2003Unpublished venueRequires access

Slicing methods using static and dynamic analysis information

Y Ashida, Fumiaki Ohata, Koji Inoue

Open publisher page 10 citations

Abstract

In this paper, we propose four slicing methods using both static and dynamic analysis information. (1) Statement-mark slice removes the unnecessary statements using an execution history of the statements. (2) Partial program analysis reduces the static analysis cost using invocation history of procedures. (3) Dynamic data dependence analysis extracts precise data dependence relations using dynamic data dependence analysis. (4) Array and pointer analysis improves the efficiency of (3) by dynamically analyzing pointer and array variables only. Using both dynamic and static information, we show that the precision of the slicing is improved with smaller run-time overhead.

About this research paper

What this paper is about

In this paper, we propose four slicing methods using both static and dynamic analysis information. (1) Statement-mark slice removes the unnecessary statements using an execution history of the statements. (2) Partial program analysis reduces the static analysis cost using invocation history of procedures. (3) Dynamic data dependence analysis extracts precise data dependence relations using dynamic data dependence analysis. (4) Array and pointer analysis improves the efficiency of (3) by dynamically analyzing pointer and array variables only. Using both dynamic and static information, we show that the precision of the slicing is improved with smaller run-time overhead.

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Available abstract

In this paper, we propose four slicing methods using both static and dynamic analysis information. (1) Statement-mark slice removes the unnecessary statements using an execution history of the statements. (2) Partial program analysis reduces the static analysis cost using invocation history of procedures. (3) Dynamic data dependence analysis extracts precise data dependence relations using dynamic data dependence analysis. (4) Array and pointer analysis improves the efficiency of (3) by dynamically analyzing pointer and array variables only. Using both dynamic and static information, we show that the precision of the slicing is improved with smaller run-time overhead.

Key concepts: Slicing, Static analysis, Program slicing, Computer science, Pointer (user interface), Dependence analysis, Pointer analysis, Dynamic data

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