Robusta-一個對於Java例外處理壞味道的偵測工具

Robusta-A Tool for Exception Handling Bad Smell Detection for Java Programs

楊智傑(Chih-Chieh Yang)

指導教授 ： 謝金雲

國立臺北科技大學/電資學院/資訊工程系研究所/碩士(2013年)

https://doi.org/10.6841/NTUT.2013.00536

摘要

程式碼若存在壞味道，會降低程式品質，因此必須盡可能清除。由於例外處理機制之用途特殊，其壞味道型態顯然也會有所不同。現有的工具如PMD及FindBugs已經能著重於一般程式碼壞味道的偵測。本論文中，我們延續先前的例外處理壞味道工具，對其新增Overwritten Lead Exception的偵測能力並命名為Robusta。為了驗證Robusta之效益，我們選擇PMD與FindBugs，透過分析兩個常用的開放原始碼軟體──JFreeChart與Ant──做比較。實驗結果顯示，Robusta確實能夠偵測出更多例外處理中的壞味道。

關鍵字

壞味道 ； 例外處理 ； 強健度

並列摘要

Bad smells in code decrease code quality, so it must be removed. Since exception handling code is very different from code in normal flow, the bad smells in exception handling are very different from those in normal flow. Existing tools such as PMD and FindBugs have been developed with detecting bad smells in code for normal flow in mind. In this thesis, we continue our previous exception handling bad smell tool called Robusta by adding the capability of detecting overwritten lead exceptions. In order to verify the effectiveness of Robusta, we compare Robusta with PMD and FindBugs by applying them to analyze two popular open source software, JFreeChart and Ant. The result indicates that Robusta can indeed detect more bad smells in exception handling code.

並列關鍵字

bad smell ； exception handling ； robustness

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