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.
Recent developments in geotechnologies provide resources to propose innovative strategies for urban and environmental management, including remote sensing data and computational resources for processing them. With the main objective of identifying urban areas of illegal occupation, this work uses WorldView-2-sensor images and the InterIMAGE, an image interpretation software, based on knowledge, under...
Although object-based image analysis (OBIA) has been used for detailed classification of urban areas, its attribute selection and knowledge discovery have been time consuming and subjective to analysts' performance. In this study, Data Mining was performed using C4.5 algorithm to select the appropriate attributes for object-based classification. This algorithm provides a decision tree output to represent...
With the impact of climate change in India, majority of the agricultural crops are being badly affected interms of their performance over a period of last two decades. Predicting the crop yield well ahead of its harvest would help the policy makers and farmers for taking appropriate measures for marketing and storage. Such predictions will also help the associated industries for planning the logistics...
Defects in every software must be handled properly, and the number of defects directly reflects the quality of a software. In recent years, researchers have applied data mining and machine learning methods to predicting software defects. However, in their studies, the method in which the machine learning models are directly adopted may not be precise enough. Optimizing the machine learning models...
Bug fixing accounts for a large amount of the software maintenance resources. Generally, bugs are reported, fixed, verified and closed. However, in some cases bugs have to be re-opened. Re-opened bugs increase maintenance costs, degrade the overall user-perceived quality of the software and lead to unnecessary rework by busy practitioners. In this paper, we study and predict re-opened bugs through...
In this article we present an application of Artificial Intelligence for estimation of software projects. The research presented herein was based on several methods of classification and metaclassification. Due to increasing significance of Open Source, we have selected projects being hosted on the leading platform for Open Source projects — Sourceforge.net. In the first part of article, we describe...
In this paper, we explore the viability of mining the basic data provided in bug repositories to predict bug lifetimes. We follow the method of Lucas D. Panjer as described in his paper, Predicting Eclipse Bug Lifetimes. However, in place of Eclipse data, the FreeBSD bug repository is used. We compare the predictive accuracy of five different classification algorithms applied to the two data sets...
Bug assignment is an important step in bug life-cycle management. In large projects, this task would consume a substantial amount of human effort. To compare with the previous studies on automatic bug assignment in FOSS (free/open source software) projects, we conduct a case study on a proprietary software project in China. Our study consists of two experiments of automatic bug assignment, using Chinese...
Essence of software testing is to choose a representative value (known as test case) from the input to perform the programs under test. The actual results of the programs will be checked to verify the consistency with the expected ones. If the results are different, it should take some correction and adjustment correspondingly. The existing method for test suite generation is mainly based on the test...
Signature-based anti-viruses are very accurate, but are limited in detecting new malicious code. Dozens of new malicious codes are created every day, and the rate is expected to increase in coming years. To extend the generalization to detect unknown malicious code, heuristic methods are used; however, these are not successful enough. Recently, classification algorithms were used successfully for...
Selecting suitable features is very crucial for achieving successful classification of land cover types. This paper presents a comparative study of three typical feature selection methods for the task of regional land cover classification using MODIS data. Comparison results have shown that Branch and Bound is the best for land cover classification with MODIS data, while ReliefF and mRMR achieve nearly...
In this paper we present a comparative analysis of the predictive power of two different sets of metrics for defect prediction. We choose one set of product related and one set of process related software metrics and use them for classifying Java files of the Eclipse project as defective respective defect-free. Classification models are built using three common machine learners: logistic regression,...
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.