A Program Slicer Using Def-Slice-Use Tables for Efficiently Slicing Both User-Defined and Library Functions
スポンサーリンク
概要
- 論文の詳細を見る
Program slicing is a technique for statically an-alyzing a program and extracting an executable sub-program, which is called a program slice, from the original program. This technique has been widely applied to program testing, debugging and maintenance. This paper presents a slicing method for extracting program slices from a program that calls library functions, which are provided as object code. The method this paper presents analyzes dependence relationships between library functions using global data that are referred to by the library functions but not explicitly declared in a program. In this method, before slicing a program with respect to a slicing criterion, a Def-Slice-Use table will be generated that stores slice information for each function in the program by slicing these functions in advance, and then the program can be efficiently sliced using this table. The paper also illustrates some examples of program slicing using a program slicer LibSlicer that implements this method.
- 社団法人電子情報通信学会の論文
- 2000-09-25
著者
-
Zhang X
Department Of Intelligent Image Information Division Of Regeneration And Advanced Medical Science Gr
-
Zhou Xiangrong
Department Of Intelligent Image Information Division Of Regeneration And Advanced Medical Sciences G
-
Zhou Xiangrong
Gifu Univ. Graduate School Of Medicine Gifu Jpn
-
Shimomura Takao
Dept.of Info.sci.& Intel.syst. University Of Tokushima
-
Zhang Xuejun
Fact. Of Eng. Gifu Univ
-
ZHANG Xinjun
Graduate School of Engineering, University of Tokushima
関連論文
- Brain CT Scoring Method Using Normal CT Scans to Detect Bain Damage for Emergency Medical Care(International Forum on Medical Imaging in Asia 2009 (IFMIA 2009))
- An improved powell method for registration of MRI and MRA (医用画像)
- Automated body cavity extraction and recognition based on non-contrast torso CT images(Joint Session 2)
- Improving the Detection of Microcalcifications in Masses by Artificial Neural Networks
- K-means clustering and classification of medical images based on regions-of-interest
- Development of an Automated Method for the Detection of Chronic Lacunar Infarct Regions in Brain MR Images(Image Recognition, Computer Vision)
- Classification of Cirrhotic Liver in MRI Images Using Texture Features
- An atlas-driven approach for automated recognition of liver structure in non-contrasted torso CT images
- Automatic Segmentation of Hepatic Tissue and 3D Volume Analysis of Cirrhosis in Multi-Detector Row CT Scans and MR Imaging(Biological Engineering)
- Detection of hepatic tumours on Multi-phase CT images for surgical plan
- Automated detection of chest nodules in 3D chest CT scans by using 2nd-order autocorrelation features
- Nodule Detection in 3D Chest CT Images Using 2nd Order Autocorrelation Features and GA Template Matching(Joint Session 1)
- A Program Slicer Using Def-Slice-Use Tables for Efficiently Slicing Both User-Defined and Library Functions
- Analysis of bone mineral density distribution at trabecular bones in thoracic and lumbar vertebrae using X-ray CT images