Template-based program verification and program synthesis

Program verification is the task of automatically generating proofs for a program’s compliance with a given specification. Program synthesis is the task of automatically generating a program that meets a given specification. Both program verification and program synthesis can be viewed as search problems, for proofs and programs, respectively. For these search problems, we present approaches based on user-provided insights in the form of templates. Templates are hints about the syntactic forms of the invariants and programs, and help guide the search for solutions. We show how to reduce the template-based search problem to satisfiability solving, which permits the use of off-the-shelf solvers to efficiently explore the search space. Template-based approaches have allowed us to verify and synthesize programs outside the abilities of previous verifiers and synthesizers. Our approach can verify and synthesize difficult algorithmic textbook programs (e.g., sorting and dynamic programming-based algorithms) and difficult arithmetic programs.     

Thiamine concentrations in lake whitefish eggs from the upper Great Lakes are related to maternal diet

Thiamine deficiency is responsible for reproductive impairment in several species of salmonines in the Great lakes, and is thought to be caused by the consumption of prey containing thiaminase, a thiamine-degrading enzyme. Because thiaminase levels are extremely high in dreissenid mussels, fish that prey on them may be susceptible to thiamine deficiency. We determined thiamine concentrations in lake whitefish Coregonus clupeaformis eggs from the upper Laurentian Great Lakes to assess the potential for thiamine deficiency and to determine if thiamine concentrations in lake whitefish eggs were related to maternal diet. Mean thiamine concentrations in lake whitefish eggs were highest in Lake Huron, intermediate in Lake Superior, and lowest in Lake Michigan. Some fish had thiamine concentrations below putative thresholds for lethal and sublethal effects in salmonines, suggesting that some larval lake whitefish may currently be at risk of at least sublethal effects of low thiamine concentrations, although thiamine thresholds are unknown for lake whitefish. Egg thiamine concentrations in lake whitefish eggs were statistically significantly related to isotopic carbon signatures, suggesting that egg thiamine levels were related to maternal diet, but low egg thiamine concentrations did not appear to be associated with a diet of dreissenids. Egg thiamine concentrations were not statistically significantly related to multifunction oxidase induction, suggesting that lower egg thiamine concentrations in lake whitefish were not related to contaminant exposure.     

Safety, domain independence and translation of complex value database queries

This paper considers the theory of database queries on the complex value data model with external functions. Motivated by concerns regarding query evaluation, we first identify recursive sets of formulas, called embedded allowed, which is a class with desirable properties of “reasonable” queries.We then show that all embedded allowed calculus (or fix-point) queries are domain independent and continuous. An algorithm for translating embedded allowed queries into equivalent algebraic expressions as a basis for evaluating safe queries in all calculus-based query classes has been developed.Finally we discuss the topic of “domain independent query programs”, compare the expressive power of the various complex value query languages and their embedded allowed versions, and discuss the relationship between safety, embedded allowed, and domain independence in the various calculus-based queries.     

Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data

In this study we implemented a comprehensive analysis to validate the MODIS and GOES satellite active fire detection products (MOD14 and WFABBA, respectively) and characterize their major sources of omission and commission errors which have important implications for a large community of fire data users. Our analyses were primarily based on the use of 30 m resolution ASTER and ETM+ imagery as our validation data. We found that at the 50% true positive detection probability mark, WFABBA requires four times more active fire area than is necessary for MOD14 to achieve the same probability of detection, despite the 16× factor separating the nominal spatial resolutions of the two products. Approximately 75% and 95% of all fires sampled were omitted by the MOD14 and WFABBA instantaneous products, respectively; whereas an omission error of 38% was obtained for WFABBA when considering the 30-minute interval of the GOES data. Commission errors for MOD14 and WFABBA were found to be similar and highly dependent on the vegetation conditions of the areas imaged, with the larger commission errors (approximately 35%) estimated over regions of active deforestation. Nonetheless, the vast majority (> 80%) of the commission errors were indeed associated with recent burning activity where scars could be visually confirmed in the higher resolution data. Differences in thermal dynamics of vegetated and non-vegetated areas were found to produce a reduction of approximately 50% in the commission errors estimated towards the hours of maximum fire activity (i.e., early-afternoon hours) which coincided with the MODIS/Aqua overpass. Lastly, we demonstrate the potential use of temporal metrics applied to the mid-infrared bands of MODIS and GOES data to reduce the commission errors found with the validation analyses.     

Use of a dark object concept and support vector machines to automate forest cover change analysis

An automated method was developed for mapping forest cover change using satellite remote sensing data sets. This multi-temporal classification method consists of a training data automation (TDA) procedure and uses the advanced support vector machines (SVM) algorithm. The TDA procedure automatically generates training data using input satellite images and existing land cover products. The derived high quality training data allow the SVM to produce reliable forest cover change products. This approach was tested in 19 study areas selected from major forest biomes across the globe. In each area a forest cover change map was produced using a pair of Landsat images acquired around 1990 and 2000. High resolution IKONOS images and independently developed reference data sets were available for evaluating the derived change products in 7 of those areas. The overall accuracy values were over 90% for 5 areas, and were 89.4% and 89.6% for the remaining two areas. The user's and producer's accuracies of the forest loss class were over 80% for all 7 study areas, demonstrating that this method is especially effective for mapping major disturbances with low commission errors. IKONOS images were also available in the remaining 12 study areas but they were either located in non-forest areas or in forest areas that did not experience forest cover change between 1990 and 2000. For those areas the IKONOS images were used to assist visual interpretation of the Landsat images in assessing the derived change products. This visual assessment revealed that for most of those areas the derived change products likely were as reliable as those in the 7 areas where accuracy assessment was conducted. The results also suggest that images acquired during leaf-off seasons should not be used in forest cover change analysis in areas where deciduous forests exist. Being highly automatic and with demonstrated capability to produce reliable change products, the TDA-SVM method should be especially useful for quantifying forest cover change over large areas.     

Model driven middleware: A new paradigm for developing distributed real-time and embedded systems

Distributed real-time and embedded (DRE) systems have become critical in domains such as avionics (e.g., flight mission computers), telecommunications (e.g., wireless phone services), tele-medicine (e.g., robotic surgery), and defense applications (e.g., total ship computing environments). These types of system are increasingly interconnected via wireless and wireline networks to form systems of systems. A challenging requirement for these DRE systems involves supporting a diverse set of quality of service (QoS) properties, such as predictable latency/jitter, throughput guarantees, scalability, 24x7 availability, dependability, and security that must be satisfied simultaneously in real-time. Although increasing portions of DRE systems are based on QoS-enabled commercial-off-the-shelf (COTS) hardware and software components, the complexity of managing long lifecycles (often ∼15-30 years) remains a key challenge for DRE developers and system integrators. For example, substantial time and effort is spent retrofitting DRE applications when the underlying COTS technology infrastructure changes.This paper provides two contributions that help improve the development, validation, and integration of DRE systems throughout their lifecycles. First, we illustrate the challenges in creating and deploying QoS-enabled component middleware-based DRE applications and describe our approach to resolving these challenges based on a new software paradigm called Model Driven Middleware (MDM), which combines model-based software development techniques with QoS-enabled component middleware to address key challenges faced by developers of DRE systems — particularly composition, integration, and assured QoS for end-to-end operations. Second, we describe the structure and functionality of CoSMIC (Component Synthesis using Model Integrated Computing), which is an MDM toolsuite that addresses key DRE application and middleware lifecycle challenges, including partitioning the components to use distributed resources effectively, validating software configurations, assuring multiple simultaneous QoS properties in real-time, and safeguarding against rapidly changing technology.     

Valuing pilot projects in a learning by investing framework: An approximate dynamic programming approach

We introduce a general discrete time dynamic framework to value pilot project investments that reduce idiosyncratic uncertainty with respect to the final cost of a project. The model generalizes different settings introduced previously in the literature by incorporating both market and technical uncertainty and differentiating between the commercial phase and the pilot phase of a project. In our model, the pilot phase requires N$N$ stages of investment for completion. With this distinction we are able to frame the problem as a compound perpetual Bermudan option. We work in an incomplete markets setting where market uncertainty is spanned by tradable assets and technical uncertainty is idiosyncratic to the firm. The value of the option to invest as well as the optimal exercise policy are solved by an approximate dynamic programming algorithm that relies on the independence of the state variables increments. We prove the convergence of our algorithm and derive a theoretical bound on how the errors compound as the number of stages of the pilot phase is increased. We implement the algorithm for a simplified version of the model where revenues are fixed, providing an economic interpretation of the effects of the main parameters driving the model. In particular, we explore how the value of the investment opportunity and the optimal investment threshold are affected by changes in market volatility, technical volatility, the learning coefficient, the drift rate of costs and the time to completion of a pilot stage.     

Development of a Weather Forecasting Code: A Case Study

Computational science is increasingly supporting advances in scientific and engineering knowledge. The unique constraints of these types of projects result in a development process that differs from the process more traditional information technology projects use. This article reports the results of the sixth case study conducted under the support of the Darpa High Productivity Computing Systems Program. The case study aimed to investigate the technical challenges of code development in this environment, understand the use of development tools, and document the findings as concrete lessons learned for other developers' benefit. The project studied here is a major component of a weather forecasting system of systems. It includes complex behavior and interaction of several individual physical systems (such as the atmosphere and the ocean). This article describes the development of the code and presents important lessons learned.     

Linear actuation in coextruded dielectric elastomer tubes

Cylindrical fibre actuators have been constructed by a coextrusion method using a thermoplastic polyurethane wall and a conductive grease filler. These actuators may be operated as single fibres or bundled together as actuating ropes. Key results include the validation of Carpi’s wall pressure model [F. Carpi, D.D. Rossi, Dielectric elastomer cylindrical actuators: electromechanical modelling and experimental evaluation, Mater. Sci. Eng. C-Biomimetic Supramol. Syst. 24 (2004) 555–562] and the proof-of-concept demonstration of a technique that can be used for producing inexpensive dielectric elastomer actuators on an industrial scale.     

A dynamic workflow framework for mass customization using web service and autonomous agent techniques

Custom software development and maintenance is one of the key expenses associated with developing automated systems for mass customization. This paper presents a method for reducing the risk associated with this expense by developing a flexible environment for determining and executing dynamic workflow paths. Strategies for developing an autonomous agent-based framework and for identifying and creating web services for specific process tasks are presented. The proposed methods are outlined in two different case studies to illustrate the approach for both a generic process with complex workflow paths and a more specific sequential engineering process.