Post-release detection of a software vulnerability does not only cost a company money to fix, but also results in loss of reputation and damaging litigation. Techniques to prevent and detect vulnerabilities prior to release, therefore, are valuable. We performed empirical case studies on two large, widely-used open source projects: the Mozilla Firefox web browser and the Red Hat Enterprise Linux kernel. We investigated whether software metrics obtained early in the software development life cycle are discriminative of vulnerable code locations, and can guide actions for an organization to take for improvement of code and development team. We also investigated whether the metrics are predictive of vulnerabilities so that prediction models can prioritize validation and verification efforts. The metrics fall into three categories: complexity, code churn, and developer activity metrics. The results indicate that the metrics are discriminative and predictive of vulnerabilities. The predictive model on the three categories of metrics predicted 70.8% of the known vulnerabilities by selecting only 10.9% of the project's files. Similarly, the model for the Red Hat Enterprise Linux kernel found 68.8% of the known vulnerabilities by selecting only 13.0% of the files.

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Human noroviruses (NoVs) are the leading cause of food- and waterborne outbreaks of acute nonbacterial gastroenteritis worldwide. As a result of the lack of a mammalian cell culture model for these viruses, studies on persistence, inactivation, and transmission have been limited to cultivable viruses, including feline calicivirus (FCV). Recently, reports of the successful cell culture of murine norovirus 1 (MNV-1) have provided investigators with an alternative surrogate for human NoVs. In this study, we compared the inactivation profiles of MNV-1 to FCV in an effort to establish the relevance of MNV-1 as a surrogate virus. Specifically, we evaluated (i) stability upon exposure to pH extremes; (ii) stability upon exposure to organic solvents; (iii) thermal inactivation; and (iv) surface persistence under wet and dry conditions. MNV-1 was stable across the entire pH range tested (pH 2 to 10) with less than 1 log reduction in infectivity at pH 2, whereas FCV was inactivated rapidly at pH values < 3 and > 9. FCV was more stable than MNV-1 at 56 degrees C, but both viruses exhibited similar inactivation at 63 and 72 degrees C. Long-term persistence of both viruses suspended in a fecal matrix and inoculated onto stainless steel coupons were similar at 4 degrees C, but at room temperature in solution, MNV-1 was more stable than FCV. The genetic relatedness of MNV-1 to human NoVs combined with its ability to survive under gastric pH levels makes this virus a promising and relevant surrogate for studying environmental survival of human NoVs.

Chiari malformations and syringohydromyelia are an important disease complex in Cavalier King Charles Spaniels. Although abnormalities in caudal fossa morphology are considered major contributors to the development of this disease, limited information exists on the range of morphologies in Cavalier King Charles Spaniels and on the relationship of these to clinically evident disease. Sixty-four Cavalier King Charles Spaniels were studied. Each underwent a neurologic examination and magnetic resonance imaging of the cervical spine and brain. T2-weighted sagittal images were used to determine both the morphologic characteristics and volume of the caudal fossa in each dog. This volume was also analyzed as a percentage of total cranial cavity volume. Each attribute was correlated with neurological grade and presence of syringohydromyelia. Fifteen dogs had neurologic signs, and 59 had morphologic abnormalities of the craniocervical junction. While 27 dogs had syringohydromyelia, 13 of these were clinically normal. Cerebellar herniation and occipital dysplasia were common findings but were not associated with syringohydromyelia. Dorsal compressive lesions were noted at the first and second cervical vertebral junction. Factors associated with the presence of neurologic signs included syringohydromyelia and the ratio of caudal fossa/total cranial cavity volume; dogs with signs had significantly larger syringohydromyelia than asymptomatic dogs. Caudal fossa size was not associated with syringohydromyelia. A positive association was identified between foramen magnum size and length of cerebellar herniation. The prevalence of craniocervical junction abnormalities is high in Cavalier King Charles Spaniels. While several factors are associated with neurologic signs, occipital hypoplasia appears to be the most important factor.

Software fails and fixing it is expensive. Research in failure prediction has been highly successful at modeling software failures. Few models, however, consider the key cause of failures in software: people. Understanding the structure of developer collaboration could explain a lot about the reliability of the final product. We examine this collaboration structure with the developer network derived from code churn information that can predict failures at the file level. We conducted a case study involving a mature Nortel networking product of over three million lines of code. Failure prediction models were developed using test and post-release failure data from two releases, then validated against a subsequent release. One model's prioritization revealed 58% of the failures in 20% of the files compared with the optimal prioritization that would have found 61% in 20% of the files, indicating that a significant correlation exists between filebased developer network metrics and failures.