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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Compiler
Putra, I Putu Aditya
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Computer Science & IT Electrical & Electronics Engineering

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Software Defects Predictions using SQL Complexity and Naïve Bayes Subali, Made Agus Putra; Sugiartha, I Gusti Rai Agung; Adnyana, I Made Budi; Putra, I Putu Aditya; Subawa, Made Dai
Compiler Vol 14, No 1 (2025): May
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i1.2979

Abstract

Software defects result in unreliable software, therefore predicting software defects is an effort to produce quality software. In this study, we used the naïve bayes method because it has the appropriate characteristics of the data used. The data used include NASA MDP datasets and datasets from the calculation of the sql complexity method on eight software modules. The use of two datasets was carried out because in the NASA MDP datasets there were no attributes that paid attention to the use of sql commands, therefore in the datasets from the eight software modules the sql complexity attribute was included which paid attention to the level of complexity of the use of sql commands in each module. The prediction results of this study were evaluated by considering the values of accuracy, precision, recall, and f-measure. Based on these results, the accuracy results of CM1 were 88%, PC2 was 97%, and KC3 was 78%.
Development of SLOC, CC, SQL Complexity Methods to Measure the Level of Similarity Complexity of Software Modules Subali, Made Agus Putra; Sugiartha, I Gusti Rai Agung; Putra, I Putu Aditya
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.27150

Abstract

Software metrics are often used to reflect vulnerabilities in program code to measure the complexity of each software module. Knowing the complexity of each software module is an important thing to do because the project manager can analyze defects that may occur, costs spent, work schedules, and the resources needed. In this research, we aim to apply the SLOC, CC, SQL Complexity method in measuring the level of similarity of complexity between software modules by paying attention to the level of similarity of the syntactic structure of program logic and SQL commands, by knowing the similarity between software modules the project manager can predict the effort required. Based on the results of the level of equality for the eight modules, an average of 90% was obtained. The high results are due to the third feature used having a high level of similarity. In further research, other features will be added and weighting will be given to each feature.
Co-Authors I Gusti Rai Agung Sugiartha I Made Budi Adnyana, I Made Budi Subali, Made Agus Putra Subawa, Made Dai