Predicting Accurate and Actionable Static Analysis Warnings: An Experimental Approach

Static analysis tools report software defects that may or may not be detected by other verification methods. Two challenges complicating the adoption of these tools are spurious false positive warnings and legitimate warnings that are not acted on. This paper reports automated support to help address these challenges using logistic regression models that predict the foregoing types of warnings from signals in the warnings and implicated code. Because examining many potential signaling factors in large software development settings can be expensive, we use a screening methodology to quickly discard factors with low predictive power and cost-effectively build predictive models. Our empirical evaluation indicates that these models can achieve high accuracy in predicting accurate and actionable static analysis warnings, and suggests that the models are competitive with alternative models built without screening.

Infrastructure Support for Controlled Experimentation with Software Testing and Regression Testing Techniques

Where the creation, understanding, and assessment of software testing and regression testing techniques are concerned, controlled experimentation is an indispensable research methodology. Obtaining the infrastructure necessary to support such experimentation, however, is difficult and expensive. As a result, progress in experimentation with testing techniques has been slow, and empirical data on the costs and effectiveness of techniques remains relatively scarce. To help address this problem, we have been designing and constructing infrastructure to support controlled experimentation with testing and regression testing techniques. This paper reports on the challenges faced by researchers experimenting with testing techniques, including those that inform the design of our infrastructure. The paper then describes the infrastructure that we are creating in response to these challenges, and that we are now making available to other researchers, and discusses the impact that this infrastructure has and can be expected to have.

Revealing the Copy and Paste Habits of End Users

Transferring data across applications is a common end user task, and copying and pasting via the clipboard lets users do so relatively easily. Using the clipboard, however, can also introduce inefficiencies and errors in user tasks. To help researchers and tool developers understand and address these problems, we studied how end users interact with the clipboard through cut, copy, and paste actions. This study was performed by logging clipboard interactions while end users performed everyday tasks. From the clipboard usage data, we have identified several usage patterns that describe how data is transferred within the desktop environment. Such patterns help us understand end user behavior and indicate areas in which clipboard support tools can be improved.

Incorporating Varying Test Costs and Fault Severities into Test Case Prioritization

Test case prioritization techniques schedule test cases for regression testing in an order that increases their ability to meet some performance goal. One performance goal, rate offault detection, measures how quickly faults are detected within the testing process. In previous work we provided a metric, APFD, for measuring rate of fault detection, and techniques for prioritizing test cases to improve APFD, and reported the results of experiments using those techniques. This metric and these techniques, however, applied only in cases in which test costs and fault severity are uniform. In this paper, we present a new metric for assessing the rate of fault detection of prioritized test cases, that incorporates varying test case and fault costs. We present the results of a case study illustrating the application of the metric. This study raises several practical questions that might arise in applying test case prioritization; we discuss how practitioners could go about answering these questions.

Balancing Exploration and Exploitation: A New Algorithm for Active Machine Learning

Active machine learning algorithms are used when large numbers of unlabeled examples are available and getting labels for them is costly (e.g. requiring consulting a human expert). Many conventional active learning algorithms focus on refining the decision boundary, at the expense of exploring new regions that the current hypothesis misclassifies. We propose a new active learning algorithm that balances such exploration with refining of the decision boundary by dynamically adjusting the probability to explore at each step. Our experimental results demonstrate improved performance on data sets that require extensive exploration while remaining competitive on data sets that do not. Our algorithm also shows significant tolerance of noise.

Cross-Layer Packet Size Optimization for Wireless Terrestrial, Underwater, and Underground Sensor Networks

In this paper, a cross-layer solution for packet size optimization in wireless sensor networks (WSN) is introduced such that the effects of multi-hop routing, the broadcast nature of the physical wireless channel, and the effects of error control techniques are captured. A key result of this paper is that contrary to the conventional wireless networks, in wireless sensor networks, longer packets reduce the collision probability. Consequently, an optimization solution is formalized by using three different objective functions, i.e., packet throughput, energy consumption, and resource utilization. Furthermore, the effects of end-to-end latency and reliability constraints are investigated that may be required by a particular application. As a result, a generic, cross-layer optimization framework is developed to determine the optimal packet size in WSN. This framework is further extended to determine the optimal packet size in underwater and underground sensor networks. From this framework, the optimal packet sizes under various network parameters are determined.

Nebraska LEAD XXI Fellow/Spouses Dinner

“Nearly all men can stand adversity, but if you want to test a man’s character give him power.” That quote, by my hero Abraham Lincoln, is one I think all leaders should remember and reflect on regularly in their life, and so I pass it on to each of you. I wish each member of this LEAD group the character to use power wisely, with compassion and integrity, and a strong-sense of justice and fair play.

Lincoln Downtown Rotary Club

Good afternoon, and thank you for inviting me to be here with you today. One of the things I'm enjoying most in my new position as University of Nebraska Vice President of Agriculture and Natural Resources and Harlan Vice Chancellor of the Institute of Agriculture and Natural Resources is meeting the people who live in this state, in urban and rural areas, from Scottsbluff to Omaha, from Lincoln to Curtis, and at any number of towns - north, south, east, west - in between.

Social Cognition and Interaction Training (SCIT) for Individuals with Schizophrenia Spectrum Disorders in Outpatient Treatment Settings

The role of social cognition in severe mental illness (SMI) has gained much attention, especially over the last decade. The impact of deficits in socio-cognitive functioning has been found to have detrimental effects on key areas of day-to-day functioning in individuals with SMI, such as gaining and maintaining employment and overall experienced quality of life. Treatment of individuals with SMI is challenging, as the presentation of individual signs and symptoms is rather heterogeneous. There are several treatment approaches addressing deficits ranging from broader social and interpersonal functioning to neurocognitive and more intrapersonal functioning. As research in the domain of social cognition continues to identify specific deficits and its functional detriments, treatment options need to evolve to better target identified functional deficits. Social Cognition and Interaction Training (SCIT) was recently developed to address specific socio-cognitive deficits in an inpatient population of individuals with schizophrenia-spectrum disorders. This study applied SCIT in an outpatient SMI population as many deficits remain after individuals’ symptoms are less severe and overall functioning is more stable than during the acute inpatient phase of their rehabilitation. Specifically, this study has two objectives. First, to demonstrate that deficits in social cognition persist after the acute phase of illness has abated. Second, to demonstrate that these deficits can be ameliorated via targeted treatment such as SCIT. Data was gathered in local outpatient treatment settings serving a heterogeneous SMI population. Adviser: William D. Spaulding

Time series analysis of jaw muscle contraction and tissue deformation during mastication in miniature pigs

Masticatory muscle contraction causes both jaw movement and tissue deformation during function. Natural chewing data from 25 adult miniature pigs were studied by means of time series analysis. The data set included simultaneous recordings of electromyography (EMG) from bilateral masseter (MA), zygomaticomandibularis (ZM) and lateral pterygoid muscles, bone surface strains from the left squamosal bone (SQ), condylar neck (CD) and mandibular corpus (MD), and linear deformation of the capsule of the jaw joint measured bilaterally using differential variable reluctance transducers. Pairwise comparisons were examined by calculating the cross-correlation functions. Jaw-adductor muscle activity of MA and ZM was found to be highly cross-correlated with CD and SQ strains and weakly with MD strain. No muscle’s activity was strongly linked to capsular deformation of the jaw joint, nor were bone strains and capsular deformation tightly linked. Homologous muscle pairs showed the greatest synchronization of signals, but the signals themselves were not significantly more correlated than those of non-homologous muscle pairs. These results suggested that bone strains and capsular deformation are driven by different mechanical regimes. Muscle contraction and ensuing reaction forces are probably responsible for bone strains, whereas capsular deformation is more likely a product of movement.

学術機関リポジトリでのオリジナルコンテンツの公開

学術機関リポジトリ（Institutional Repository、IR）は主に、学術雑誌、記念論文集、論文集など、他の場所で公開済みの学術的コンテンツを再公開する手段として開発され促進されてきた。本書では、他ではまだ公開していない資料の最初の公開場所にIRを使用する方法について考察し、学術的公開のための発展性のある「第一手段」として、また従来の商業出版社または大学出版局の代わりとなる既存の手段としてIRを利用できる可能性を評価する。Serials Review 2008; 34:27-30. Translation courtesy of Library Liaison Team, National Institute of Informatics, Japan, Cyber Science Infrastructure Development Department, Scholarly and Academic Information Division.

QUANTITATIVE TRAIT LOCI FOR AGRONOMIC AND END-USE QUALITY PERFORMANCE AND THE EFFECT OF SOILBORNE WHEAT MOSAIC VIRUS IN A HARD WINTER WHEAT POPULATION IN NEBRASKA

To better understand agronomic and end-use quality in wheat (Triticum aestivum L.) we developed a population containing 154 F6:8 recombinant inbred lines (RILs) from the cross TAM107-R7/Arlin. The parental lines and RILs were phenotyped at six environments in Nebraska and differed for resistance to Wheat soilborne mosaic virus (WSBMV), morphological, agronomic, and end-use quality traits. Additionally, a 2300 cM genome-wide linkage map was created for quantitative trait loci (QTL) analysis. Based on our results across multiple environments, the best RILs could be used for cultivar improvement. The population and marker data are publicly available for interested researchers for future research. The population was used to determine the effect of WSBMV on agronomic and end-use quality and for the mapping of a resistance locus. Results from two infected environments showed that all but two agronomic traits were significantly affected by the disease. Specifically, the disease reduced grain yield by 30% of susceptible RILs and they flowered 5 d later and were 11 cm shorter. End-use quality traits were not negatively affected but flour protein content was increased in susceptible RILs. The resistance locus SbmTmr1 mapped to 27.1 cM near marker wPt-5870 on chromosome 5DL using ELISA data. Finally, we investigated how WSBMV affected QTL detection in the population. QTLs were mapped at two WSBMV infected environments, four uninfected environments, and in the resistant and susceptible RIL subpopulations in the infected environments. Fifty-two significant (LOD≥3) QTLs were mapped in RILs at uninfected environments. Many of the QTLs were pleiotropic or closely linked at 6 chromosomal regions. Forty-seven QTLs were mapped in RILs at WSBMV infected environments. Comparisons between uninfected and infected environments identified 20 common QTLs and 21 environmentally specific QTLs. Finally, 24 QTLs were determined to be affected by WSBMV by comparing the subpopulations in QTL analyses within the same environment. The comparisons were statistically validated using marker by disease interactions. These results showed that QTLs can be affected by WSBMV and careful interpretation of QTL results is needed where biotic stresses are present. Finally, beneficial QTLs not affected by WSBMV or the environment are candidates for marker-assisted selection.

Impact of the Internet on Final Year Students' Research: A Case Study of Covenant University, Ota, Nigeria

The 21st century is characterized by advancements in information and communication technology (ICT), including the Internet. Final year students of Covenant University implore the use of the Internet in writing their projects. This paper examines the extent of accessibility and use of the Internet by these students and the impact the Internet has on their projects. A questionnaire was used for data collection. A total of 150 questionaires were distributed to students from each of the three colleges in the university. The results show that all respondents used the Internet for their project work. Nearly all indicated that the Internet has an impact on their projects, especially in the areas of quality of work, speed, time economy, and recency of materials. Recommendations for improvement include provision of wireless Internet access points and training and retraining of students to acquire computer and Internet search skills.

Linkage & Selective Mapping and QTL Analysis in a Harosoy x Clark population of 300 RILs

Four of the 12 major Glycine max ancestors of all modern elite U.S.A. soybean cultivars were the grandparents of Harosoy and Clark, so a Harosoy x Clark population would include some of that genetic diversity. A mating of eight Harosoy and eight Clark plants generated eight F1 plants. The eight F1:2 families were advanced via a plant-to-row selfing method to produce 300 F6-derived RILs that were genotyped with 266 SSR, 481 SNP, and 4 classical markers. SNPs were genotyped with the Illumina 1536-SNP assay. Three linkage maps, SSR, SNP, and SSR-SNP, were constructed with a genotyping error of < 1 %. Each map was compared with the published soybean consensus map. The best subset of 94 RILs for a high-resolution framework (joint) map was selected based on the expected bin length statistic computed with MapPop. The QTLs of seven traits measured in a 2-year replicated performance trial of the 300 RILs were identified using composite interval mapping (CIM) and multiple-interval mapping (MIM). QTL x Year effects in multiple trait analysis were compared with results of multiple-interval mapping. QTL x QTL effects were identified in MIM.

SimSight: A Virtual Machine Based Dynamic Call Graph Generator

One problem with using component-based software development approach is that once software modules are reused over generations of products, they form legacy structures that can be challenging to understand, making validating these systems difficult. Therefore, tools and methodologies that enable engineers to see interactions of these software modules will enhance their ability to make these software systems more dependable. To address this need, we propose SimSight, a framework to capture dynamic call graphs in Simics, a widely adopted commercial full-system simulator. Simics is a software system that simulates complete computer systems. Thus, it performs nearly identical tasks to a real system but at a much lower speed while providing greater execution observability. We have implemented SimSight to generate dynamic call graphs of statically and dynamically linked functions in x86/Linux environment. A case study illustrates how we can use SimSight to identify sources of software errors. We then evaluate its performance using 12 integer programs from SPEC CPU2006 benchmark suite.