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Software development process encompasses multiple types of and differentiated versions of artefacts during the corresponding lifecycle. These artefacts are vulnerable to artefact drift or erosion when the product being developed gets changed. As a result different artefacts are subject to differential rates of updates compared to each other. Managing the software artefacts is one of the major problems...
How to accurately estimate facial age is a difficult problem due to insufficiency of training data. In this paper, an effective approach is proposed to estimate facial age by means of extreme learning machine (ELM). In the proposed method, a set of features is randomly selected from the original features to consist of a feature subspace. Given an initial weight matrix, the training samples within...
The number of devices that are being connected by the Internet is growing rapidly and hence, safeguarding private information by incorporating hardware and software security measures has become crucial. Physically unclonable functions (PUFs) have been proposed to enable lightweight hardware security which uses the inherent manufacturing variations as a way to generate unique signatures. However, given...
Current automatic program repair techniques often produce overfitting patches. Such a patch passes the test suite but does not actually repair the bug. In this paper, we propose two techniques to address the patch overfitting problem. First, we propose an automatic repair technique that performs syntactic code search to leverage bug-related code from a code database to produce patches that are likely...
Handwritten text in any language is believed to convey a great deal of information about writers' personality and identity. Handwritten documents are frequently used as evidences in forensic tasks. Handwriting skills is learnt and developed from the early schooling stages. Research interest in behavioral biometrics was the main driving force behind the growth in research into Writer Identification...
This paper aims to experimental evaluation of different methodologies to recognize human face based on different facial expression. The face and facial images were captured locally, as the experiment is aimed to be done in India domain. The features were extracted based on two techniques, viz, Discrete Wavelet Transform (DWT) and Local Binary Pattern (LBP). The range of extracted feature is 150,300,600,1200...
Vulnerabilities in web applications are due to various factors. Failure to properly validated user input is one of the factors that led to run unauthorized code in these programs. Sqli and Xss are two common vulnerabilities in web applications, That is due to lack of proper input validation. Therefore, in this paper we study how to protect organizational websites of north khorasan in iran against...
Face recognition methods are evaluated against face image databases. Recent face image databases provide an evaluation protocol for an impartial comparison and assessment of where a facial recognition algorithm stands compared to other methods. Unfortunately, many authors test their facial recognition methods using either restricted face databases, random subsets from public databases, or do not follow...
The trend for about twenty years, the research regarding the number of states in Hidden Markov Model (HMM) was mainly aimed at increasing it in order to ensure the robustness of the face recognition system. In this paper, a novel face recognition method is presented based on one state of discrete HMM, where it seemed impossible in the past. Contrary to other approaches that use the three parameters...
The performance of speech emotion classifiers greatly degrade when the training conditions do not match the testing conditions. This problem is observed in cross-corpora evaluations, even when the corpora are similar. The lack of generalization is particularly problematic when the emotion classifiers are used in real applications. This study addresses this problem by combining active learning (AL)...
When emotion recognition systems are used in new domains, the classification performance usually drops due to mismatches between training and testing conditions. Annotations of new data in the new domain is expensive and time demanding. Therefore, it is important to design strategies that efficiently use limited amount of new data to improve the robustness of the classification system. The use of...
Automated white-box testing is a major issue in software engineering. In previous work, we introduced LTest, a generic and integrated toolkit for automated white-box testing of C programs. LTest supports a broad class of coverage criteria in a unified way (through the label specification mechanism) and covers most major parts of the testing process – including coverage measurement, test generation...
Finding an effective way to represent human actions is yet an open problem because it usually requires taking evidences extracted from various temporal resolutions into account. A conventional way of representing an action employs temporally ordered fine-grained movements, e.g., key poses or subtle motions. Many existing approaches model actions by directly learning the transitional relationships...
We propose a Low-Dimensional Deep Feature based Face Alignment (LDFFA) method to address the problem of face alignment “in-the-wild”. Recently, Deep Bottleneck Features (DBF) has been proposed as an effective channel to represent input with compact, low-dimensional descriptors. The locations of fiducial landmarks of human faces could be effectively represented using low dimensional features due to...
We propose an image aesthetic quality assessment algorithm, which considers personal taste in addition to generally perceived preference. This problem is formulated by a combination of two different learning frameworks based on support vector machines—Support Vector Regression (SVR) and Ranking SVM (R-SVM), where SVR learns a general model based on public datasets and R-SVM adjusts the model to accommodate...
Search-based test generation, if effective at fault detection, can lower the cost of testing. Such techniques rely on fitness functions to guide the search. Ultimately, such functions represent test goals that approximate — but do not ensure — fault detection. The need to rely on approximations leads to two questions — can fitness functions produce effective tests and, if so, which should be used...
In most cases, web applications communicate with web services (SOAP and RESTful). The former act as a front-end to the latter, which contain the business logic. A hacker might not have direct access to those web services (e.g., they are not on public networks), but can still provide malicious inputs to the web application, thus potentially compromising related services. Typical examples are XML injection...
Continuous security certification of software-as-a-service (SaaS) aims at continuously, i.e. repeatedly and automatically validating whether a SaaS application adheres to a set of security requirements. Since SaaS applications make heavy use of web application technologies, checking security requirements with the help of web application testing techniques seems evident. However, these techniques mainly...
Mobile app testing and evaluation requires exposing the app to a wide array of real world context conditions viz. location, sensor values, network conditions etc. Such comprehensive context conditions are difficult to create in a development environment on a real device, therefore, simulating them in a mobile emulator is a promising alternative. We present ContextMonkey, a framework for context generation...
Empirical studies have shown that most software interaction faults involve one or two variables interacting, with progressively fewer triggered by three to six variables interacting. This paper introduces a model for the origin of this distribution. We start with two empirically reasonable assumptions regarding the distribution of branch conditions in code and the proportion of t-way combinations...
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