ACM Home Page
Please provide us with feedback. Feedback
HATARI: raising risk awareness
Full text PdfPdf (414 KB)
Source Foundations of Software Engineering archive
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering table of contents
Lisbon, Portugal
SESSION: Research tool demonstrations I table of contents
Pages: 107 - 110  
Year of Publication: 2005
ISBN:1-59593-014-0
Also published in ...
Authors
Jacek Śliwerski  Max-Planck-Institut für Informatik, Saarbrücken, Germany
Thomas Zimmermann  Saarland University, Saarbrücken, Germany
Andreas Zeller  Saarland University, Saarbrücken, Germany
Sponsors
SIGSOFT: ACM Special Interest Group on Software Engineering
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 5,   Downloads (12 Months): 37,   Citation Count: 9
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1081706.1081725
What is a DOI?

ABSTRACT

As a software system evolves, programmers make changes which sometimes lead to problems. The risk of later problems significantly depends on the location of the change. Which are the locations where changes impose the greatest risk? Our HATARI prototype relates a version history (such as CVS) to a bug database (such as BUGZILLA) to detect those locations where changes have been risky in the past. HATARI makes this risk visible for developers by annotating source code with color bars. Furthermore, HATARI provides views to browse through the most risky locations and to analyze the risk history of a particular location.


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
 
2
 
3
 
4
 
5
 
6
A. Mockus and D. M. Weiss. Predicting risk of software changes. Bell Labs Technical Journal, 5(2):169--180, April--June 2000.
7
8
9
 
10
T. Zimmermann and P. Weiβgerber. Preprocessing CVS data for fine-grained analysis. In Proc. International Workshop on Mining Software Repositories (MSR 2004), pages 2--6, Edinburgh, Scotland, UK, May 2004.

CITED BY  9

Collaborative Colleagues:
Jacek Śliwerski: colleagues
Thomas Zimmermann: colleagues
Andreas Zeller: colleagues