Amplification of automated tests via dynamic analysis

• Grant number: 23/00577-8
• Support Opportunities: Regular Research Grants
• Start date: April 01, 2023
• End date: September 30, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: André Takeshi Endo
• Grantee: André Takeshi Endo
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Associated scholarship(s): 24/13565-0 - Dynamic Analysis and Benchmarks for Flaky Test Dectection in Python Applications, BP.TT; 24/05445-5 - Dynamic Analysis and Benchmarks for Event Races in JavaScript Applications, BP.TT; 23/05945-5 - Dynamic Analysis and Benchmarks for Flaky Test Dectection in Python Applications, BP.TT; 23/05949-0 - Dynamic Analysis and Benchmarks for Event Races in JavaScript Applications, BP.TT

Abstract

Agile methods and their practices have fostered the widespread presence of automated tests in software projects. In practice, such test cases have been successfully and extensively adopted to test different software levels, from unit tests (e.g., xUnit frameworks) to end-to-end Graphical User Interface (GUI) tests (e.g., Selenium Webdriver). To increase the return on investment in testing, approaches have been proposed to reuse existing tests in the verification of other software characteristics. Such approaches, so called test amplification, could be notably powerful when supported by specific pieces of information collected from the software at runtime. This project aims to propose mechanisms to amplify automated tests using lightweight and targeted dynamic analysis. In particular, we are going to investigate how test amplification can be employed in two scenarios: (i) event race exploration, and (ii) flaky test detection. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

DUARTE, YOHAN; DURELLI, VINICIUS; NARDI, PAULO AUGUSTO; ENDO, ANDRE TAKESHI. Exploratory testing strategies for video games: an experience report. PROCEEDINGS OF THE 22ND BRAZILIAN SYMPOSIUM ON COMPUTER GAMES AND DIGITAL ENTERTAINMENT, SBGAMES, 2023, v. N/A, p. 10-pg., 2023-01-01. (23/00577-8, 22/13469-6)

REBELO DOS SANTOS, LUCIANA BRASIL; DE SOUZA, ERICA FERREIRA; ENDO, ANDRE TAKESHI; TRUBIANI, CATIA; PINCIROLI, RICCARDO; VIJAYKUMAR, NANDAMUDI LANKALAPALLI. Performance regression testing initiatives: a systematic mapping. INFORMATION AND SOFTWARE TECHNOLOGY, v. 179, p. 20-pg., 2024-12-18. (23/00577-8, 20/09835-1)

ARANTES, EVERTON; LOPES CORREA, ANA MARIA; DA SILVA PEREIRA, PEDRO HENRIQUE; FERNANDES, TANIA DE ARRUDA; TREVISAN, JOAO PEDRO; DURELLI, VINICIUS; ELER, MARCELO MEDEIROS; ENDO, ANDRE TAKESHI. Prime Control-IQD: a Platform for Software Quality Analytics. PROCEEDINGS OF THE 8TH BRAZILIAN SYMPOSIUM ON SYSTEMATIC AND AUTOMATED SOFT-WARE TESTING, SAST 2023, v. N/A, p. 3-pg., 2023-01-01. (23/00577-8)