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A quality model for assessing the changeability level of java code is important for software development. It permits developer to know which classes to be improved for having a better software maintainability. Moreover, a good quality model must be created based on a set of well-selected attributes and metrics. Currently, no research work proposes a changeability assessment model that takes into consideration...
Software changes are inevitable during maintenance, Object-oriented software (OOS) in particular. For change not to be performed in the “dark”, software change impact analysis (SCIA) is used. However, due to the exponential growth in the size and complexity of OOS, classes are not without faults and the existing SCIA techniques only predict change impact set. This means that a change implemented on...
Network function virtualization (NFV) raises new possibilities for embedding data plane processing functions, e.g., firewalls, NAT, packet forwarding, etc., on commodity hardware. However, the advantages of flexibility, scalability and low cost of commodity hardware come at a price, such as resource over-provisioning, because the performance of softwarized network functions on shared resources is...
The software reliability represents one of the most crucial aspects of functional safety. Software is used in almost any electronic systems. When a safety-critical system is considered, it has to be ensured that the software is able to fulfil the minimum safety requirements. If this is not the case, the software will have to be improved until the minimum requirements are fulfilled. Reliability growth...
Software reliability is deliberated as a measurable metric, which is the probability of any software operation to be free of failure for a stated course of time in a given environment. Many Software Reliability Growth Models have been developed over the years that can calculate and anticipate the software product reliability. This paper gives an analysis of various Soft Computing Techniques and considers...
Software Analytics is gaining momentum as aresult of involved empirical research in enhancing quality andproductivity of software engineering activities. There have beenrigorous research efforts in the areas of bug prediction and testingeffort prediction by making use of historical data. The problemof predicting bug fix times is an interesting problem with lotsof advantages to industry but there have...
It is common knowledge in the IT service domain that changes to the system configuration are responsible for a major portion of incidents that result in client outages. However, it is typically very difficult to establish a relationship between changes and incidents as proper documentation takes lower priority at change creation time, as well as during incident management, in order to deal with the...
This work presents a data-intensive solution topredict heating and hot water consumption. The ability topredict locally those flexible sources considering meteorologicaluncertainty can play a key role in the management of microgrid. A microgrid is a building block of future smart grid, it canbe defined as a network of low voltage power generating units, storage devices and loads. The main novelties...
In recent years, data mining algorithm have been successfully applied in software defects and metrics prediction throughout the software development life cycle (SDLC). Features dependencies and class imbalance are the two main issues in the traditional Bayesian models for defect prediction. Traditional supervised models build high prediction rate with limited single product defect and metric data...
Software is an entity that keeps on progressing and endures continuous changes, in order to boost its functionality and maintain its effectiveness. During the development of software, even with advanced planning, well documentation and proper process control, are problems that are countered. These defects influence the quality of software in one way or the other which may result into failure. Therefore,...
Software effort estimation consists of those procedures and activities which help to predict most accurate development effort as well as cost of a software product. After analyzing various proposed concept and theories regarding this we tried to give a new concept which works over partition of a data set. The partition procedure depends over the correlation of input features as well as output features...
Prediction of faults in a proposed software is helpful in deciding the amount of effort to be given for software development. We observed that, a good number of authors hypothesized that the performance of fault prediction model depends on the source code metrics which are used as input of the model. Feature selection technique is a process of selecting suitable set of source code metrics which may...
Fast and accurate performance and power prediction is a key challenge in co-development of hardware and software. Traditional analytical or simulation-based approaches are often too inaccurate or slow. In this work, we propose LACross, a novel learning-based, analytical cross-platform prediction framework that provides fast and accurate estimation of time-varying software performance and power consumption...
For a successful software project, accurate prediction of its overall effort and cost estimation is a very much essential task. Software projects have evolved through a number of development models over the last few decades. Hence, to cover an accurate measurement of the effort and cost for different software projects based on different development models having new and innovative phases of software...
Software must be well developed and maintainable to adapt to the constantly changing requirement of the competitive world. In this article, we distinct different software maintainability prediction models and techniques which can help us to predict the maintainability of software, and can lead us to minimum the effort required to fix the faults in the software and the software will be more maintainable...
The ability to predict which modules are fault-prone can assist in directing quality enhancement efforts to modules at risk. This is especially critical for high-assurance systems where software failures may have severe consequences. While the field of defect rediction based on software metrics is mature, no study has addressed the use of metrics for predicting faults related to exception handling...
As the need of software has been increasing, the danger of malicious attacks against software has been worse. In order to fortify software systems against adversaries, researchers have devoted significant efforts on mitigating software vulnerabilities. To eliminate security vulnerabilities from software with lower inspection effort, vulnerability prediction approaches have been emerged. By allocating...
In this paper, with the help of the method known as predictive profiling, a fuzzy inference based software application is developed that inputs a person's behavior and outputs the degree of suspiciousness. The novelty of this paper is the design and implementation of a fuzzy inference system, equipped with a graphical user interface, to help airport officials in identifying potential troublemakers,...
A software defect prediction model is used to help identifying the defects of software module. Software attributes play an important role to build the model. The performance and effectiveness of a software defection model depends on the characteristics of various software attributes which can be used to predict whether a software module is defected or non-defected. Based on software, one or more software...
To reveal the information hiding in the scholarly big data, relationship analysis among academic entities has been studied from different perspectives in recent years. In this paper, we focus on the problem of collaboration relationship prediction between authors in heterogeneous information networks, and a new method called MACP, i.e., Meta path and author Attribute based Collaboration Prediction...
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