MediumDarwin: LittleDarwin Grows with Performance and Research-oriented Extensions
This program is tentative and subject to change.
Software testing is essential to ensure the reliability and correctness of software systems. However, the effectiveness of testing is highly dependent on the quality of the test suites themselves. Mutation analysis, a powerful technique for evaluating the quality of tests, introduces small changes into the code and checks whether the tests detect them. Despite its strengths, mutation analysis faces challenges in scalability due to the high computational cost of compiling and running tests against mutants.
This paper presents MediumDarwin, a substantially upgraded version of the original LittleDarwin, initially introduced as a research prototype. Our enhanced version retains the original foundational architecture but introduces significant new capabilities and performance optimisations that transform it into a robust platform for both industrial use and advanced research.
The enhancements made to LittleDarwin include include: (1) persistent storage of mutation results in a relational database to facilitate advanced analysis, (2) coverage-based test selection optimisation to minimise test executions, (3) implementation of mutant schemata to reduce compilation overhead, (4) enhanced mutation operators alongside safeguards against non-compilable mutants, and (5) dynamic subsumption graph computation for efficient mutant analysis. These innovations collectively improve the tool’s scalability and practical utility in software quality assurance in both industrial and research contexts.
A screencast demonstrating the use of MediumDarwin is available at https://www.youtube.com/watch?v=Zsd3pZt63AE.
This program is tentative and subject to change.
Thu 11 SepDisplayed time zone: Auckland, Wellington change
10:30 - 12:00 | Session 7 - Testing 2Registered Reports / Research Papers Track / Journal First Track / Tool Demonstration Track / Industry Track / NIER Track at Case Room 3 260-055 Chair(s): Jiajun Jiang Tianjin University | ||
10:30 15m | OptionFuzz: Fuzzing SMT Solvers with Optimized Option Exploration via Large Language Models Research Papers Track Yuhao Peng (Institute of Software, Chinese Academy of Sciences; University of Chinese Academy of Sciences), Jingzheng Wu Institute of Software, The Chinese Academy of Sciences, Xiang Ling Institute of Software, Chinese Academy of Sciences, Zhiyuan Li , Tianyue Luo (Institute of Software Chinese Academy of Sciences), Yanjun Wu Institute of Software, Chinese Academy of Sciences | ||
10:45 15m | Nüwa: Enhancing MLIR Fuzzing with LLM-Driven Generation and Adaptive Mutation Research Papers Track Bocan Cao Northwest University, Weiyuan Tong Northwest University, Zhanyong Tang Northwest University, Zixu Wang Northwest University, Hao Huang Northwest University, Yuheng Yan Northwest University | ||
11:00 10m | MediumDarwin: LittleDarwin Grows with Performance and Research-oriented Extensions Tool Demonstration Track Sajjad Hesamipour Khelejan School of Computer Science and Statistics, Trinity College Dublin & Research Ireland Lero, Thomas Laurent School of Computer Science and Statistics, Trinity College Dublin & Research Ireland Lero, Anthony Ventresque School of Computer Science and Statistics, Trinity College Dublin & Research Ireland Lero | ||
11:10 10m | Rethinking Cognitive Complexity for Unit Tests: Toward a Readability-Aware Metric Grounded in Developer Perception NIER Track Wendkuuni Arzouma Marc Christian OUEDRAOGO University of Luxembourg, Yinghua Li University of Luxembourg, Xueqi Dang University of Luxembourg, SnT, Xin Zhou Singapore Management University, Singapore, Anil Koyuncu Bilkent University, Jacques Klein University of Luxembourg, David Lo Singapore Management University, Tegawendé F. Bissyandé University of Luxembourg | ||
11:20 15m | Targeted Test Selection Approach in Continuous Integration Industry Track Pavel Plyusnin T-Technologies, Aleksey Antonov T-Technologies, Vasilii Ermakov T-Technologies, Aleksandr Khaybriev T-Technologies, Margarita Kikot T-Technologies, Nikolay Bushkov T-Technologies, Stanislav Moiseev T-Technologies DOI | ||
11:35 15m | An Empirical Investigation into the Capabilities of Anomaly Detection Approaches for Test Smell Detection Journal First Track Valeria Pontillo Gran Sasso Science Institute, Luana Martins University of Salerno, Ivan Machado Federal University of Bahia - UFBA, Fabio Palomba University of Salerno, Filomena Ferrucci Università di Salerno DOI Pre-print | ||
11:50 10mResearch paper | Assessing Reliability of Statistical Maximum Coverage Estimators in Fuzzing Registered Reports Danushka Liyanage University of Sydney, Australia, Nelum Attanayake University of Sydney, Australia, Zijian Luo University of Sydney, Australia, Rahul Gopinath University of Sydney DOI Pre-print | ||