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The last few years have seen a resurgence of interest in the use of symbolic execution--program analysis technique developed more than three decades ago to analyze program execution paths. However, symbolic execution remains an expensive technique and scaling it remains a key technical challenge. There are two key factors that contribute to its cost: (1) the number of paths that need to be explored and (2) the cost of constraint solving, which is typically required for each path explored. Our insight is that the cost of symbolic execution can be reduced by an incremental approach, which uses static analysis and dynamic analysis to focus on relevant parts of code and reuse previous analysis results, thereby addressing both the key cost factors of symbolic execution. This dissertation presents Memoized Incremental Symbolic Execution, a novel approach that embodies our insight. Using symbolic execution in practice often requires several successive runs of the technique on largely similar underlying problems where successive problems differ due to some change, which may be to code, e.g., to fix a bug, to analysis parameters, e.g., to increase the path exploration depth, or to correctness properties, e.g., to check against stronger specifications that are written as assertions in code. Memoized Incremental Symbolic Execution, a three-fold approach, leverages the similarities in the successive problems to reduce the total cost of applying the technique. Our prototype tool-set is based on the Symbolic PathFinder. Experimental results show that Memoized Incremental Symbolic Execution enhances the efficacy of symbolic execution. / text

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This thesis concerns with change detection problematics in digital images captured under indoor conditions with an ordinary integrated camera in two consecutive moments. All challenges that accompany this problem will be discussed, starting with preprocessing and arriving to evaluation of the results. Currently used methods from this field are described and compared with each other such as differencing and LCP (Local Correlation Peak). A novel method, based on LTP descriptors, effectively solving this problem is proposed in this work. The proposed method is then tested on real data. The results of this tests are discussed subsequently. Besides the change detection method a method for parallax error minimization is proposed here.

MODCONV is a FORTRAN Computer code using the primitive form of the conservation equations for natural convection in porous medium to calculate the velocity and temperature distribution in the moderator of a typical CANDU reactor under normal and shut down operations, as well as postulated LOCA for which the rupture in the system is external to the core. Appropriate velocities are imposed at the boundary walls so that the free convection equations set can be used to model a mixed convection problem. Purely explicit, donor cell finite differencing scheme is used. A heat exchanger model using NTU method is also included to give a realistic inflow temperature for the moderator. The heat load distribution is calculated according to a channel power map, but can be redefined through input. / Thesis / Master of Engineering (MEngr)

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Many image processing algorithms exist that can accurately detect humans and other objects such as vehicles and animals. Many of these algorithms require large amounts of processing often requiring hardware acceleration with powerful central processing units (CPUs), graphics processing units (GPUs), field programmable gate arrays (FPGAs), etc. Implementing an algorithm that can detect objects such as humans at longer ranges makes these hardware requirements even more strenuous as the numbers of pixels necessary to detect objects at both close ranges and long ranges is greatly increased. Comparing the performance of different low-power implementations can be used to determine a trade-off between performance and power. An image differencing algorithm is proposed along with selected low-power hardware that is capable of detected humans at ranges of 500 m. Multiple versions of the detection algorithm are implemented on the selected hardware and compared for run-time performance on a low-power system.

Throughout its lifetime, software must be changed for many reasons, such as bug fixing, performance tuning, and code restructuring. Testing modified software is the main activity performed to gain confidence that changes behave as they are intended and do not have adverse effects on the rest of the software. A fundamental problem of testing evolving software is determining whether test suites adequately exercise changes and, if not, providing suitable guidance for generating new test inputs that target the modified behavior. Existing techniques evaluate the adequacy of test suites based only on control- and data-flow testing criteria. They do not consider the effects of changes on program states and, thus, are not sufficiently strict to guarantee that the modified behavior is exercised. Also, because of the lack of this guarantee, these techniques can provide only limited guidance for generating new test inputs. This research has developed techniques that will assist testers in testing evolving software and provide confidence in the quality of modified versions. In particular, this research has developed a technique to identify testing requirements that ensure that the test cases satisfying them will result in different program states at preselected parts of the software. This research has also developed supporting techniques for identifying testing requirements. Such techniques include (1) a differencing technique, which computes differences and correspondences between two software versions and (2) two dynamic-impact-analysis techniques, which identify parts of software that are likely affected by changes with respect to a set of executions.

Understanding the impact of changes made daily by development teams working on large-scale software products is a challenge faced by many organizations nowadays. Development efficiency can be severely affected by the increase in fragility that can creep in as products evolve and become more complex. Processes, such as gated check-in mechanisms, can be put in place to detect problematic changes before submission, but are usually limited in effectiveness due to their reliance on statically-defined sets of tests. Traditional change-impact analysis techniques can be combined with information gathered at run-time in order to create a system that can select tests for change verification. This report provides the high-level architecture of a system, named Ratchet, that combines static analysis of C++ programs, enabled by the reuse of the Clang compiler frontend, and code-coverage information gathered from automated test runs, in order to automatically select and schedule tests that exercise functions and methods possibly affected by the change. Prototype implementations of the static-analysis components of the system are provided, along with a basic evaluation of their capabilities through synthetic examples. / text

xi, 54 p. : ill. (some col.) / On the Middle Fork John Day River (MFJD), a low gradient, meandering river in eastern Oregon, restoration includes engineered log structures intended to increase in-stream complexity and habitat diversity. Effects of log structures on riverbed topography can be captured through repeat topographic surveys, digital elevation model (DEM) of differencing (DoD), and aerial imagery. This study evaluates the (1) potential for remote sensing analysis, (2) effect of survey point density on DEMs, and (3) application of DoDs, in monitoring riverbed changes in the MFJD. An average point spacing and density finer than 0.50m and 1.25pts/m<super>2</super> captures riverbed complexities. Although elevation changes were expected to be minimal, DoDs revealed -0.9 to 0.5m elevation changes associated with log structure designs. Incorporating numerical thresholds into future monitoring survey methods will improve the modeling of MFJD riverbed surfaces. Monitoring riverbed changes through DoDs can inform improvements to future restoration design and the effectiveness of log structures. / Committee in charge: Patricia McDowell, Chairperson; Andrew Marcus, Member