Pruning Boolean Expressions to Shorten Dynamic Slices

Thomas Hirsch; Birgit Gertraud Hofer

doi:10.1109/SCAM55253.2022.00006

Pruning Boolean Expressions to Shorten Dynamic Slices

Thomas Hirsch, Birgit Gertraud Hofer

Institute of Software Technology (7160)

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

This paper presents a novel extension to dynamic slicing that we call pruned slicing. The proposed slicing approach produces smaller slices than traditional dynamic slicing. This is achieved by reasoning over Boolean expressions. We have implemented a prototype in Python and empirically evaluated its performance on three different benchmarks: TCAS, QuixBugs and the Refactory dataset. We show that pruned slicing reduces the size of dynamic slices on average by 10.96 percent for TCAS. For QuixBugs and the Refactory dataset, the slice size remains the same, but the number of Boolean expressions within the slice is reduced. Further, the empirical evaluation shows that pruned dynamic slicing comes with a low computational overhead compared to dynamic slicing. Pruned slicing can also be used in combination with relevant slicing.

Original language	English
Title of host publication	2022 IEEE 22nd International Working Conference on Source Code Analysis and Manipulation (SCAM)
Publisher	IEEE Computer Society
Number of pages	11
DOIs	https://doi.org/10.1109/SCAM55253.2022.00006
Publication status	Published - 3 Oct 2022
Event	2022 IEEE 22nd International Working Conference on Source Code Analysis and Manipulation: SCAM 2022 - Limassol, Cyprus Duration: 3 Oct 2022 → 4 Oct 2022 http://www.ieee-scam.org/2022

Conference

Conference	2022 IEEE 22nd International Working Conference on Source Code Analysis and Manipulation
Abbreviated title	SCAM 2022
Country/Territory	Cyprus
City	Limassol
Period	3/10/22 → 4/10/22
Internet address	http://www.ieee-scam.org/2022

Keywords

fault localization
dynamic slicing
relevant slicing
metamorphic testing

Fields of Expertise

Information, Communication & Computing

Treatment code (Nähere Zuordnung)

Basic - Fundamental (Grundlagenforschung)

Access to Document

10.1109/SCAM55253.2022.00006

FWF - AMADEUS - Automated Debugging in Use
Hofer, B. G.
1/01/20 → 30/04/24
Project: Research project

Cite this

@inproceedings{b9bb6f4c854447d891ea9d8a732ba8d4,

title = "Pruning Boolean Expressions to Shorten Dynamic Slices",

abstract = "This paper presents a novel extension to dynamic slicing that we call pruned slicing. The proposed slicing approach produces smaller slices than traditional dynamic slicing. This is achieved by reasoning over Boolean expressions. We have implemented a prototype in Python and empirically evaluated its performance on three different benchmarks: TCAS, QuixBugs and the Refactory dataset. We show that pruned slicing reduces the size of dynamic slices on average by 10.96 percent for TCAS. For QuixBugs and the Refactory dataset, the slice size remains the same, but the number of Boolean expressions within the slice is reduced. Further, the empirical evaluation shows that pruned dynamic slicing comes with a low computational overhead compared to dynamic slicing. Pruned slicing can also be used in combination with relevant slicing.",

keywords = "fault localization, dynamic slicing, relevant slicing, metamorphic testing",

author = "Thomas Hirsch and Hofer, {Birgit Gertraud}",

year = "2022",

month = oct,

day = "3",

doi = "10.1109/SCAM55253.2022.00006",

language = "English",

booktitle = "2022 IEEE 22nd International Working Conference on Source Code Analysis and Manipulation (SCAM)",

publisher = "IEEE Computer Society",

address = "United States",

note = "2022 IEEE 22nd International Working Conference on Source Code Analysis and Manipulation : SCAM 2022, SCAM 2022 ; Conference date: 03-10-2022 Through 04-10-2022",

url = "http://www.ieee-scam.org/2022",

}

TY - GEN

T1 - Pruning Boolean Expressions to Shorten Dynamic Slices

AU - Hirsch, Thomas

AU - Hofer, Birgit Gertraud

PY - 2022/10/3

Y1 - 2022/10/3

N2 - This paper presents a novel extension to dynamic slicing that we call pruned slicing. The proposed slicing approach produces smaller slices than traditional dynamic slicing. This is achieved by reasoning over Boolean expressions. We have implemented a prototype in Python and empirically evaluated its performance on three different benchmarks: TCAS, QuixBugs and the Refactory dataset. We show that pruned slicing reduces the size of dynamic slices on average by 10.96 percent for TCAS. For QuixBugs and the Refactory dataset, the slice size remains the same, but the number of Boolean expressions within the slice is reduced. Further, the empirical evaluation shows that pruned dynamic slicing comes with a low computational overhead compared to dynamic slicing. Pruned slicing can also be used in combination with relevant slicing.

AB - This paper presents a novel extension to dynamic slicing that we call pruned slicing. The proposed slicing approach produces smaller slices than traditional dynamic slicing. This is achieved by reasoning over Boolean expressions. We have implemented a prototype in Python and empirically evaluated its performance on three different benchmarks: TCAS, QuixBugs and the Refactory dataset. We show that pruned slicing reduces the size of dynamic slices on average by 10.96 percent for TCAS. For QuixBugs and the Refactory dataset, the slice size remains the same, but the number of Boolean expressions within the slice is reduced. Further, the empirical evaluation shows that pruned dynamic slicing comes with a low computational overhead compared to dynamic slicing. Pruned slicing can also be used in combination with relevant slicing.

KW - fault localization

KW - dynamic slicing

KW - relevant slicing

KW - metamorphic testing

U2 - 10.1109/SCAM55253.2022.00006

DO - 10.1109/SCAM55253.2022.00006

M3 - Conference paper

BT - 2022 IEEE 22nd International Working Conference on Source Code Analysis and Manipulation (SCAM)

PB - IEEE Computer Society

T2 - 2022 IEEE 22nd International Working Conference on Source Code Analysis and Manipulation

Y2 - 3 October 2022 through 4 October 2022

ER -

Pruning Boolean Expressions to Shorten Dynamic Slices

Abstract

Conference

Keywords

Fields of Expertise

Treatment code (Nähere Zuordnung)

Access to Document

Fingerprint

Projects

FWF - AMADEUS - Automated Debugging in Use

Cite this