale factor of RAGG can be obtained as (5.4 ± 0.2) E/μV, which is consistent with the theoretical simulation. Error analyses reveal that the performance of the proposed calibration scheme is mainly limited by positioning error of the excitation and can be improved by applying higher accuracy position rails. Furthermore, the RAGG is expected to perform more efficiently and reliably in field tests in the future

The synthesis of extracellular vesicles by the protistan parasite Blastocystis

10.3389/fcimb.2022.1019789FRONTIERS IN CELLULAR AND INFECTION MICROBIOLOGY1