Debugging method based on a scalable dynamic analysis infrastructure

2015 Fiscal Year Final Research Report

• Project/Area Number: 25730037
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Software
• Research Institution: Tokyo Institute of Technology
• Principal Investigator: Kobayashi Takashi 東京工業大学, 情報理工学(系)研究科, 准教授 (50345386)
• Project Period (FY): 2013-04-01 – 2016-03-31
• Keywords: ソフトウェア工学 / 動的解析 / デバッグ

Outline of Final Research Achievements

Our main research aim is to support debugging task for a real-world software. In this research, we developed a scalable execution trace analysis framework and a novel technique to abstract execution traces through considering the software design intent. We also studied scalable and accurate fault localization techniques based on the analysis of dynamic data dependencies and detailed method level behavior.
We finally proposed a method to find the temporal specifications of API usage based on the selective inlining and data mining techniques. We also studied a method to extract the logical dependencies among methods based on the analysis of program change histories. Based on the combination of those proposed techniques methods, developer can be support to comprehend and debug large scale code.

Free Research Field

ソフトウェア工学