Dads: dynamic slicing continuously-running distributed programs with budget constraints

Xiaoqin Fu; Haipeng Cai; Li Li

doi:10.1145/3368089.3417920

Dads: dynamic slicing continuously-running distributed programs with budget constraints

Xiaoqin Fu, Haipeng Cai, Li Li

Department of Software Systems & Cybersecurity

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

7 Citations (Scopus)

Abstract

We present Dads, the first distributed, online, scalable, and cost-effective dynamic slicer for continuously-running distributed programs with respect to user-specified budget constraints. Dads is distributed by design to exploit distributed and parallel computing resources. With an online analysis, it avoids tracing hence the associated time and space costs. Most importantly, Dads achieves and maintains practical scalability and cost-effectiveness tradeoffs according to a given budget on analysis time by continually and automatically adjusting the configuration of its analysis algorithm on the fly via reinforcement learning. Against eight real-world Java distributed systems, we empirically demonstrated the scalability and cost-effectiveness merits of Dads. The open-source tool package of Dads with a demo video is publicly available.

Original language	English
Title of host publication	ESEC/FSE'20 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering
Editors	Prem Devanbu, Myra Cohen, Thomas Zimmermann
Place of Publication	New York NY USA
Publisher	Association for Computing Machinery (ACM)
Pages	1566-1570
Number of pages	5
ISBN (Electronic)	9781450370431
DOIs	https://doi.org/10.1145/3368089.3417920
Publication status	Published - 2020
Event	Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering 2020 - Virtual, United States of America Duration: 8 Nov 2020 → 13 Nov 2020 Conference number: 28th https://dl.acm.org/doi/proceedings/10.1145/3368089 (Proceedings) https://2020.esec-fse.org (Website)

Conference

Conference	Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering 2020
Abbreviated title	ESEC/FSE 2020
Country/Territory	United States of America
City	Virtual
Period	8/11/20 → 13/11/20
Internet address	https://dl.acm.org/doi/proceedings/10.1145/3368089 (Proceedings) https://2020.esec-fse.org (Website)

Keywords

Distributed system
Dynamic slicing
Reinforcement learning

Access to Document

10.1145/3368089.3417920

338489477-oaFinal published version, 752 KB

Cite this

Fu, X., Cai, H., & Li, L. (2020). Dads: dynamic slicing continuously-running distributed programs with budget constraints. In P. Devanbu, M. Cohen, & T. Zimmermann (Eds.), ESEC/FSE'20 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering (pp. 1566-1570). Association for Computing Machinery (ACM). https://doi.org/10.1145/3368089.3417920

Fu, Xiaoqin ; Cai, Haipeng ; Li, Li. / Dads : dynamic slicing continuously-running distributed programs with budget constraints. ESEC/FSE'20 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. editor / Prem Devanbu ; Myra Cohen ; Thomas Zimmermann. New York NY USA : Association for Computing Machinery (ACM), 2020. pp. 1566-1570

@inproceedings{35a5e84aa9dd49c584e4cbcf4849a2f2,

title = "Dads: dynamic slicing continuously-running distributed programs with budget constraints",

abstract = "We present Dads, the first distributed, online, scalable, and cost-effective dynamic slicer for continuously-running distributed programs with respect to user-specified budget constraints. Dads is distributed by design to exploit distributed and parallel computing resources. With an online analysis, it avoids tracing hence the associated time and space costs. Most importantly, Dads achieves and maintains practical scalability and cost-effectiveness tradeoffs according to a given budget on analysis time by continually and automatically adjusting the configuration of its analysis algorithm on the fly via reinforcement learning. Against eight real-world Java distributed systems, we empirically demonstrated the scalability and cost-effectiveness merits of Dads. The open-source tool package of Dads with a demo video is publicly available.",

keywords = "Distributed system, Dynamic slicing, Reinforcement learning",

author = "Xiaoqin Fu and Haipeng Cai and Li Li",

year = "2020",

doi = "10.1145/3368089.3417920",

language = "English",

pages = "1566--1570",

editor = "Prem Devanbu and Myra Cohen and Thomas Zimmermann",

booktitle = "ESEC/FSE'20 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering",

publisher = "Association for Computing Machinery (ACM)",

address = "United States of America",

note = "Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering 2020, ESEC/FSE 2020 ; Conference date: 08-11-2020 Through 13-11-2020",

url = "https://dl.acm.org/doi/proceedings/10.1145/3368089, https://2020.esec-fse.org",

}

Fu, X, Cai, H & Li, L 2020, Dads: dynamic slicing continuously-running distributed programs with budget constraints. in P Devanbu, M Cohen & T Zimmermann (eds), ESEC/FSE'20 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. Association for Computing Machinery (ACM), New York NY USA, pp. 1566-1570, Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering 2020, Virtual, New York, United States of America, 8/11/20. https://doi.org/10.1145/3368089.3417920

Dads : dynamic slicing continuously-running distributed programs with budget constraints. / Fu, Xiaoqin; Cai, Haipeng; Li, Li.

ESEC/FSE'20 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. ed. / Prem Devanbu; Myra Cohen; Thomas Zimmermann. New York NY USA : Association for Computing Machinery (ACM), 2020. p. 1566-1570.

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

TY - GEN

T1 - Dads

T2 - Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering 2020

AU - Fu, Xiaoqin

AU - Cai, Haipeng

AU - Li, Li

N1 - Conference code: 28th

PY - 2020

Y1 - 2020

N2 - We present Dads, the first distributed, online, scalable, and cost-effective dynamic slicer for continuously-running distributed programs with respect to user-specified budget constraints. Dads is distributed by design to exploit distributed and parallel computing resources. With an online analysis, it avoids tracing hence the associated time and space costs. Most importantly, Dads achieves and maintains practical scalability and cost-effectiveness tradeoffs according to a given budget on analysis time by continually and automatically adjusting the configuration of its analysis algorithm on the fly via reinforcement learning. Against eight real-world Java distributed systems, we empirically demonstrated the scalability and cost-effectiveness merits of Dads. The open-source tool package of Dads with a demo video is publicly available.

AB - We present Dads, the first distributed, online, scalable, and cost-effective dynamic slicer for continuously-running distributed programs with respect to user-specified budget constraints. Dads is distributed by design to exploit distributed and parallel computing resources. With an online analysis, it avoids tracing hence the associated time and space costs. Most importantly, Dads achieves and maintains practical scalability and cost-effectiveness tradeoffs according to a given budget on analysis time by continually and automatically adjusting the configuration of its analysis algorithm on the fly via reinforcement learning. Against eight real-world Java distributed systems, we empirically demonstrated the scalability and cost-effectiveness merits of Dads. The open-source tool package of Dads with a demo video is publicly available.

KW - Distributed system

KW - Dynamic slicing

KW - Reinforcement learning

UR - http://www.scopus.com/inward/record.url?scp=85097150414&partnerID=8YFLogxK

U2 - 10.1145/3368089.3417920

DO - 10.1145/3368089.3417920

M3 - Conference Paper

AN - SCOPUS:85097150414

SP - 1566

EP - 1570

BT - ESEC/FSE'20 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering

A2 - Devanbu, Prem

A2 - Cohen, Myra

A2 - Zimmermann, Thomas

PB - Association for Computing Machinery (ACM)

CY - New York NY USA

Y2 - 8 November 2020 through 13 November 2020

ER -

Fu X, Cai H, Li L. Dads: dynamic slicing continuously-running distributed programs with budget constraints. In Devanbu P, Cohen M, Zimmermann T, editors, ESEC/FSE'20 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. New York NY USA: Association for Computing Machinery (ACM). 2020. p. 1566-1570 https://doi.org/10.1145/3368089.3417920

Dads: dynamic slicing continuously-running distributed programs with budget constraints

Abstract

Conference

Keywords

Access to Document

Other files and links

Cite this