Browsing by Author "Lal, Manohar"

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    Defect Prediction Framework Using Neural Networks for Software Enhancement Projects
    (SCIENCEDOMAIN international Ltd.) Vashisht, Vipul; Lal, Manohar; G.S, Sureshchandar
    So far, various approaches have been proposed for effective and accurate prediction of software defects, yet most of these approaches have limited adoption in practice. The objective of this paper is to provide a framework which is expected to be more user-friendly, effective and acceptable for predicting the defects in multiple phases across software enhancement projects. This communication describes a process of applying computational intelligence technologies, in particular neural networks in formulating defect prediction models early in the software development life cycle. A series of empirical experiments are carried out based on input and output measures extracted from 50 'real world' project subsystems. In order to increase the adoption and make the prediction framework easily accessible to project managers, a graphical user interface (GUI) based tool has been designed and implemented that allows input data to be fed easily. The proposed framework uses historical data for training model and as a result provides a defect range (minimum, maximum) based output instead of a definite defect count based output. This is done in view of the fact that exact-count prediction has less probability of being correct as compared to range based predictions. The defect predictions can be used for taking informed decisions including prioritizing software testing efforts, planning additional round of code reviews, allocating human and computerresources, planning for risk mitigation strategy and other corrective actions. The claim of effectiveness of proposed framework is established through results of a comparative study, involving the proposed framework and some well-known models for software defect prediction.
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    Descriptive Analysis of Enrollment Data and Adaptive Educational Hypermedia.
    (BIJIT - BVICAM’s International Journal of Information Technology Bharati Vidyapeeth’s Institute of Computer Applications and Management) Chopra, Nidhi; Lal, Manohar
    As the world around is going through a technological revolution with the dawn of digital age, educationists are in some ways compelled to rethink the existing education system and its components. With the tools and the techniques available, nowadays it's imperative to reconsider how they can be used to improve educational institutions and associated bodies. Opportunities for knowledge discovery in educational data have increased tremendously with digital revolution now as compared to the scenario in the past. Educational data is becoming increasingly rich as more and more educational systems are going online and collecting large amounts of data. In this paper a study of an enrollment dataset is presented. Copyright of BVICAM's International Journal of Information Technology is the property of Institute of Computer Applications & Management and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.
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    Web 3.0 in Education & Research
    (BIJIT - BVICAM’s International Journal of Information Technology Bharati Vidyapeeth’s Institute of Computer Applications and Management (BVICAM), New Delhi) Rajiv; Lal, Manohar
    The continuous evolution of the Internet has opened unimaginable opportunities and challenges in web based education and learning. The traditional version of web i.e. Web 1.0 started as a Read only medium; the next version Web 2.0 established itself as Read/Write medium. Now the currently evolving version of web, viz., Web 3.0 is said to be a technologically advanced medium which allows the users to Read/Write/Execute and also allows the machines to carry out some of the thinking so far expected only from the human beings. In a short time, Web 2.0 and now Web 3.0 have created new tools and technologies for facilitating web based education & learning. To begin with, this paper discusses some definitions of the Web 3.0, its evolution and characteristics. Next, we have discussed about the possible future Web 3.0 technologies, trends, tools and services that will assist in the areas of online learning, personalization and knowledge construction powered by the Semantic Web.