A pointcut-based coverage analysis approach for aspect-oriented programs

Aspect-oriented programming (AOP) is a promising technology that supports separation of crosscutting concerns (i.e., functionality that tends to be tangled with, and scattered through the rest of the system). In AOP, a method-like construct named advice is applied to join points in the system through a special construct named pointcut. This mechanism supports the modularization of crosscutting behavior; however, since the added interactions are not explicit in the source code, it is hard to ensure their correctness. To tackle this problem, this paper presents a rigorous coverage analysis approach to ensure exercising the logic of each advice - statements, branches, and def-use pairs - at each affected join point. To make this analysis possible, a structural model based on Java bytecode - called PointCut-based Del-Use Graph (PCDU) - is proposed, along with three integration testing criteria. Theoretical, empirical, and exploratory studies involving 12 aspect-oriented programs and several fault examples present evidence of the feasibility and effectiveness of the proposed approach. (C) 2010 Elsevier Inc. All rights reserved.

Fault Coverage-Driven Incremental Test Generation

In this paper, we consider a classical problem of complete test generation for deterministic finite-state machines (FSMs) in a more general setting. The first generalization is that the number of states in implementation FSMs can even be smaller than that of the specification FSM. Previous work deals only with the case when the implementation FSMs are allowed to have the same number of states as the specification FSM. This generalization provides more options to the test designer: when traditional methods trigger a test explosion for large specification machines, tests with a lower, but yet guaranteed, fault coverage can still be generated. The second generalization is that tests can be generated starting with a user-defined test suite, by incrementally extending it until the desired fault coverage is achieved. Solving the generalized test derivation problem, we formulate sufficient conditions for test suite completeness weaker than the existing ones and use them to elaborate an algorithm that can be used both for extending user-defined test suites to achieve the desired fault coverage and for test generation. We present the experimental results that indicate that the proposed algorithm allows obtaining a trade-off between the length and fault coverage of test suites.

[Coverage of pressure sores with free flaps]

INTRODUCTION: The coverage of recurrent pressure sores with unstable scar in the surrounding tissue is still an unsolved problem in the literature. Local and regional transfer of tissue often does not meet the requirements of the tissue deficit. Especially in recurrent pressure sores, the adjacent skin has already been consumed due to multiple surgeries. As a good alternative, the microsurgical transfer of flaps offers viable tissue to cover even large pressure sores. METHODS: We performed a total of six free flaps in five patients who suffered from intractable pressure sores in the hip region. The age of the patients was between 41 and 63 years. The defect size varied between 6 x 6 cm and 25 x 30 cm. Two combined myocutaneous scapula-latissimus dorsi, two myocutaneous latissimus dorsi, one anteromedial thigh, and one rectus femoris flap were used to cover the defects. RESULTS: The average follow-up time was 29 months. Flaps provided stable coverage in four of five patients at 12-month follow-up. There was one subtotal flap necrosis that was subsequently treated with split-thickness skin grafting. CONCLUSION: In this series of five patients with six free flaps, we were able to show that the microsurgical transfer of tissue is a valuable option in the treatment of difficult pressure sores. Even in older and debilitated patients, this method is a good alternative to conventional local flaps.

Aerial Coverage Path Planning applied to Mapping

In the last decade we have seen how small and light weight aerial platforms - aka, Mini Unmanned Aerial Vehicles (MUAV) - shipped with heterogeneous sensors have become a 'most wanted' Remote Sensing (RS) tool. Most of the off-the-shelf aerial systems found in the market provide way-point navigation. However, they do not rely on a tool that compute the aerial trajectories considering all the aspects that allow optimizing the aerial missions. One of the most demanded RS applications of MUAV is image surveying. The images acquired are typically used to build a high-resolution image, i.e., a mosaic of the workspace surface. Although, it may be applied to any other application where a sensor-based map must be computed. This thesis provides a study of this application and a set of solutions and methods to address this kind of aerial mission by using a fleet of MUAVs. In particular, a set of algorithms are proposed for map-based sampling, and aerial coverage path planning (ACPP). Regarding to map-based sampling, the approaches proposed consider workspaces with different shapes and surface characteristics. The workspace is sampled considering the sensor characteristics and a set of mission requirements. The algorithm applies different computational geometry approaches, providing a unique way to deal with workspaces with different shape and surface characteristics in order to be surveyed by one or more MUAVs. This feature introduces a previous optimization step before path planning. After that, the ACPP problem is theorized and a set of ACPP algorithms to compute the MUAVs trajectories are proposed. The problem addressed herein is the problem to coverage a wide area by using MUAVs with limited autonomy. Therefore, the mission must be accomplished in the shortest amount of time. The aerial survey is usually subject to a set of workspace restrictions, such as the take-off and landing positions as well as a safety distance between elements of the fleet. Moreover, it has to avoid forbidden zones to y. Three different algorithms have been studied to address this problem. The approaches studied are based on graph searching, heuristic and meta-heuristic approaches, e.g., mimic, evolutionary. Finally, an extended survey of field experiments applying the previous methods, as well as the materials and methods adopted in outdoor missions is presented. The reported outcomes demonstrate that the findings attained from this thesis improve ACPP mission for mapping purpose in an efficient and safe manner.

Aerial Coverage Path Planning applied to Mapping

In the last decade we have seen how small and light weight aerial platforms - aka, Mini Unmanned Aerial Vehicles (MUAV) - shipped with heterogeneous sensors have become a 'most wanted' Remote Sensing (RS) tool. Most of the off-the-shelf aerial systems found in the market provide way-point navigation. However, they do not rely on a tool that compute the aerial trajectories considering all the aspects that allow optimizing the aerial missions. One of the most demanded RS applications of MUAV is image surveying. The images acquired are typically used to build a high-resolution image, i.e., a mosaic of the workspace surface. Although, it may be applied to any other application where a sensor-based map must be computed. This thesis provides a study of this application and a set of solutions and methods to address this kind of aerial mission by using a fleet of MUAVs. In particular, a set of algorithms are proposed for map-based sampling, and aerial coverage path planning (ACPP). Regarding to map-based sampling, the approaches proposed consider workspaces with different shapes and surface characteristics. The workspace is sampled considering the sensor characteristics and a set of mission requirements. The algorithm applies different computational geometry approaches, providing a unique way to deal with workspaces with different shape and surface characteristics in order to be surveyed by one or more MUAVs. This feature introduces a previous optimization step before path planning. After that, the ACPP problem is theorized and a set of ACPP algorithms to compute the MUAVs trajectories are proposed. The problem addressed herein is the problem to coverage a wide area by using MUAVs with limited autonomy. Therefore, the mission must be accomplished in the shortest amount of time. The aerial survey is usually subject to a set of workspace restrictions, such as the take-off and landing positions as well as a safety distance between elements of the fleet. Moreover, it has to avoid forbidden zones to y. Three different algorithms have been studied to address this problem. The approaches studied are based on graph searching, heuristic and meta-heuristic approaches, e.g., mimic, evolutionary. Finally, an extended survey of field experiments applying the previous methods, as well as the materials and methods adopted in outdoor missions is presented. The reported outcomes demonstrate that the findings attained from this thesis improve ACPP mission for mapping purpose in an efficient and safe manner.

Coverage and invariance for the biological control of pests in mediterranean greenhouses

A major problem related to the treatment of ecosystems is that they have no available mathematical formalization. This implies that many of their properties are not presented as short, rigorous modalities, but rather as long expressions which, from a biological standpoint, totally capture the significance of the property, but which have the disadvantage of not being sufficiently manageable, from a mathematical standpoint. The interpretation of ecosystems through networks allows us to employ the concepts of coverage and invariance alongside other related concepts. The latter will allow us to present the two most important relations in an ecosystem – predator–prey and competition – in a different way. Biological control, defined as “the use of living organisms, their resources or their products to prevent or reduce loss or damage caused by pests”, is now considered the environmentally safest and most economically advantageous method of pest control (van Lenteren, 2011). A guild includes all those organisms that share a common food resource (Polis et al., 1989), which in the context of biological control means all the natural enemies of a given pest. There are several types of intraguild interactions, but the one that has received most research attention is intraguild predation, which occurs when two organisms share the same prey while at the same time participating in some kind of trophic interaction. However, this is not the only intraguild relationship possible, and studies are now being conducted on others, such as oviposition deterrence. In this article, we apply the developed concepts of structural functions, coverage, invariant sets, etc. (Lloret et al., 1998, Esteve and Lloret, 2006a, Esteve and Lloret, 2006b and Esteve and Lloret, 2007) to a tritrophic system that includes aphids, one of the most damaging pests and a current bottleneck for the success of biological control in Mediterranean greenhouses.

An Efficient and Verifiable Solution to the Millionaire Problem

A new solution to the millionaire problem is designed on the base of two new techniques: zero test and batch equation. Zero test is a technique used to test whether one or more ciphertext contains a zero without revealing other information. Batch equation is a technique used to test equality of multiple integers. Combination of these two techniques produces the only known solution to the millionaire problem that is correct, private, publicly verifiable and efficient at the same time.