以執行監測爲基礎之別名分析

Abstract

在許多程式分析中，別名分析扮演了一個重要的角色。跟傳統缺乏動態資訊的靜態別名分析相比，使用執行監測的方法具有極大的潛力，因爲並不需要做過度的預測。在這篇論文中，我們提出一個用執行監測的框架以用來做別名分析。我們發現使用執行監測的方法可以比傳統的靜態別名分析獲得更多的非別名答案。儘管我們可以獲得更準確的別名分析，但執行時間並沒有太多的成長。我們也針對文本性質和域性質分別做了探討，並發現在文本性質中，非環式的方式較其他的方法有效以及域性質對別名分析是有很大的影響等結論。

Alias analysis plays an important role in various program analyses Comparing to traditional static alias analysis which struggles for precision under the lack of dynamic information, profile techniques show a great potential in this area since they don't need to make any over-approximation. In this paper, we propose an framework which uses profile techniques to perform alias analysis. We can get more 52 % queries than the worst case for 429.mcf. We also find that although we have a more accurate alias analysis, the performance has insignificance gain. And we simulate several schemes in context sensitivity and field sensitivity. We find that acyclic scheme in context sensitivity is useful and field sensitivity is important for alias analysis.