research-article

Using data provenance to improve software process enactment, monitoring and analysis

Author:

Gabriella Castro Barbosa CostaAuthors Info & Claims

ICSE '16: Proceedings of the 38th International Conference on Software Engineering Companion

Pages 875 - 878

https://doi.org/10.1145/2889160.2889255

Published: 14 May 2016 Publication History

Abstract

A practice to support software processes continuous improvement is to reuse the knowledge acquired in previous executions. One way to capture process execution data is by using data provenance models. Data provenance refers to the origin, lineage or source of data. In computational terms, provenance is a historical record of the derivation of data that can help in its understanding. But, does the provenance data be used to contribute to the software process improvement? Based on this question, the approach proposed in this work aims to apply data provenance to support software process execution, monitoring and analysis phases as well as software process improvement as a whole. To achieve this goal, data provenance, ontology and predefined metrics were used in a pilot case study, considering software processes used in two real software development companies. With this study, two types of implicit information were derived: (1) information about artifacts that can increase new process instances runtime, and (2) information related to new agents that can be added to execute a task and contribute to the reduction of the task runtime.

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Cited By

Schreiber Avon Kurnatowski Lde Boer C(2021)Analyzing Software Engineering Processes with Provenance-based Knowledge Graphs2021 IEEE Aerospace Conference (50100)10.1109/AERO50100.2021.9438358(1-11)Online publication date: 6-Mar-2021
https://doi.org/10.1109/AERO50100.2021.9438358
Packer HChapman ACarr LMoyer TRoy S(2019)GitHub2PROVProceedings of the 11th USENIX Conference on Theory and Practice of Provenance10.5555/3359032.3359039(5-5)Online publication date: 3-Jun-2019
https://dl.acm.org/doi/10.5555/3359032.3359039
Wolfengagen VIsmailova LKosikov SParfenova IErmak MPetrov VNikulin IKholodov V(2016)Migration of the IndividualsProcedia Computer Science10.1016/j.procs.2016.07.44988(359-364)Online publication date: 2016
https://doi.org/10.1016/j.procs.2016.07.449

Index Terms

Using data provenance to improve software process enactment, monitoring and analysis
1. Applied computing
  1. Enterprise computing
    1. Business process management
      1. Business process monitoring

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Published In

cover image ACM Conferences

ICSE '16: Proceedings of the 38th International Conference on Software Engineering Companion

May 2016

946 pages

ISBN:9781450342056

DOI:10.1145/2889160

General Chair:
Laura Dillon
Michigan State University
,
Program Chairs:
Willem Visser
Stellenbosch University, South Africa
,
Laurie Williams
North Carolina State University

Copyright © 2016 ACM.

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IEEE-CS\TCSE: TC on Software Engineering
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Published: 14 May 2016

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ICSE '16: 38th International Conference on Software Engineering

May 14 - 22, 2016

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Cited By

Schreiber Avon Kurnatowski Lde Boer C(2021)Analyzing Software Engineering Processes with Provenance-based Knowledge Graphs2021 IEEE Aerospace Conference (50100)10.1109/AERO50100.2021.9438358(1-11)Online publication date: 6-Mar-2021
https://doi.org/10.1109/AERO50100.2021.9438358
Packer HChapman ACarr LMoyer TRoy S(2019)GitHub2PROVProceedings of the 11th USENIX Conference on Theory and Practice of Provenance10.5555/3359032.3359039(5-5)Online publication date: 3-Jun-2019
https://dl.acm.org/doi/10.5555/3359032.3359039
Wolfengagen VIsmailova LKosikov SParfenova IErmak MPetrov VNikulin IKholodov V(2016)Migration of the IndividualsProcedia Computer Science10.1016/j.procs.2016.07.44988(359-364)Online publication date: 2016
https://doi.org/10.1016/j.procs.2016.07.449

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