SSBSE 2022
Thu 17 - Fri 18 November 2022 Singapore
co-located with ESEC/FSE 2022
Thu 17 Nov 2022 11:00 - 11:30 at ERC SR 9 - Session 1 Chair(s): Ezekiel Soremekun

Search-based test case generation approaches make use of static type information to determine which data types should be used for the creation of new test cases. Dynamically typed languages like JavaScript, however, do not have this type information. In this paper, we propose an unsupervised probabilistic type inference approach to infer data types within the test case generation process. We evaluated the proposed approach on a benchmark of 98 units under test (i.e., exported classes and functions) compared to random type sampling w.r.t. branch coverage. Our results show that our type inference approach achieves a statistically significant increase in 56% of the test files with up to 71% of branch coverage compared to the baseline.

Thu 17 Nov

Displayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change

11:00 - 12:30
Session 1Research Papers / RENE / NIER at ERC SR 9
Chair(s): Ezekiel Soremekun SnT, University of Luxembourg
Guess What: Test Case Generation for Javascript with Unsupervised Probabilistic Type Inference
Research Papers
Dimitri Stallenberg Delft University of Technology, Mitchell Olsthoorn Delft University of Technology, Annibale Panichella Delft University of Technology
Pre-print Media Attached File Attached
Improving Search-based Android Test Generation using Surrogate Models
Research Papers
Michael Auer University of Passau, Felix Adler University of Passau, Gordon Fraser University of Passau
Media Attached File Attached
Applying Combinatorial Testing to Verification-Based Fairness Testing
Takashi Kitamura , Zhenjiang Zhao Graduate School of Informatics and Engineering, University of Electro-Communications, Tokyo, Japan, Takahisa Toda The University of Electro-Communications