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Quantitative description and complexity understanding of software architecture are difficult questions of software development. Taking The complexity evolution of VTK software version as an example, this paper proposes a model for predicting the complexity of software evolution based on logistic equation and quantitative validation of Lehman's law. Its basic idea is that the software architecture...
Predictive models for software projects' characteristics have been traditionally based on project-level metrics, employing only little developer-level information, or none at all. In this work we suggest novel metrics that capture temporal and semantic developer-level information collected on a per developer basis. To address the scalability challenges involved in computing these metrics for each...
Understanding critical aspects of software fault-proneness prediction contributes significantly to building effective fault-proneness prediction models. This paper conducts an investigation of essential topics in this area, including techniques for evaluating the effectiveness of fault-proneness prediction models, issues of concerns when building the prediction models, as well as findings shared by...
In this paper, we report an evaluation study of predictive models of programmer navigation. In particular, we compared two operationalizations of navigation from the literature (click-based versus view-based) to see which more accurately records a developer's navigation behaviors. Moreover, we also compared the predictive accuracy of seven models of programmer navigation from the literature, including...
Network defenders are locked in a constant race with attackers as they try to defend their networks. The defenders suffer from a huge disadvantage: they lack knowledge of the existence of zero-day vulnerabilities that have not been yet been discovered or publically disclosed, but that are still weakening the security of their networks. It would be a huge advantage to these defenders if they had some...
Software maintenance phase of Software Development Lifecycle (SDLC) is the most expensive and complex phase that requires nearly 60–70% of the total project cost. Due to this, many software fails to get repair within real time constraint. Ascribe to technology advancements and changing requirements, software must be well developed and maintained to get adapted. Hence, it is necessary to predict software...
Software development is an essential field today. The advancement in software systems leads to risk of them being exposed to defects. It is important to predict the defects well in advance in order to help the researchers and developers to build cost effective and reliable software. Defect prediction models extract information about the software from its past releases and predict the occurrence of...
Software defect prediction (SDP) is a most dynamic research area in software engineering. SDP is a process used to predict the deformities in the software. To identifying the defects before the arrival of item or aimed the software improvement, to make software dependable, defect prediction model is utilized. It is always desirable to predict the defects at early stages of life cycle. Hence to predict...
Management of natural and industrial hazards is performed through cooperation of a multitude of actors, sometimes from different institutions sharing common objectives, which belong to virtual organizations responsible of monitoring risks and responding to emergency situations. The information systems dedicated to this domain are multidisciplinary, highly distributed, and characterized by the co-existence...
As machine learning (ML) becomes increasingly popular, developers without deep experience in ML — who we will refer to as ML practitioners — are facing the need to diagnose problems with ML models. Yet successful diagnosis requires high-level expertise that practitioners lack. As in many complex data-oriented domains, visualization could help. This two-phase study explored the design of visualizations...
Software metrics are very helpful in measuring the different aspects of software like cohesion, coupling, polymorphism, inheritance etc. The objective of measuring software metrics are quality assurance, defect prediction, maintainability prediction, cost estimation, debugging, etc. Many authors proposed the use of static metrics for the software maintainability prediction (SMP) and were successful,...
Data-Driven Software Reliability Modeling (DDSRM) is an approach in software reliability prediction problem which only relies on software failure data. There are two kinds of model architecture in this modeling, which are Single-Input Single-Output (SISO) and Multiple-Delayed-Input Single-Output (MDISO). In MDISO architecture, the prediction process involves having multiple inputs from the failure...
Corrosion and scaling is a frequent phenomenon in the operation of industrial circulating cooling water system, they have great influence on pipeline equipment, which will cause serious economic losses and waste of water resources, so the treatment of corrosion and scaling of industrial circulating cooling water is particularly important. In this paper, the relevant water quality and process data...
The KEEL software provides several methods to mine fuzzy association rules, however, few modules are available to study them. In this paper we introduce four new KEEL modules to analyze and export fuzzy association rules. Firstly, we present a module to calculate various interest measures for existing sets of fuzzy association rules in order to analyze rules on the basis of their potential interest...
Environmentally friendly and comfortable buildings are a much sought after goal in today's architectural practice. In order to improve energy consumption of buildings without sacrificing indoor comfort, careful consideration of design decisions is needed. Simulation tools provide a solution to one aspect arising from this need, namely the requirement for accurate quantitative results. On the other...
Economic transmission planning heavily relies on the accuracy of the quantitative analysis using market simulation tool, and it therefore requires benchmarking the simulation tool and model against historical actuals. Facing the technical challenges of such analyses, there is a lack of systematic approach and standard in doing such analyses in the industry. In that regard, this paper presents a thorough...
Software fault prediction (SFP) is useful for helping the software engineer to locate potential faulty modules in software testing more easily, so that it can save a lot of time and budgets to improve the software quality. In this paper, aiming at solving the problem that the faulty samples are too rare to train a classifier, an one-class SFP model is proposed by using only non-faulty samples based...
Application of neural networks for direct prediction of lateral-directional force and moments coefficients from the measured flight data of the research aircraft is proposed in this paper. Proposed model of neural networks appears to be a suitable practical approach to develop relationship between flight variables. This relationship eliminates the need of aerodynamic model as well as thrust model...
In this work we present an operative implementation of three numerical weather prediction models with the goal of being used in early warning systems for environmental emergencies. Models are executed in different temporal ranges (from days to months) in which emergencies, such as ground frost, floods, fires, droughts and epidemics, are developed. Products generated are thought and adapted to be used...
We have obtained a new molecular descriptor, called BETSIM, containing and implying the molecular path code. BETSIM it was involved in obtaining a model with high power of prediction of boiling point of 27 cycloalkanes.
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