Blogs (1) >>
ASE 2019
Sun 10 - Fri 15 November 2019 San Diego, California, United States
Wed 13 Nov 2019 15:00 - 15:20 at Hillcrest - Configurations and Variability Chair(s): Shin Hwei Tan

The significant rise in the complexity and configurations of software systems potentially requires a large number of test cases to test configurations of the systems. To deal with this challenge, we present a novel automated approach (termed as SBI) to implant existing test cases of software systems with the functionality to cover untested configurations of the software system; thus significantly reducing the effort to write new test cases to test the untested configurations. Our automated approach consists of two keys steps implemented into software components termed as Test Case Analyzer and Test Case Implanter. Test Case Analyzer automatically analyzes the code of test cases and generates a program dependence graph required by the second component. Test Case Implanter is implemented with a multi-objective search approach that searches for the most suitable test cases for implantation using search operators (i.e., selection, crossover, and mutation operators) followed by implanting the selected test cases by applying mutation operations focusing on adding, modifying, or deleting the test case source code. To guide the search, we defined various objectives: number of configuration variable values covered, pairwise coverage of parameter values of test API commands, number of implanted test cases, number of changed statements, and estimated execution time.
To assess the cost-effectiveness of our approach, we applied it to one industrial case study of video conferencing system and one open source case study. We experimented our approach (i.e., SBI) with three search algorithms: Non-dominated Sorting Genetic Algorithm II (NSGA-II), weight-based genetic algorithm (WGA), and random search (RS). In general, we found that the implanted test cases with SBI using the three algorithms had significantly higher configuration coverage than the original test cases for both case studies. When comparing the three algorithms with our approach, we found that NSGA-II performed the best. Specifically, SBI with NSGA-II managed to achieve, on average 19.3% higher number of configuration variable values and 57.0% higher pairwise coverage of parameter values of test API commands.

Wed 13 Nov

Displayed time zone: Tijuana, Baja California change

13:40 - 15:20
Configurations and VariabilityJournal First Presentations / Research Papers at Hillcrest
Chair(s): Shin Hwei Tan Southern University of Science and Technology
13:40
20m
Talk
ACTGAN: Automatic Configuration Tuning for Software Systems with Generative Adversarial Networks
Research Papers
Liang Bao School of Computer Science and Technology, XiDian University, Xin Liu Department of Computer Science, University of California, Davis, Fangzheng Wang School of Computer Science and Technology, XiDian University, Baoyin Fang School of Computer Science and Technology, XiDian University
14:00
20m
Talk
Automated N-way Program Merging for Facilitating Family-Based Analyses of Variant-Rich Software
Journal First Presentations
Dennis Reuling Software Engineering Group, University of Siegen, Udo Kelter Software Engineering Group, University of Siegen, Johannes B├╝rdek TU Darmstadt, Real-time Systems Lab, Malte Lochau TU Darmstadt
Link to publication DOI
14:20
20m
Talk
V2: Fast Detection of Configuration Drift in Python
Research Papers
Eric Horton North Carolina State University, Chris Parnin NCSU
Pre-print
14:40
20m
Talk
Feature-Interaction Aware Configuration Prioritization for Configurable Code
Research Papers
Son Nguyen The University of Texas at Dallas, Hoan Anh Nguyen Amazon, Ngoc Tran University of Texas at Dallas, Hieu Tran The University of Texas at Dallas, Tien N. Nguyen University of Texas at Dallas
15:00
20m
Talk
Search-based test case implantation for testing untested configurations
Journal First Presentations
Dipesh Pradhan Simula Research Laboratory, Norway, Shuai Wang Hong Kong University of Science and Technology, Tao Yue Nanjing University of Aeronautics and Astronautics & Simula Research Laboratory, Shaukat Ali Simula Research Lab, Marius Liaaen Cisco Systems
Link to publication