poster

Text mining in supporting software systems risk assurance

Authors:

LiGuo Huang,

Daniel Port,

Liang Wang,

Tao Xie,

Tim MenziesAuthors Info & Claims

ASE '10: Proceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering

Pages 163 - 166

https://doi.org/10.1145/1858996.1859027

Published: 20 September 2010 Publication History

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Abstract

Insufficient risk analysis often leads to software system design defects and system failures. Assurance of software risk documents aims to increase the confidence that identified risks are complete, specific, and correct. Yet assurance methods rely heavily on manual analysis that requires significant knowledge of historical projects and subjective, perhaps biased judgment from domain experts. To address the issue, we have developed RARGen, a text mining-based approach based on well-established methods aiming to automatically create and maintain risk repositories to identify usable risk association rules (RARs) from a corpus of risk analysis documents. RARs are risks that have frequently occurred in historical projects. We evaluate RARGen on 20 publicly available e-service projects. Our evaluation results show that RARGen can effectively reason about RARs, increase confidence and cost-effectiveness of risk assurance, and support difficult-to-perform activities such as assuring complete-risk identification.

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Cited By

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Amasaki SAman HYokogawa T(2022)An extended study on applicability and performance of homogeneous cross-project defect prediction approaches under homogeneous cross-company effort estimation situationEmpirical Software Engineering10.1007/s10664-021-10103-427:2Online publication date: 27-Jan-2022
https://dl.acm.org/doi/10.1007/s10664-021-10103-4
Amasaki SAman HYokogawa TMinku LMenzies TNagappan M(2020)An exploratory study on applicability of cross project defect prediction approaches to cross-company effort estimationProceedings of the 16th ACM International Conference on Predictive Models and Data Analytics in Software Engineering10.1145/3416508.3417118(71-80)Online publication date: 8-Nov-2020
https://dl.acm.org/doi/10.1145/3416508.3417118
Choetkiertikul MDam HTran TGhose AGrundy J(2018)Predicting Delivery Capability in Iterative Software DevelopmentIEEE Transactions on Software Engineering10.1109/TSE.2017.269398944:6(551-573)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1109/TSE.2017.2693989
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Index Terms

Text mining in supporting software systems risk assurance
1. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. System management
        Quality assurance

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Information & Contributors

Information

Published In

ASE '10: Proceedings of the 25th IEEE/ACM International Conference on Automated Software Engineering

September 2010

534 pages

ISBN:9781450301169

DOI:10.1145/1858996

General Chair:
Charles Pecheur
Université catholique de Louvain, Belgium
,
Program Chairs:
Jamie Andrews
University of Western Ontario, Canada
,
Elisabetta Di Nitto
Politecnico di Milano, Italy

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 September 2010

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ASE10

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ASE10: IEEE/ACM International Conference on Automated Software Engineering

September 20 - 24, 2010

Antwerp, Belgium

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Overall Acceptance Rate 82 of 337 submissions, 24%

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Cited By

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Amasaki SAman HYokogawa T(2022)An extended study on applicability and performance of homogeneous cross-project defect prediction approaches under homogeneous cross-company effort estimation situationEmpirical Software Engineering10.1007/s10664-021-10103-427:2Online publication date: 27-Jan-2022
https://dl.acm.org/doi/10.1007/s10664-021-10103-4
Amasaki SAman HYokogawa TMinku LMenzies TNagappan M(2020)An exploratory study on applicability of cross project defect prediction approaches to cross-company effort estimationProceedings of the 16th ACM International Conference on Predictive Models and Data Analytics in Software Engineering10.1145/3416508.3417118(71-80)Online publication date: 8-Nov-2020
https://dl.acm.org/doi/10.1145/3416508.3417118
Choetkiertikul MDam HTran TGhose AGrundy J(2018)Predicting Delivery Capability in Iterative Software DevelopmentIEEE Transactions on Software Engineering10.1109/TSE.2017.269398944:6(551-573)Online publication date: 1-Jun-2018
https://dl.acm.org/doi/10.1109/TSE.2017.2693989
Herbold STrautsch AGrabowski J(2017)Global vs. local models for cross-project defect predictionEmpirical Software Engineering10.1007/s10664-016-9468-y22:4(1866-1902)Online publication date: 1-Aug-2017
https://dl.acm.org/doi/10.1007/s10664-016-9468-y
Choetkiertikul MDam HTran TGhose APenta MPinzger MRobbes R(2015)Characterization and prediction of issue-related risks in software projectsProceedings of the 12th Working Conference on Mining Software Repositories10.5555/2820518.2820552(280-291)Online publication date: 16-May-2015
https://dl.acm.org/doi/10.5555/2820518.2820552
Choetkiertikul MDam HTran TGhose A(2015)Characterization and Prediction of Issue-Related Risks in Software Projects2015 IEEE/ACM 12th Working Conference on Mining Software Repositories10.1109/MSR.2015.33(280-291)Online publication date: May-2015
https://doi.org/10.1109/MSR.2015.33
Razavi AInkpen DFalcon RAbielmona R(2014)Textual risk mining for maritime situational awareness2014 IEEE International Inter-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA)10.1109/CogSIMA.2014.6816558(167-173)Online publication date: Mar-2014
https://doi.org/10.1109/CogSIMA.2014.6816558
Menzies TTurhan B(2013)Beyond data mining; towards "idea engineering"Proceedings of the 9th International Conference on Predictive Models in Software Engineering10.1145/2499393.2499401(1-6)Online publication date: 9-Oct-2013
https://dl.acm.org/doi/10.1145/2499393.2499401
Dey LVerma I(2013)Text-Driven Multi-structured Data Analytics for Enterprise IntelligenceProceedings of the 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT) - Volume 0310.1109/WI-IAT.2013.186(213-220)Online publication date: 17-Nov-2013
https://dl.acm.org/doi/10.1109/WI-IAT.2013.186
Port DNikora AHihn JHuang LTaylor RGall HMedvidović N(2011)Experiences with text mining large collections of unstructured systems development artifacts at jplProceedings of the 33rd International Conference on Software Engineering10.1145/1985793.1985891(701-710)Online publication date: 21-May-2011
https://dl.acm.org/doi/10.1145/1985793.1985891
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