Comparing Constraints Mined From Execution Logs to Understand Software Evolution

Thomas Krismayer, Michael Vierhauser, Rick Rabiser, Paul Grünbacher

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Complex software systems evolve frequently, e.g., when introducing new features or fixing bugs during maintenance. However, understanding the impact of such changes on system behavior is often difficult. Many approaches have thus been proposed that analyze systems before and after changes, e.g., by comparing source code, model-based representations, or system execution logs. In this paper, we propose an approach for comparing run-time constraints, synthesized by a constraint mining algorithm, based on execution logs recorded before and after changes. Specifically, automatically mined constraints define the expected timing and order of recurring events and the values of data elements attached to events. Our approach presents the differences of the mined constraints to users, thereby providing a higher-level view on software evolution and supporting the analysis of the impact of changes on system behavior.
Original languageEnglish
Title of host publicationProceedings of the 35th International Conference on Software Maintenance and Evolution, September 30-Ocotober 4, 2019, Cleveland, OH, USA
PublisherIEEE
Pages491-495
Number of pages5
DOIs
Publication statusPublished - Oct 2019

Fields of science

  • 202005 Computer architecture
  • 202017 Embedded systems
  • 102 Computer Sciences
  • 102002 Augmented reality
  • 102006 Computer supported cooperative work (CSCW)
  • 102015 Information systems
  • 102020 Medical informatics
  • 102022 Software development
  • 102034 Cyber-physical systems
  • 201132 Computational engineering
  • 201305 Traffic engineering
  • 207409 Navigation systems
  • 502032 Quality management
  • 502050 Business informatics

JKU Focus areas

  • Digital Transformation

Cite this