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  • 學位論文

應用程式正規化改善程式複雜度測量

Applying Program Normalization to Improve Software Complexity Metrics

指導教授 : 林金城
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摘要


軟體複雜度測量是軟體工程領域中的一個十分重要部分。測量方法大致上可分為宏觀測量與微觀測量。前者測量系統法雜度而後者針對程式複雜度。雖然已有許多有名的測量方法,但為提升測量準確性,新的測量方法不斷被發表。但是許多導致測量不準確的因素是來至測量目標。針對微觀測量方法與結構化程式,我們藉由對C語言的研究找出語法中可能導致測量不準確的因素。並且藉由程式的正規劃來改善測量的準確性。

並列摘要


Software complexity measurement is an essential part in the domain of software engineering. In measurement metrics developing, metrics was classed as two kinds, macro and micro. Macro complexity metrics consider the difficulty of system. Micro metrics are based on program code measuring. In order to enhance the measuring precision, people invent new metrics to replace famous metrics. But, many factors which cause imprecise measuring exist in measuring target. We focus on micro measuring and structure program. We find out the imprecision factors which hide in syntax via studying C language. And, we use program normalization to improve accuracy of measuring.

參考文獻


[1] Z. Ammarguellat, “A Control-Flow Normalization Algorithm and Its Complexity,” Software Engineering, IEEE Transactions on, Vol. 18, Issue 3, pp. 237-251, March 1992.
[2] T. Ball, J. R. Larus, “Using paths to measure, explain and enhance program behavior,” IEEE, Computer, Vol. 33, Issue 7, pp. 57-65, July 2000.
[5] N. Fenton, “Software Measurement: A Necessary Scientific Basis”, IEEE Tran. Software Eng., Vol. 20, No. 3, pp. 199-206, March 1994.
[11] Ling-Hsuan Huang, “Applying Computing Theory on Program Normalization for Quantitative Complexity Measurement,” 2001.
[12] IEEE Software Engineering Standards, Std. 610.12-1990.

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