The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Reconstructing architectural components from existing software applications is an important task during the software maintenance cycle because either those elements do not exist or are outdated. Reverse engineering techniques are used to reduce the effort demanded during the reconstruction. Unfortunately, there is no widely accepted technique to retrieve software components from source code. Moreover,...
The emerging new data types bring tremendous challenges to data mining. There is an enormous amount of high-dimensional class-imbalanced data in different fields. In this case, traditional classification methods are not appropriate because they are prone to ensure the accuracy of the majority class. Meanwhile, the curse of dimensionality makes situations more complicated. Finding a complicated classifier...
This paper describes, and illustrates using documented applications, a general framework methodology for wide-area forest and land use mapping and change detection using Synthetic Aperture Radar (SAR) remote sensing. Consideration is given to implementation of the SAR-based methodology using both commercial and free/open-source software. Our experience shows that constructing a complete processing...
System call analysis is a behavioral malware detection technique that is popular due to its promising detection results and ease of implementation. This study describes a system that uses system call analysis to detect malware that evade traditional defenses. The system monitors executing processes to identify compromised hosts in production environments. Experimental results compare the effectiveness...
Software watermarking is a tool used to combat software piracy by embedding identifying information into a program. Most existing proposals for software watermarking have the shortcoming that they heavily rely on the stealth of watermark to prevent adversaries removing marks. Besides, the watermark is separate from the original program and can be destroyed via fairly straightforward semantics-preserving...
Detection of infeasible paths is required in many areas including test coverage analysis, test case generation, security vulnerability analysis, etc. Existing approaches typically use static analysis coupled with symbolic evaluation, heuristics, or path-pattern analysis. This paper is related to these approaches but with a different objective. It is to analyze code of real systems to build patterns...
Understanding the severity of reported bugs is important in both research and practice. In particular, a number of recently proposed mining-based software engineering techniques predict bug severity, bug report quality, and bug-fix time, according to this information. Many bug tracking systems provide a field "severity" offering options such as "severe", "normal", and...
Sketch recognition is one of the integral components used by law enforcement agencies in solving crime. In recent past, software generated composite sketches are being preferred as they are more consistent and faster to construct than hand drawn sketches. Matching these composite sketches to face photographs is a complex task because the composite sketches are drawn based on the witness description...
In the online job recruitment domain, accurate classification of jobs and resumes to occupation categories is important for matching job seekers with relevant jobs. An example of such a job title classification system is an automatic text document classification system that utilizes machine learning. Machine learning-based document classification techniques for images, text and related entities have...
In this study, we developed rehabilitation software for SEMUL (simple exercise machine for upper limbs). SEMUL has eight software routines; however, these routines do not manage to combine quantitative evaluation with user amusement. To solve this problem, we developed training software in the form of coin-collecting software. In addition, we developed the coin-collecting software such that it was...
Software defect prediction is important for improving software quality. Defect predictors allow software test engineers to focus on defective modules. Cross-Project Defect Prediction (CPDP) uses data from other companies to build defect predictors. However, outliers may lower prediction accuracy. In this study, we propose a transfer learning based model called VAB-SVM for CPDP robust in handling outliers...
In the software development, defects affect quality and cost in an adverse way. Therefore, various studies have been proposed defect prediction techniques. Most of current defect prediction approaches use past project data for building prediction models. That is, these approaches are difficult to apply new development projects without past data. In this study, we focus on the cross project prediction...
The popularity of internet along with the huge number of reviews posted daily via social media, blogs and review sites invokes the research challenges on topic or aspect based analysis. In the recent years, it also has become a challenging task to mine opinions with respect to the aspects from the available unstructured and noisy data. In this paper, we present a novel approach to identify the key...
An increasing interest in energy-efficiency combined with the decreasing cost of embedded networked sensors is lowering the cost of outlet-level metering. If these trends continue, new buildings in the near future will be able to install “smart” outlets, which monitor and transmit an outlets power usage in real time, for nearly the same cost as conventional outlets. One problem with the pervasive...
Nowadays, online credit card transactions has become a hot spot for frauds. The amount spent by a person using his credit card can vary and there is never a particular pattern of a person's expenses. Due to this characteristic of credit card use and its fraud, traditional algorithms cannot be implemented for credit card fraud detection. We required some trial and error methods which also gained experience...
Predicting the changes in the next release of software, during the early phases of software development is gaining wide importance. Such a prediction helps in allocating the resources appropriately and thus, reduces costs associated with software maintenance. But predicting the changes using the historical data (data of past releases) of the software is not always possible due to unavailability of...
Machine learning techniques have been earnestly explored by many software engineering researchers. At present state of art, there is no conclusive evidence on the kind of machine learning techniques which are most accurate and efficient for software defect prediction but some recent studies suggest that combining multiple machine learners, that is, ensemble learning, may be a more accurate alternative...
The exploding volume of network traffic and expanding Quality of Service (QoS) requirements from emerging multimedia and interactive applications in the last decade demand improved internet traffic engineering techniques. In particular, traffic classification and packet marking became essential components for end-to-end QoS assurance of different traffic classes. In this paper we present WekaTIE,...
Malicious software and especially botnets are among the most important security threats in the Internet. Thus, the accurate and timely detection of such threats is of great importance. Detecting machines infected with malware by identifying their malicious activities at the network level is an appealing approach, due to the ease of deployment. Nowadays, the most common communication channels used...
This paper proposes a method to optimize the Nonorthogonal Space Distance (NoSD) based on the Particle Swarm Optimization (PSO) algorithm so as to increase estimation accuracy in analogy-based software cost estimation. NoSD is a measure of projects similarity that uses a matrix defined based on mutual information to take both feature redundancies and feature weights into distance computation. We assumes...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.