Name
Abstract | ||
|---|---|---|
Aspect-oriented programming (AOP) is a programmatic methodology to handle better modularized code by separating crosscutting concerns from the traditional abstraction boundaries. Automated testing, as one of the most demanding needs of the software development to reduce both human effort and costs, is a delicate issue in testing aspect-oriented programs. Prior studies in the automated test generation for aspect-oriented programs have been very limited with respect to the need for both adequate tool support and capability concerning effectiveness and efficiency. This paper describes a new AOP-specific tool for testing aspect-oriented programs, called RAMBUTANS. The RAMBUTANS tool uses a directed random testing technique that is especially well suited for generating tests for aspectual features in AspectJ. The directed random aspect of the tool is parameterized by associating weights to aspects, advice, methods, and classes by controlling object and joint point creations during the test generation process. We present a comprehensive empirical evaluation of our tool against the current AOP test generation approaches on three industrial aspect-oriented projects. The results of the experimental and statistical tests showed that RAMBUTANS tool produces test suites that have higher fault-detection capability and efficiency for AspectJ-like programs. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s10009-016-0432-3 | STTT |
Keywords | Field | DocType |
Software testing, Automated test generation, Testing tool, Aspect-oriented programming, Object-oriented programming, AspectJ | Parameterized complexity,Abstraction,Random testing,Programming language,Aspect-oriented programming,Object-oriented programming,Computer science,AspectJ,Software development,Statistical hypothesis testing | Journal |
Volume | Issue | ISSN |
19 | 6 | 1433-2787 |
Citations | PageRank | References |
0 | 0.34 | 37 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Reza Meimandi Parizi | 1 | 264 | 29.36 |
| Abdul Azim Abdul | 2 | 145 | 21.87 |
| Sai Peck Lee | 3 | 142 | 22.55 |
| Saif ur Rehman Khan | 4 | 3 | 1.44 |