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Power Analysis (PA) is a powerful method to extract leakage information from theoretically secure cryptographic devices. In general, Differential Power Analysis (DPA) correlates the processed data with power consumption of devices through statistical analysis to reveal systems' secret key. A common approach to counteract DPA is a low-entropy lightweight masking strategy. This masking scheme, known...
Knowing faulty modules prior to testing makes testing more effective and helps to obtain reliable software. Here, we develop a framework for automatic extraction of human understandable fuzzy rules for software fault detection/classification. This is an integrated framework to simultaneously identify useful determinants (attributes) of faults and fuzzy rules using those attributes. At the beginning...
Developing software applications that are free of vulnerabilities is a necessity, especially if these applications are intended to operate over the World Wide Web. As the development of software applications is evolving in a quick manner the need to develop tools that can automatically detect vulnerabilities in a software has emerged. The main challenge in these tools is providing a high accuracy...
Aphasia is a common adult language disorder acquired after a stroke, head injury, tumor, etc. Accurate diagnosis influences the prognosis of any speech and language disorder including aphasia. Therefore, in this paper we have proposed a semi-automated Aphasia diagnosis and classification framework employing feature extraction and pattern matching techniques of the digital signal processing (DSP)....
The Corona discharge represents one of the main concerns of the century in the field of electricity and powerline design, as it is both harmful for the environment as well as very costly to cover for the voltage losses on the transport. In this paper, we propose the design for a measurement and analysis platform for this phenomenon that can estimate the Corona discharge losses based on a video stream...
In this work, we introduce a Deep Neural Network model for automated software categorization. The model is ableto form high-level concepts from low-level code tokens andto distinguish important features such as API calls and identifiersin order to support software categorization. Our empirical evaluationshows that DNN outperformed other machine learning approacheswith 15.9–36.4% higher accuracy in...
In crowdsourced testing, it is beneficial to automatically classify the test reports that actually reveal a fault – a true fault, from the large number of test reports submitted by crowd workers. Most of the existing approaches toward this task simply leverage historical data to train a machine learning classifier and classify the new incoming reports. However, our observation on real industrial data...
The detection of similar code can support many software engineering tasks such as program understanding and API replacement. Many excellent approaches have been proposed to detect programs having similar syntactic features. However, some programs dynamically or statistically close to each other, which we call kindred programs, may be ignored. We believe the detection of kindred programs can enhance...
System availability is one of the major requirements expected from systems in the trading domain. In order to prevent system outages that can deteriorate system availability, anomaly detection must be able to assess the status of the system and detect anomalies that can lead to failures on a real-time basis. This paper presents a framework for anomaly detection for complex trading systems based on...
Feature-oriented programming allows developers to physically separate and reuse features via composition. This promises several benefits compared to other reuse approaches, for instance, easier traceability and maintenance. However, due to their simplicity cloning and annotation-based product lines are established in practice. We aim to reduce risks and costs of migrating towards composition, lowering...
Feature-oriented software development (FOSD) has recently emerged as a promising approach for developing a collection of similar software products from a shared set of software assets. A well-recognized issue in FOSD is the analysis of feature interactions: cases where the integration of multiple features would alter the behavior of one or several of them. Existing approaches to detecting feature...
Version information plays an important role in spreadsheet understanding, maintaining and quality improving. However, end users rarely use version control tools to document spreadsheets' version information. Thus, the spreadsheets' version information is missing, and different versions of a spreadsheet coexist as individual and similar spreadsheets. Existing approaches try to recover spreadsheet version...
Software developer turnover has become a big challenge for information technology (IT) companies. The departure of key software developers might cause big loss to an IT company since they also depart with important business knowledge and critical technical skills. Understanding developer turnover is very important for IT companies to retain talented developers and reduce the loss due to developers'...
This paper reports a large-scale study that aims to understand how mobile application (app) vulnerabilities are associated with software libraries. We analyze both free and paid apps. Studying paid apps was quite meaningful because it helped us understand how differences in app development/maintenance affect the vulnerabilities associated with libraries. We analyzed 30k free and paid apps collected...
Using Clustering algorithm to improve the effectiveness of test case prioritization has been well recognized by many researchers. Software fault prediction has been one of the active parts of software engineering, but to date, there are few test cases prioritization technique using fault prediction. We conjecture that if the code has a fault-proneness, the test cases covering the code will findfault...
Adopting Software Product Line (SPL) engineering principles demands a high up-front investment. Bottom-Up Technologies for Reuse (BUT4Reuse) is a generic and extensible tool aimed to leverage existing similar software products in order to help in extractive SPL adoption. The envisioned users are 1) SPL adopters and 2) Integrators of techniques and algorithms to provide automation in SPL adoption activities...
Continuous Delivery (CD) enables mobile developers to release small, high quality chunks of working software in a rapid manner. However, faster delivery and a higher software quality do neither guarantee user satisfaction nor positive business outcomes. Previous work demonstrates that app reviews may contain crucial information that can guide developer's software maintenance efforts to obtain higher...
Automatic building of software projects providesa desirable foundation to support a large variety of softwareengineering research tasks based on open software repositories. In this paper, we propose the first technique to automaticallyextract software build commands from software readme files andWiki pages, and combine the extracted commands for softwarebuilding. Specifically, we leverage the Named...
Using Clustering algorithm to improve the effectiveness of test case prioritization has been well recognized by many researchers. Software fault prediction has been one of the active parts of software engineering, but to date, there are few test cases prioritization technique using fault prediction. We conjecture that if the code has a fault-proneness, the test cases covering the code will find fault...
Over the course of time an organization working with geospatial data accumulates tons of data both in the form of vector and raster formats. This data is a result of coordinated processes within the organization and external sources such as other collaborative organizations, projects and agencies, crowd sourcing efforts, etc. The massive amount of data accumulated as a result and the recent developments...
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