Paper Info
Title
Comparing Constraints Mined From Execution Logs to Understand Software Evolution
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. We present a motivating example and a preliminary evaluation based on a cyber-physical system controlling unmanned aerial vehicles. The results of our preliminary evaluation show that our approach can help to analyze changed behavior and thus contributes to understanding software evolution.
Year
DOI
Venue
2019
10.1109/ICSME.2019.00082
2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)
Keywords
Field
DocType
software evolution,constraint mining,dynamic analysis
Software engineering,Computer science,Source code,Software system,Theoretical computer science,Drone,Control system,Software evolution,Data mining algorithm
Conference
ISSN
ISBN
Citations 
1063-6773
978-1-7281-3095-8
0
PageRank 
References 
Authors
0.34
17
4
Name
Order
Citations
PageRank
Thomas Krismayer1102.51
Michael Vierhauser228025.55
Rick Rabiser3136979.63
Paul Grunbacher430625.59