Tracking down Exceptions in Standard ML Programs
Manuel Fahndrich and Jeffrey S. Foster and Jason Cu and Alexander Aiken
EECS Department, University of California, Berkeley
Technical Report No. UCB/CSD-98-996
, 1998
http://www2.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}, Year= {1998}, Month= {Feb}, Url= {http://www2.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://www2.eecs.berkeley.edu/Pubs/TechRpts/1998/5561.html %F Fahndrich:CSD-98-996