Paper Info
Title
GRT: Program-Analysis-Guided Random Testing (T)
Abstract
We propose Guided Random Testing (GRT), which uses static and dynamic analysis to include information on program types, data, and dependencies in various stages of automated test generation. Static analysis extracts knowledge from the system under test. Test coverage is further improved through state fuzzing and continuous coverage analysis. We evaluated GRT on 32 real-world projects and found that GRT outperforms major peer techniques in terms of code coverage (by 13 %) and mutation score (by 9 %). On the four studied benchmarks of Defects4J, which contain 224 real faults, GRT also shows better fault detection capability than peer techniques, finding 147 faults (66 %). Furthermore, in an in-depth evaluation on the latest versions of ten popular real-world projects, GRT successfully detects over 20 unknown defects that were confirmed by developers.
Year
DOI
Venue
2015
10.1109/ASE.2015.49
Automated Software Engineering
Keywords
Field
DocType
Automatic test generation, random testing, static analysis, dynamic analysis
Code coverage,Data mining,System under test,Fuzz testing,Random testing,Computer science,Fault detection and isolation,Static analysis,Software bug,Algorithm,Theoretical computer science,Program analysis
Conference
ISSN
Citations 
PageRank 
1527-1366
22
0.70
References 
Authors
36
6
Name
Order
Citations
PageRank
Lei Ma135734.63
Cyrille Artho258844.46
Cheng Zhang3442.26
Hiroyuki Sato410125.20
Johannes Gmeiner5381.73
Rudolf Ramler630436.20