Jonathan Stallings

Spatial Distribution of Brown Marmorated Stink Bug (Hemiptera: Pentatomidae) Injury at Harvest in Mid-Atlantic Apple Orchards

ABSTRACT Brown marmorated stink bug, Halyomorpha halys (Stål), injury to late-season apple cultivars was measured at harvest in 2011 and 2012 in commercial orchards in four mid-Atlantic states. In each orchard block, a border zone (adjacent to woods), an interior zone (near orchard center), and an intermediate zone (between border and interior zones) comprised 1–3 tree rows per zone, depending on block size. Just before commercial harvest, 10 fruit were sampled from the upper, middle, and lower third of the canopy from five trees in each zone. After 3–5 wk in cold storage, fruit were examined for external and internal injury, and severity of internal injury (number of injury sites per fruit) from H. halys. A zero-inflated negative binomial model accounted for significant variation among the orchards and showed that apples from the upper canopy of border zone trees had the highest probability of experiencing external and internal injury. A minor interaction was detected among the orchards and zones for injury prevalence and severity, but there was no evidence of an orchard showing less expected injury in the border zone compared with other zones. Adjusting for orchard-to-orchard variation, differences in injury distributions among the zones and canopies were primarily due to injury prevalence rather than expected injury severity. The implications of these results to scouting and managing H. halys in eastern apple orchards are discussed.

Under-Trellis Cover Crop and Rootstock Affect Growth, Yield Components, and Fruit Composition of Cabernet Sauvignon

We compared the effectiveness of an under-trellis cover crop treatment (CC, Festuca rubra) and an 85-cm-wide herbicide-treated strip treatment (HTS) and rootstock (101-14, 420-A, or riparia) for regulating vegetative growth and improving fruit composition in Cabernet Sauvignon over a six- to seven-year period of data collection. The cover crop reduced average vine pruning weight by 26% and increased fruit exposure by 35% compared to the HTS floor management scheme. Vines grafted to riparia rootstock had pruning weights that were lower than those of vines grafted to 101-14 in two years; however, effects of rootstock were insignificant when averaged over the seven-year experiment. There was a measurable crop yield penalty for the CC floor management: vines grown with CC averaged 610 kg/ha/year lower crop yields, and had reduced cluster weight, berries per cluster, and berry weight compared to vines in the HTS floor management. Riparia rootstock increased berry weight, cluster weight, and crop yield per vine compared to 101-14. Fruit from vines grown with CC averaged greater soluble solids compared to vines grown with HTS. Rootstock 420-A produced fruit with lower pH than fruit from 101-14 or riparia vines. Compared to 420-A, inconsistent increases in grape anthocyanins and phenolics were observed in riparia (both) and 101-14 (phenolics only). The use of an under-trellis cover crop favorably reduced vine size, especially during the earlier years of the experiment.

DIGS: A Framework for Discovering Goals for Security Requirements Engineering

Context: The security goals of a software system provide a foundation for security requirements engineering. Identifying security goals is a process of iteration and refinement, leveraging the knowledge and expertise of the analyst to secure not only the core functionality but the security mechanisms as well. Moreover, a comprehensive security plan should include goals for not only preventing a breach, but also for detecting and appropriately responding in case a breach does occur. Goal: The objective of this research is to support analysts in security requirements engineering by providing a framework that supports a systematic and comprehensive discovery of security goals for a software system. Method: We develop a framework, Discovering Goals for Security (DIGS), that models the key entities in information security, including assets and security goals. We systematically develop a set of security goal patterns that capture multiple dimensions of security for assets. DIGS explicitly captures the relations and assumptions that underlie security goals to elicit implied goals. We map the goal patterns to NIST controls to help in operationalizing the goals. We evaluate DIGS via a controlled experiment where 28 participants analyzed systems from mobile banking and human resource management domains. Results: Participants considered security goals commensurate to the knowledge available to them. Although the overall recall was low given the empirical constraints, participants using DIGS identified more implied goals and felt more confident in completing the task. Conclusion: Explicitly providing the additional knowledge for the identification of implied security goals significantly increased the chances of discovering such goals, thereby improving coverage of stakeholder security requirements, even if they are unstated.

Poster: Defect Prediction Metrics for Infrastructure as Code Scripts in DevOps

Use of infrastructure as code (IaC) scripts helps software teams manage their configuration and infrastructure automatically. Information technology (IT) organizations use IaC scripts to create and manage automated deployment pipelines to deliver services rapidly. IaC scripts can be defective, resulting in dire consequences, such as creating wide-scale service outages for end-users. Prediction of defective IaC scripts can help teams to mitigate defects in these scripts by prioritizing their inspection efforts. The goal of this paper is to help software practitioners in prioritizing their inspection efforts for infrastructure as code (IaC) scripts by proposing defect prediction model-related metrics. IaC scripts use domain specific languages (DSL) that are fundamentally different from object-oriented programming (OOP) languages. Hence, the OOP-based metrics that researchers used in defect prediction might not be applicable for IaC scripts. We apply Constructivist Grounded Theory (CGT) on defect-related commits mined from version control systems to identify metrics suitable for IaC scripts. By applying CGT, we identify 18 metrics. Of these metrics, 13 are related to IaC, for example, count of string occurrences in a script. Four of the identified metrics are related to churn, and one metric is lines of code.

Interactions Between Transfemoral Amputees and a Powered Knee Prosthesis During Load Carriage

Machines and humans become mechanically coupled when lower limb amputees walk with powered prostheses, but these two control systems differ in adaptability. We know little about how they interact when faced with real-world physical demands (e.g. carrying loads). Here, we investigated how each system (i.e. amputee and powered prosthesis) responds to changes in the prosthesis mechanics and gravitational load. Five transfemoral amputees walked with and without load (i.e. weighted backpack) and a powered knee prosthesis with two pre-programmed controller settings (i.e. for load and no load). We recorded subjects’ kinematics, kinetics, and perceived exertion. Compared to the no load setting, the load setting reduced subjects’ perceived exertion and intact-limb stance time when they carried load. When subjects did not carry load, their perceived exertion and gait performance did not significantly change with controller settings. Our results suggest transfemoral amputees could benefit from load-adaptive powered knee controllers, and controller adjustments affect amputees more when they walk with (versus without) load. Further understanding of the interaction between powered prostheses, amputee users, and various environments may allow researchers to expand the utility of prostheses beyond simple environments (e.g. firm level ground without load) that represent only a subset of real-world environments.