Filters

2011 - 20194
Reset filters

Settings

Has files: falseSubject: entropy

Search Results

Now showing 1 - 4 of 4
  • Thumbnail Image
    Article
    Citation - WoS: 12
    Citation - Scopus: 17
    Entropy as a Measure of Quality of Xml Schema Document
    (Zarka Private Univ, 2011) Basci, Dilek; Misra, Sanjay; Computer Engineering
    In this paper, a metric for the assessment of the structural complexity of eXtensible Markup Language schema document is formulated. The present metric 'Schema Entropy is based on entropy concept and intended to measure the complexity of the schema documents written in W3C XML Schema Language due to diversity in the structures of its elements. The SE is useful in evaluating the efficiency of the design of Schemas. A good design reduces the maintainability efforts. Therefore, our metric provides valuable information about the reliability and maintainability of systems. In this respect, this metric is believed to be a valuable contribution for improving the quality of XML-based systems. It is demonstrated with examples and validated empirically through actual test cases.
  • Thumbnail Image
    Conference Object
    Citation - Scopus: 4
    Abstract conceptual database model approach
    (2013) Çaĝiltay,N.E.; Topalli,D.; Aykaç,Y.E.; Tokdemir,G.
    One of the main objectives of the software engineers is to provide software related solutions for social problems and to increase the availability of social welfare. In that sense, the quality of the software is directly related to address the users' needs and their level of satisfaction. To reflect user requirements to the software processes, the correct design of the database model provides a critical stage during software development. Database design is a fundamental tool for modeling all the requirements related to users' data. The possible faulty conditions in database design have adverse effects on all of the software development processes. The possible faulty conditions can also cause continuous changes in the software and the desired functionality of the targeted system which may result in user dissatisfaction. In this context, reflecting the user requirements accurately in the database model and understanding of the database model correctly by every person involved in the software development process is the factor that directly affects the success of software systems' development. In this study, a two-stage conceptual data modeling approach is proposed to reduce the level of complexity, to improve the understandability of database models and to improve the quality of the software. This study first describes the proposed two-stage conceptual data modeling. Than the proposed method's impact on software engineers' comprehension is also investigated and the results are compared with the degree of complexity of the related conceptual data models. Results of this study show that, the proposed two-stage conceptual modeling approach improves the understanding levels of software engineers and eliminated possible defects in this stage. © 2013 The Science and Information Organization.
  • Thumbnail Image
    Article
    Citation - WoS: 29
    Citation - Scopus: 40
    Software Code Smell Prediction Model Using Shannon, Renyi and Tsallis Entropies
    (Mdpi, 2018) Gupta, Aakanshi; Suri, Bharti; Kumar, Vijay; Misra, Sanjay; Blazauskas, Tomas; Damasevicius, Robertas
    The current era demands high quality software in a limited time period to achieve new goals and heights. To meet user requirements, the source codes undergo frequent modifications which can generate the bad smells in software that deteriorate the quality and reliability of software. Source code of the open source software is easily accessible by any developer, thus frequently modifiable. In this paper, we have proposed a mathematical model to predict the bad smells using the concept of entropy as defined by the Information Theory. Open-source software Apache Abdera is taken into consideration for calculating the bad smells. Bad smells are collected using a detection tool from sub components of the Apache Abdera project, and different measures of entropy (Shannon, Renyi and Tsallis entropy). By applying non-linear regression techniques, the bad smells that can arise in the future versions of software are predicted based on the observed bad smells and entropy measures. The proposed model has been validated using goodness of fit parameters (prediction error, bias, variation, and Root Mean Squared Prediction Error (RMSPE)). The values of model performance statistics (R-2, adjusted R-2, Mean Square Error (MSE) and standard error) also justify the proposed model. We have compared the results of the prediction model with the observed results on real data. The results of the model might be helpful for software development industries and future researchers.
  • Thumbnail Image
    Article
    Citation - WoS: 20
    Citation - Scopus: 25
    Quantitative Quality Evaluation of Software Products by Considering Summary and Comments Entropy of a Reported Bug
    (Mdpi, 2019) Kumari, Madhu; Misra, Ananya; Misra, Sanjay; Fernandez Sanz, Luis; Damasevicius, Robertas; Singh, V. B.
    A software bug is characterized by its attributes. Various prediction models have been developed using these attributes to enhance the quality of software products. The reporting of bugs leads to high irregular patterns. The repository size is also increasing with enormous rate, resulting in uncertainty and irregularities. These uncertainty and irregularities are termed as veracity in the context of big data. In order to quantify these irregular and uncertain patterns, the authors have appliedentropy-based measures of the terms reported in the summary and the comments submitted by the users. Both uncertainties and irregular patterns have been taken care of byentropy-based measures. In this paper, the authors considered that the bug fixing process does not only depend upon the calendar time, testing effort and testing coverage, but it also depends on the bug summary description and comments. The paper proposed bug dependency-based mathematical models by considering the summary description of bugs and comments submitted by users in terms of the entropy-based measures. The models were validated on different Eclipse project products. The models proposed in the literature have different types of growth curves. The models mainly follow exponential, S-shaped or mixtures of both types of curves. In this paper, the proposed models were compared with the modelsfollowingexponential, S-shaped and mixtures of both types of curves.