Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

Tracking down Exceptions in Standard ML Programs

Manuel Fahndrich, Jeffrey S. Foster, Jason Cu and Alexander Aiken

EECS Department
University of California, Berkeley
Technical Report No. UCB/CSD-98-996
February 1998

http://www.eecs.berkeley.edu/Pubs/TechRpts/1998/CSD-98-996.pdf

We describe our experiences with an exception analysis tool for Standard ML. Information about exceptions gathered by the analysis is visualized using PAM, a program visualization tool for EMACS. We study the results of the analysis of three well-known programs, classifying exceptions as assertion failures, error exceptions,control-flow exceptions, and pervasive exceptions. Even though the analysis is often conservative and reports many spurious exceptions, we have found it useful for checking the consistency of error and control-flow exceptions. Furthermore, using our tools, we have uncovered two minor exception-related bugs in the three programs we scrutinized.


BibTeX citation:

@techreport{Fahndrich:CSD-98-996,
    Author = {Fahndrich, Manuel and Foster, Jeffrey S. and Cu, Jason and Aiken, Alexander},
    Title = {Tracking down Exceptions in Standard ML Programs},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {1998},
    Month = {Feb},
    URL = {http://www.eecs.berkeley.edu/Pubs/TechRpts/1998/5561.html},
    Number = {UCB/CSD-98-996},
    Abstract = {We describe our experiences with an exception analysis tool for Standard ML. Information about exceptions gathered by the analysis is visualized using PAM, a program visualization tool for EMACS. We study the results of the analysis of three well-known programs, classifying exceptions as assertion failures, error exceptions,control-flow exceptions, and pervasive exceptions. Even though the analysis is often conservative and reports many spurious exceptions, we have found it useful for checking the consistency of error and control-flow exceptions. Furthermore, using our tools, we have uncovered two minor exception-related bugs in the three programs we scrutinized.}
}

EndNote citation:

%0 Report
%A Fahndrich, Manuel
%A Foster, Jeffrey S.
%A Cu, Jason
%A Aiken, Alexander
%T Tracking down Exceptions in Standard ML Programs
%I EECS Department, University of California, Berkeley
%D 1998
%@ UCB/CSD-98-996
%U http://www.eecs.berkeley.edu/Pubs/TechRpts/1998/5561.html
%F Fahndrich:CSD-98-996