Automatic Detection and Masking of Non-Atomic Exception Handling

Research output: Contribution to book/conference proceedings/anthology/reportConference contributionContributed

Contributors

  • Christof Fetzer - , AT&T (Author)
  • Karin Hogstedt - , AT&T (Author)
  • Pascal Felber - , Institut Eurecom (Author)

Abstract

Developing robust applications is a challenging task. Al-though modern programming languages like C++ and Java provide sophisticated exception handling mechanisms to detect and correct runtime error conditions, exception handling code must still be programmed with care to preserve application consistency. In particular, exception handling is only effective if the premature termination of a method due to an exception does not leave an object in an inconsistent state. We address this issue by introducing the notion of failure atomicity in the context of exceptions and novel techniques to automatically detect and mask non-atomic exception handling. These techniques can be applied to applications written in several different programming languages, and can be used even when the application’s source code is not available. We perform experimental evaluation on both C++ and Java applications to demonstrate the effectiveness of our techniques and measure the overhead that they introduce.

Details

Original languageEnglish
Title of host publication2003 International Conference on Dependable Systems and Networks
Pages445-454
Number of pages10
Publication statusPublished - 2003
Peer-reviewedNo
Externally publishedYes

Conference

TitleInternational Conference on Dependable Systems and Networks 2003
Abbreviated titleDSN 2003
Duration22 - 25 June 2003
Degree of recognitionInternational event
CitySan Francisco
CountryUnited States of America

External IDs

Scopus 1542359982

Keywords

Research priority areas of TU Dresden

DFG Classification of Subject Areas according to Review Boards

Keywords

  • Robustness, Programming profession, computer lanuages, Java, Runtime, Applicatioin software, Error correction codes, Performance evaluation, software measurement, software performance