Locating Core Modules through the Association between Software Source Structure and Execution

To improve software quality, the source code that composes software has to be improved, and improving the important code that largely affects the software quality should be a cost-effective method. Static analysis defines important codes as those that occupy important positions in the source network, while dynamic analysis defines important codes as those with high execution frequency. However, neither method analyzes the association between network structure and execution frequency, and both have their disadvantages. Thus, this study analyzed the association between source network structure and execution frequency to solve their disadvantages. The source function of Notepad++ was analyzed, and the function ranking was derived using the association between network structure and execution frequency. For verification, the Spearman correlation between the newly derived function ranking and the function ranking of the network and execution frequency obtained with the conventional method was measured. By measuring the Spearman correlation, the newly derived function ranking had strong correlations with execution frequency and included the network structure’s characteristics. Moreover, similar to the Pareto principle, the analysis showed that 20% of Notepad++’s functions could be categorized as important functions, largely affecting the software’s quality.

Modifikasi Algoritma Transportasi Fuzzy Menggunakan New Function Ranking

Salah satu langkah dalam algoritma transportasi <em>fuzzy</em> untuk penyelesaian masalah transportasi <em>fuzzy</em> yang mempunyai ranking biaya <em>fuzzy</em> sama yaitu memilih secara bebas biaya <em>fuzzy</em> yang mempunyai ranking sama untuk dijadikan sel basis. Padahal pemilihan secara bebas tersebut dapat berpengaruh terhadap solusi, iterasi, dan nilai optimal <em>fuzzy</em> yang dihasilkan. Oleh karena itu, pada artikel ini diperkenalkan suatu modifikasi algoritma transportasi <em>fuzzy</em> dengan menggunakan <em>new function ranking</em> yang diperoleh dari kombinasi antara metode perankingan bilangan <em>fuzzy</em> yaitu <em>ranking function</em> dan metode pembobotan yaitu <em>simple additive weighting</em>. Selanjutnya dilakukan simulasi numerik menggunakan modifikasi algoritma transportasi <em>fuzzy</em> dan hasilnya dibandingkan dengan algoritma yang sudah ada. Dari studi kasus diperoleh bahwa modifikasi algoritma transportasi <em>fuzzy</em> menghasilkan perankingan yang lebih baik, solusi dan nilai optimal <em>fuzzy</em> yang berbeda, serta iterasi yang lebih cepat dari algoritma transportasi yang sudah ada.

Statistical Hypothesis Test in Three Factor ANOVA Model under Fuzzy Environments Using Trapezoidal Fuzzy Numbers

This paper deals with the problem of three factor ANOVA model (Latin Square Design-LSD) test using Trapezoidal Fuzzy Numbers (tfns.). The proposed test is analysed under various types of trapezoidal fuzzy models such as Alpha Cut Interval, Membership Function, Ranking Function, Total Integral Value and Graded Mean Integration Representation. Finally a comparative view of the conclusions obtained from various test is given. Moreover, two numerical examples having different conclusions have been given for a concrete comparative study.