Software Product Quality Management Methodology & the Quantitative Assessment of Analyzability Indicators
Boumedyen Shannaq1, Richmond Adebiaye2
1Boumedyen Shannaq*, MIS , University of Buraimi, Al buraimi, 968, Sultanate of Oman.
2Richmond Adebiaye, Dept. of Informatics & Engineering Systems, University of South Carolina Upstate, Spartanburg, USA.
Manuscript received on March 16, 2020. | Revised Manuscript received on March 24, 2020. | Manuscript published on March 30, 2020. | PP: 2403-2408 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7780038620/2020©BEIESP | DOI: 10.35940/ijrte.F7780.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The research paper developed a new software metric methodology for evaluating the analyzability indicator for software products. The proposed research methodology provided an objective and quantitative assessment in accordance with the requirements, limitations, purpose and specific features of software products. Forty-one (41) java programs were analyzed to extract and evaluate the software metrics described in ‘Halstead metrics. The mathematical classification model was developed to replace the expert output in the evaluating process as related to the software metric indicators. The output of the algorithm was applied to identify the metrics with the greatest analyzability influence. The result indicated that 13 measured metrics with 98% of “analyzability” are relevant to seven (7) software code metrics with the remaining six (6) metrics making up only ~ 5% of “analyzability”. The analyzed ROC-curves were similarly computed to test the performance of the proposed methodology compared to the expert’s metric evaluation. The ROC-curves indicator for the proposed methodology showed resultant scores of ROC = 7.4 as compared to 7.3 from the experts’ evaluation. However, both methods were correlated effectively after analytical computations with a resultant performance which showed that the proposed method outperforms the expert’s evaluation.
Keywords: Software Metrics; Software Quality; Quantitative Assessment; Analyzability
Scope of the Article: Software & System Quality of Service.