Fuzzing is a simple yet effective approach to discover software bugs utilizing randomly generated inputs. However, it is limited by coverage and cannot find bugs hidden in deep execution paths of the program because the randomly generated inputs fail complex sanity checks, e.g., checks on magic values, checksums, or hashes.To improve coverage, existing approaches rely on imprecise heuristics or complex input mutation techniques (e.g., symbolic execution or taint analysis) to bypass sanity checks. Our novel method tackles coverage from a different angle: by removing sanity checks in the target program. T-Fuzz leverages a coverage guided fuzzer to generate inputs. Whenever the fuzzer can no longer trigger new code paths, a light-weight, dynamic tracing based technique detects the input checks that the fuzzergenerated inputs fail. These checks are then removed from the target program. Fuzzing then continues on the transformed program, allowing the code protected by the removed checks to be triggered and potential bugs discovered.Fuzzing transformed programs to find bugs poses two challenges: (1) removal of checks leads to over-approximation and false positives, and (2) even for true bugs, the crashing input on the transformed program may not trigger the bug in the original program. As an auxiliary post-processing step, T-Fuzz leverages a symbolic execution-based approach to filter out false positives and reproduce true bugs in the original program.By transforming the program as well as mutating the input, T-Fuzz covers more code and finds more true bugs than any existing technique. We have evaluated T-Fuzz on the DARPA Cyber Grand Challenge dataset, LAVA-M dataset and 4 real-world programs (pngfix, tiffinfo, magick and pdftohtml). For the CGC dataset, T-Fuzz finds bugs in 166 binaries, Driller in 121, and AFL in 105. In addition, found 3 new bugs in previouslyfuzzed programs and libraries.Permission to freely reproduce all or part of this paper for noncommercial purposes is granted provided that copies bear this notice and the full citation on the first page. Reproduction for commercial purposes is strictly prohibited without the prior written consent of the Internet Society, the first-named author (for reproduction of an entire paper only), and the author's employer if the paper was prepared within the scope of employment.

[1] Forest responses to warming, in the absence of changes in vegetation structure, reflect the balance between the increased atmospheric demand for water and changes in water availability. This study uses a coupled hydroecologic model applied to a snow-dominated mountain watershed to demonstrate how complex topography and interannual variation in climate drivers combine to alter the balance between moisture availability and energy demand. We focus specifically on how often and under what conditions changes in the timing of soil water recharge as precipitation or snowmelt are a significant control on forest actual evapotranspiration (AET) in the Central California Sierra. We show that while interannual variation in precipitation is the dominant control on interannual variation in AET, how much of that recharge accumulates as a seasonal snowpack can act as a second-order control. This sensitivity of AET to snow accumulation and melt occurs across a substantial elevation range (1800-2700 m) and at both aggregate watershed and 90 m patch scales. Model results suggest that the variation in AET due to recharge timing is greatest for patches and years with moderate levels of precipitation or patches that receive substantial lateral moisture inputs. For a 3 C warming scenario, the annual AET increases in some years due to warmer temperatures but decreases by as much as 40% in other years due to an earlier timing of snowmelt. These results help to clarify the conditions under which water availability for forests decreases and highlight scenarios that may lead to increased drought stress under a warming climate in snow-dominated mountain regions.Citation: Tague, C., and H. Peng (2013), The sensitivity of forest water use to the timing of precipitation and snowmelt recharge in the California Sierra: Implications for a warming climate,

We present four-point probe measurements of the in-plane electrical conductivities of electron beam-evaporated gold layers of thickness 20 nm to 2 μm deposited on Si(100), Si(111), and BK7 glass substrates. The values of thermal conductivities deduced from these measurements of gold films on glass samples agree well with prediction from the surface and grain-boundary scattering model, but not for gold films on silicon samples. Thermal conductivities of gold films are found to be different for samples on hydrofluoric acid etched Si(100) and Si(111) substrates, for which surface roughness and microstructures of the gold films have been examined to understand the difference in these thermal conductivity results.

Human blood plasma is a complex biological fluid containing soluble proteins, sugars, hormones, electrolytes, and dissolved gasses. As plasma interacts with a wide array of bodily systems, changes in protein expression, or the presence or absence of specific proteins are regularly used in the clinic as a molecular biomarker tool. A large body of literature exists detailing proteomic changes in pathologic contexts, however little research has been conducted on the quantitation of the plasma proteome in age-specific, healthy subjects, especially in pediatrics. In this study, we utilized SWATH-MS to identify and quantify proteins in the blood plasma of healthy neonates, infants under 1 year of age, children between 1-5 years, and adults. We identified more than 100 proteins that showed significant differential expression levels across these age groups, and we analyzed variation in protein expression across the age spectrum. The plasma proteomic profiles of neonates were strikingly dissimilar to the older children and adults. By extracting the SWATH data against a large human spectral library we increased protein identification more than 6-fold (940 proteins) and confirmed the concentrations of several of these using ELISA. The results of this study map the variation in expression of proteins and pathways often implicated in disease, and so have significant clinical implication.