Hierarchy-Debug: a scalable statistical technique for fault localization

Considering the fact that faults may be revealed as undesired mutual effect of program predicates on each other, a new approach for localizing latent bugs, namely Hierarchy-Debug, is presented in this paper. To analyze the vertical effect of predicates on each other and on program termination status, the predicates are fitted into a logistic lasso model. To support scalability, a hierarchical clustering algorithm is applied to cluster the predicates according to their presence in different executions. Considering each cluster as a pseudo-predicate, a distinct lasso model is built for intermediate levels of the hierarchy. Then, we apply a majority voting technique to score the predicates according to their lasso coefficients at different levels of the hierarchy. The predicates with relatively higher scores are ranked as fault relevant predicates. To provide the context of failure, faulty sub-paths are identified as sequences of fault relevant predicates. The grouping effect of Hierarchy-Debug helps programmers to detect multiple bugs. Four case studies have been designed to evaluate the proposed approach on three well-known test suites, Space, Siemens, and Bash. The evaluations show that Hierarchy-Debug produces more precise results compared with prior fault localization techniques on the subject programs.     

Privacy-preserving biometric verification with outsourced correlation filter computation

Multimedia Tools and Applications - In traditional biometric verification systems, personal computer stores biometric database and performs verification process. Because of limited storage,...     

Color object segmentation and tracking using flexible statistical model and level-set

Multimedia Tools and Applications - This study presents an unsupervised novel algorithm for color image segmentation, object detection and tracking based on unsupervised learning step followed with...     

Iris-based human identity recognition with machine learning methods and discrete fast Fourier transform

Innovations in Systems and Software Engineering - One of the most important modules of computer systems is the one that is responsible for user safety. It was proven that simple passwords and...     

The isoxazolidines: the effects of steric factor and hydrophobic chain length on the corrosion inhibition of mild steel in acidic medium

Several new isoxazolidines having varying degree of steric environment and hydrophobic chain length, prepared efficiently using single-step nitrone cycloaddition reactions, are tested for corrosion inhibition of mild steel in 1 M and 5 M HCl at 50-70 °C range by gravimetric and electrochemical methods. All compounds have shown very good corrosion inhibition efficiency (IE%) in acidic solution. Steric crowding around the nitrogen centres and hydrophobic chain lengths as well as increase in temperature (in the presence of the inhibitor in the higher concentration range 100-400 ppm) are found to increase the inhibition efficiency of the isoxazolidines. Thermodynamic parameters (ΔG°_ads, ΔH°_ads, ΔS°_ads) for the adsorption process and kinetic parameters for the metal dissolution (or hydrogen evolution) reaction in the presence of one of the isoxazolidines were determined. Experimental results agree with the Temkin adsorption isotherm. The inhibition of corrosion in 1 M HCl, influenced by both physi- and chemi-sorption, was found to be under mixed control, but predominantly under cathodic control.     

Swarm Intelligent Compressive Routing in Wireless Sensor Networks

This article proposes a novel algorithm to improve the lifetime of a wireless sensor network. This algorithm employs swarm intelligence algorithms in conjunction with compressive sensing theory to build up the routing trees and to decrease the communication rate. The main contribution of this article is to extend swarm intelligence algorithms to build a routing tree in such a way that it can be utilized to maximize efficiency, thereby rectifying the delay problem of compressive sensing theory and improving the network lifetime. In addition, our approach offers accurate data recovery from small amounts of compressed data. Simulation results show that our approach can effectively extend the network lifetime of a large‐scale wireless sensor network.     

A Model for Incident Tickets Correlation in Network Management

In Information Technology Service Management (ITSM), network management teams typically use an Incident Ticket System (ITS) as a tool to track, troubleshoot, and coordinate the resolution of network incidents that occur during the daily operation of the network. A well organized ITS may positively impact on the efficiency of the incident management process. Nevertheless, in many cases the handling of tickets by the management team is not completely systematic and may be incoherent and inefficient. This way, irrelevant or redundant tickets for the same incident may be issued, thus creating a redundancy in the system that leads to inefficiencies. In this paper, we suggest a model aimed to correlate redundant tickets in order to reduce the information to a single ticket per incident. We validate the proposed correlation model by evaluating it with two datasets taken from a real ticketing system of a telecommunications network company. Using this model as a basis, we also develop and evaluate a methodology that assesses the efficiency of the management team during the process of tickets creation and management. Based on it, we also get some insights on the performance of the different management groups involved in the ticket creation process. These analyses can be leveraged for improving both the management groups functioning and the policies for the tickets’ creation.     

Stability Margin Determination of Linear Discrete‐Time Systems Described By Fuzzy Convex Sets Uncertainty

This paper proposes a new method for determining the stability margin of uncertain linear discrete‐time systems with uncertainty described by fuzzy convex sets. Nonsymmetrical triangular membership functions describing the uncertainty of characteristic polynomial coefficients are considered. This method is based on transformation of the uncertain discrete systems to the continuous time area and generalization of Kharitonov theorem for determining the uncommon minimum confidence level that guarantees stability of the system.