There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

We consider routing security in wireless sensor networks. Many sensor network routing protocols have been proposed, but none of them have been designed with security as a goal. We propose security goals for routing in sensor networks, show how attacks against ad-hoc and peer-to-peer networks can be adapted into powerful attacks against sensor networks, introduce two classes of novel attacks against sensor networks sinkholes and HELLO floods, and analyze the security of all the major sensor network routing protocols. We describe crippling attacks against all of them and suggest countermeasures and design considerations. This is the first such analysis of secure routing in sensor networks.

/pdf/secure-routing-in-wireless-sensor-networks-attacks-and-4630unozk9.pdf

Secure routing in wireless sensor networks: attacks and countermeasures

Previously proposed sensor network data dissemination schemes require periodic low-rate flooding of data in order to allow recovery from failure. We consider constructing two kinds of multipaths to enable energy efficient recovery from failure of the shortest path between source and sink. Disjoint multipath has been studied in the literature. We propose a novel braided multipath scheme, which results in several partially disjoint multipath schemes. We find that braided multipaths are a viable alternative for energy-efficient recovery from isolated and patterned failures.

Highly-resilient, energy-efficient multipath routing in wireless sensor networks

Extensively class tested, this text takes an innovative approach to explaining the process of software testing: it defines testing as the process of applying a few well-defined, general-purpose test criteria to a structure or model of the software. The structure of the text directly reflects the pedagogical approach and incorporates the latest innovations in testing, including techniques to test modern types of software such as OO, web applications, and embedded software.

Introduction to Software Testing: List of Figures

Background: The accurate prediction of where faults are likely to occur in code can help direct test effort, reduce costs, and improve the quality of software. Objective: We investigate how the context of models, the independent variables used, and the modeling techniques applied influence the performance of fault prediction models. Method: We used a systematic literature review to identify 208 fault prediction studies published from January 2000 to December 2010. We synthesize the quantitative and qualitative results of 36 studies which report sufficient contextual and methodological information according to the criteria we develop and apply. Results: The models that perform well tend to be based on simple modeling techniques such as Naive Bayes or Logistic Regression. Combinations of independent variables have been used by models that perform well. Feature selection has been applied to these combinations when models are performing particularly well. Conclusion: The methodology used to build models seems to be influential to predictive performance. Although there are a set of fault prediction studies in which confidence is possible, more studies are needed that use a reliable methodology and which report their context, methodology, and performance comprehensively.

/pdf/a-systematic-literature-review-on-fault-prediction-50xbihfieh.pdf

A Systematic Literature Review on Fault Prediction Performance in Software Engineering

Combinatorial testing is a specification-based testing criterion, which requires that for each t-way combination of input parameters of a system, every combination of valid values of these t parameters be covered by at least one test case. This approach is motivated by the observation that in many applications a significant number of faults are caused by interactions of a smaller number of parameters. In this paper, we propose new test generation algorithms for combinatorial testing based on two artificial life techniques: a genetic algorithm (GA) and an ant colony algorithm (ACA). The usefulness of these algorithms is demonstrated through experiments. In the case t = 3 in particular, our algorithms exhibited impressive results

Using artificial life techniques to generate test cases for combinatorial testing

In a previous paper, Kuhn [1999] showed that faults in Boolean specifications constitute a hierarchy with respect to detectability, and drew the conclusion that missing condition faults should be hypothesized to generate tests. However this conclusion was premature, since the relationships between missing condition faults and faults in other classes have not been sufficiently analyzed. In this note, we investigate such relationships, aiming to complement the work of Kuhn. As a result, we obtain an extended hierarchy of fault classes and reach a different conclusion.

On fault classes and error detection capability of specification-based testing

There have been many bug prediction models built with historical metrics, which are mined from version histories of software modules. Many studies have reported the effectiveness of these historical metrics. For prediction levels, most studies have targeted package and file levels. Prediction on a fine-grained level, which represents the method level, is required because there may be interesting results compared to coarse-grained (package and file levels) prediction. These results include good performance when considering quality assurance efforts, and new findings about the correlations between bugs and histories. However, fine-grained prediction has been a challenge because obtaining method histories from existing version control systems is a difficult problem. To tackle this problem, we have developed a fine-grained version control system for Java, Historage. With this system, we target Java software and conduct fine-grained prediction with well-known historical metrics. The results indicate that fine-grained (method-level) prediction outperforms coarse-grained (package and file levels) prediction when taking the efforts necessary to find bugs into account. Using a correlation analysis, we show that past bug information does not contribute to method-level bug prediction.

/pdf/bug-prediction-based-on-fine-grained-module-histories-m63izw7oxo.pdf

Bug prediction based on fine-grained module histories

In this paper, we present a routing protocol for finding two node-disjoint paths between each pair of nodes in a computer network. In the proposed protocol, each node in the network has the same procedure, which is driven by local information with respect to the network topology such as an adjacent node on a spanning tree in the network. Thus, the execution of the protocol can continue after changes of the network topology and load. The concept of spanning tree-based kernel construction is introduced to synchronize procedures under the distributed control of the protocol. The routing scheme based on the protocol possesses the enhanced capabilities of alternate routes and load splitting, which cope with failures and load variations in the network. Furthermore, even if topology changes occur which damage the obtained disjoint paths, the paths themselves can be updated efficiently.

Tohru Kikuno

Papers

Using artificial life techniques to generate test cases for combinatorial testing

On fault classes and error detection capability of specification-based testing

Bug prediction based on fine-grained module histories

A routing protocol for finding two node-disjoint paths in computer networks

Genetics-based multiprocessor scheduling using task duplication