PShare: Ensuring location privacy in non-trusted systems through multi-secret sharing

Location-based applications such as Facebook Places, Foursquare, or Loopt typically use location services to manage mobile object positions. However, exposing precise user positions raises user privacy concerns, especially if location service providers are not fully trusted. To enable the secure management of private user positions in non-trusted systems, we present two novel position sharing approaches based on the concept of multi-secret sharing. We improve existing geometric position sharing approaches by Dürr et al. [2] and Skvortsov et al. [3] by considering continuous position updates and by increasing the robustness against various attacks. Furthermore, we present the first position sharing approach for symbolic location models.     

The shadow approach: An orphan detection protocol for mobile agents

Orphan detection in distributed systems is a well-researched field for which many solutions exist. These solutions exploit well defined parent-child relationships given in distributed systems. But they are not applicable in mobile agent systems, since no similar natural relationship between agents exist. Thus new protocols have to be developed. In this paper one such protocol for controlling mobile mobile agents and for orphan detection is presented. The shadow approach presented in this paper uses the idea of a placeholder (shadow) which is assigned by the agent system to each new agent. This defines an artificial relationship between agents and shadow. The shadow records the location of all dependent agents. Removing the root shadow implies that all dependent agents are declared orphan and are eventually be terminated. We introduce agent proxies that create a path from shadow to every agent. In an extension of the basic protocol we additionally allow the shadow to be mobile.The shadow approach can be used for termination of groups of agents even if the exact location of each single agent is not known.     

Selecting a Cost-Effective Test Case Prioritization Technique

Regression testing is an expensive testing process used to validate modified software and detect whether new faults have been introduced into previously tested code. To reduce the cost of regression testing, software testers may prioritize their test cases so that those which are more important, by some measure, are run earlier in the regression testing process. One goal of prioritization is to increase a test suite's rate of fault detection. Previous empirical studies have shown that several prioritization techniques can significantly improve rate of fault detection, but these studies have also shown that the effectiveness of these techniques varies considerably across various attributes of the program, test suites, and modifications being considered. This variation makes it difficult for a practitioner to choose an appropriate prioritization technique for a given testing scenario. To address this problem, we analyze the fault detection rates that result from applying several different prioritization techniques to several programs and modified versions. The results of our analyses provide insights into which types of prioritization techniques are and are not appropriate under specific testing scenarios, and the conditions under which they are or are not appropriate. Our analysis approach can also be used by other researchers or practitioners to determine the prioritization techniques appropriate to other workloads.     

Directed test suite augmentation: an empirical investigation

Test suite augmentation techniques are used in regression testing to identify code elements in a modified program that are not adequately tested and to generate test cases to cover those elements. A defining feature of test suite augmentation techniques is the potential for reusing existing regression test suites. Our preliminary work suggests that several factors influence the efficiency and effectiveness of augmentation techniques that perform such reuse. These include the order in which target code elements are considered while generating test cases, the manner in which existing regression test cases and newly generated test cases are used, and the algorithm used to generate test cases. In this work, we present the results of two empirical studies examining these factors, considering two test case generation algorithms (concolic and genetic). The results of our studies show that the primary factor affecting augmentation using these approaches is the test case generation algorithm utilized; this affects both cost and effectiveness. The manner in which existing and newly generated test cases are utilized also has a substantial effect on efficiency and in some cases a substantial effect on effectiveness. The order in which target code elements are considered turns out to have relatively few effects when using concolic test case generation but in some cases influences the efficiency of genetic test case generation. The results of our first study, on four relatively small programs using a large number of test suites, are supported by our second study of a much larger program available in multiple versions. Together, the studies reveal a potential opportunity for creating a more cost‐effective hybrid augmentation approach leveraging both concolic and genetic test case generation techniques, while appropriately utilizing our understanding of the factors that affect them. Copyright © 2014 John Wiley & Sons, Ltd.     

Efficient real-time trajectory tracking

Moving objects databases (MOD) manage trajectory information of vehicles, animals, and other mobile objects. A crucial problem is how to efficiently track an object’s trajectory in real-time, in particular if the trajectory data is sensed at the mobile object and thus has to be communicated over a wireless network. We propose a family of tracking protocols that allow trading the communication cost and the amount of trajectory data stored at a MOD off against the spatial accuracy. With each of these protocols, the MOD manages a simplified trajectory that does not deviate by more than a certain accuracy bound from the actual movement. Moreover, the different protocols enable several trade-offs between computational costs, communication cost, and the reduction in the trajectory data: Connection-Preserving Dead Reckoning minimizes the communication cost using dead reckoning, a technique originally designed for tracking an object’s current position. Generic Remote Trajectory Simplification (GRTS) further separates between tracking of the current position and simplification of the past trajectory and can be realized with different line simplification algorithms. For both protocols, we discuss how to bound the space consumption and computing time at the moving object and thereby present an effective compression technique to optimize the reduction performance of real-time line simplification in general. Our evaluations with hundreds of real GPS traces show that a realization of GRTS with a simple simplification heuristic reaches 85–90% of the best possible reduction rate, given by retrospective offline simplification. A realization with the optimal line simplification algorithm by Imai and Iri even reaches more than 97% of the best possible reduction rate.     

On the Use of Mutation Faults in Empirical Assessments of Test Case Prioritization Techniques

Regression testing is an important activity in the software life cycle, but it can also be very expensive. To reduce the cost of regression testing, software testers may prioritize their test cases so that those which are more important, by some measure, are run earlier in the regression testing process. One potential goal of test case prioritization techniques is to increase a test suite's rate of fault detection (how quickly, in a run of its test cases, that test suite can detect faults). Previous work has shown that prioritization can improve a test suite's rate of fault detection, but the assessment of prioritization techniques has been limited primarily to hand-seeded faults, largely due to the belief that such faults are more realistic than automatically generated (mutation) faults. A recent empirical study, however, suggests that mutation faults can be representative of real faults and that the use of hand-seeded faults can be problematic for the validity of empirical results focusing on fault detection. We have therefore designed and performed two controlled experiments assessing the ability of prioritization techniques to improve the rate of fault detection of test case prioritization techniques, measured relative to mutation faults. Our results show that prioritization can be effective relative to the faults considered, and they expose ways in which that effectiveness can vary with characteristics of faults and test suites. More importantly, a comparison of our results with those collected using hand-seeded faults reveals several implications for researchers performing empirical studies of test case prioritization techniques in particular and testing techniques in general     

Prioritizing JUnit Test Cases: An Empirical Assessment and Cost-Benefits Analysis

Test case prioritization provides a way to run test cases with the highest priority earliest. Numerous empirical studies have shown that prioritization can improve a test suite's rate of fault detection, but the extent to which these results generalize is an open question because the studies have all focused on a single procedural language, C, and a few specific types of test suites. In particular, Java and the JUnit testing framework are being used extensively to build software systems in practice, and the effectiveness of prioritization techniques on Java systems tested under JUnit has not been investigated. We have therefore designed and performed a controlled experiment examining whether test case prioritization can be effective on Java programs tested under JUnit, and comparing the results to those achieved in earlier studies. Our analyses show that test case prioritization can significantly improve the rate of fault detection of JUnit test suites, but also reveal differences with respect to previous studies that can be related to the language and testing paradigm. To investigate the practical implications of these results, we present a set of cost-benefits models for test case prioritization, and show how the effectiveness differences observed can result in savings in practice, but vary substantially with the cost factors associated with particular testing processes.     

Testing homogeneous spreadsheet grids with the "what you see iswhat you test" methodology

Although there has been recent research into ways to design environments that enable end users to create their own programs, little attention has been given to helping these end users systematically test their programs. To help address this need in spreadsheet systems (the most widely used type of end-user programming language), we previously introduced a visual approach to systematically testing individual cells in spreadsheet systems. However, the previous approach did not scale well in the presence of largely homogeneous grids, which introduce problems somewhat analogous to the array-testing problems of imperative programs. We present two approaches to spreadsheet testing that explicitly support such grids. We present the algorithms, time complexities, and performance data comparing the two approaches. This is part of our continuing work to bring to end users at least some of the benefits of formalized notions of testing without requiring knowledge of testing beyond a naive level     

Vertical variability of aerosol backscatter from an airborne-focused continuous-wave CO2 lidar at 9.1-microm wavelength

Atmospheric aerosol backscatter measurements taken with a continuous-wave focused Doppler lidar at 9.1-mum wavelength were obtained over western North America and the Pacific Ocean from 13 to 26 September 1995 as part of a NASA airborne mission. Backscatter variability was measured for ~52 flight hours, covering an equivalent horizontal distance of ~30,000 km in the troposphere. Some quasi-vertical backscatter profiles were also obtained during various ascents and descents at altitudes that ranged from ~0.1 to 12 km. Similarities and differences for aerosol loading over land and ocean were observed. A midtropospheric aerosol backscatter background mode near 3 x 10(-11) to 1 x 10(-10) m(-1) sr(-1) was obtained, which is consistent with those of previous airborne and ground-based data sets.