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A lightweight approach to technical risk estimation via probabilistic impact analysis
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Source International Conference on Software Engineering archive
Proceedings of the 2006 international workshop on Mining software repositories table of contents
Shanghai, China
SESSION: Impact analysis table of contents
Pages: 98 - 104  
Year of Publication: 2006
ISBN:1-59593-397-2
Authors
Robert J. Walker  University of Calgary, Calgary, Alberta, Canada
Reid Holmes  University of Calgary, Calgary, Alberta, Canada
Ian Hedgeland  University of Calgary, Calgary, Alberta, Canada
Puneet Kapur  Chartwell Technology Inc., Calgary, Alberta, Canada
Andrew Smith  Chartwell Technology Inc., Calgary, Alberta, Canada
Sponsors
ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering
Publisher
ACM  New York, NY, USA
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ABSTRACT

An evolutionary development approach is increasingly commonplace in industry but presents increased difficulties in risk management, for both technical and organizational reasons. In this context, technical risk is the product of the probability of a technical event and the cost of that event. This paper presents a technique for more objectively assessing and communicating technical risk in an evolutionary development setting that (1) operates atop weakly-estimated knowledge of the changes to be made, (2) analyzes the past change history and current structure of a system to estimate the probability of change propagation, and (3) can be discussed vertically within an organization both with development staff and high-level management. A tool realizing this technique has been developed for the Eclipse IDE.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
L. A. Belady and M. M. Lehman. A model of large program development. IBM Systems J., 15(3):225--252, 1976.
 
2
 
3
C. Chittister and Y. Y. Haimes. Assessment and management of software technical risk. IEEE Trans. Systems, Man and Cybernetics, 24(2):187--202, 1994.
 
4
E. W. Dijkstra. A note on two problems in connection with graphs. Numerische Mathematik, 1:169--271, 1959.
5
 
6
 
7
8
9
 
10
11
 
12
A. Mockus and D. M. Weiss. Predicting risk of software changes. Bell Labs Technical J., 5(2):169--180, 2000.
 
13
 
14
15
16
17
 
18
19
 
20
 
21
O. Saliu and G. Ruhe. Software release planning for evolving systems. Innovations in Systems and Softw. Eng., 1(2), 2005. To appear.
22
23
 
24
 
25
R. J. Turver and M. Munro. An early impact analysis technique for software maintenance. J. Softw. Maintenance: Res. and Pract., 6:35--52, 1994.
 
26
R. J. Walker, R. Holmes, I. Hedgeland, P. Kapur, and A. Smith. A lightweight approach to technical risk estimation via probabilistic impact analysis. Tech. rep. 2006-817-10, Computer Science, Univ. of Calgary, 2006.
 
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L. A. Zadeh. Fuzzy sets. Information and Control, 8(3):338--353, 1965.
 
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Collaborative Colleagues:
Robert J. Walker: colleagues
Reid Holmes: colleagues
Ian Hedgeland: colleagues
Puneet Kapur: colleagues
Andrew Smith: colleagues