Coverage-directed differential testing of JVM implementations

By Yuting Chen, Ting Su, Chengnian Sun, Zhendong Su, Jianjun Zhao. 2016

217 citations recorded by the source corpus.

Subfields: Hardware and Architecture, Software

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Hardware and Architecture

1. Suman Sekhar Jana
2. Angelos Dennis Keromytis
3. Yuting Chen
4. Sheng Wen
5. Abhik Roychoudhury
6. Salvatore J. Stolfo
7. Edward J. Schwartz
8. Sang Kil Cha

In Software

1. Suman Sekhar Jana
2. Yang Liu
3. Kexin Pei
4. Angelos Dennis Keromytis
5. Junfeng Yang
6. Ting Su
7. Yinzhi Cao
8. Yang Xiang

Citations in the corpus

• DeepXplore: Automated Whitebox Testing of Deep Learning Systems (2017, methodology): “Since then differential testing has been widely used for successfully testing various types of traditional software including JVMs [8], C compliers [31, 61], SSL/TLS certification validation logic [6, 9, 37, 46], PDF viewers [37], space flight software [20], mobile applications [25], and Web applica”
• Synthesizing benchmarks for predictive modeling (2017, methodology): “A mutation-based approach for the Java Virtual Machine is demonstrated in [38].”
• SFADiff: Automated Evasion Attacks and Fingerprinting Using Black-box Differential Automata Learning (2016, methodology): “Differential testing has been used successfully for testing a diverse set of systems including C compilers [32], Java virtual machine implementations [11], SSL/TLS implementations [8], mobile applications for privacy leaks [20], PDF malware detectors [31], and space flight software [18].”
• Coverage-Based Greybox Fuzzing as Markov Chain (2016, methodology): “[35] utilize MCMC to leverage knowledge about a mutation operator’s effectiveness.”
• The Art, Science, and Engineering of Fuzzing: A Survey (2018, background): “Several fuzzers [44], [178], [62] have used differential testing to identify discrepancies between similar programs, which are likely to indicate a bug.”
• NEZHA: Efficient Domain-Independent Differential Testing (2017, methodology): “Differential testing has been used successfully to find semantic bugs in diverse domains like SSL/TLS implementations [24], [32], C compilers [65], and JVM implementations [31].”
• Fuzzing: A Survey for Roadmap (2022, background): “Classfuzz [42] argues that the mutators that have explored more new states have a higher probability of being selected.”
• Guided, stochastic model-based GUI testing of Android apps (2017, methodology): “MCMC sampling is also used to guide fuzz testing of JVMs’ startup process [12], where mutators are selected on the basis of prior knowledge.”