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Large Language Models (LLMs) represent a leap in artificial intelligence, excelling in tasks using human language(s). Although the main focus of general-purpose LLMs is not code generation, they have shown promising results in the domain. However, th
Externí odkaz:
http://arxiv.org/abs/2401.16186
Autor:
Pramod, K. D., De Silva, W. T. N., Thabrew, W. U. K., Shariffdeen, Ridwan, Wickramanayake, Sandareka
Automated Program Repair (APR) improves developer productivity by saving debugging and bug-fixing time. While APR has been extensively explored for C/C++ and Java programs, there is little research on bugs in PHP programs due to the lack of a benchma
Externí odkaz:
http://arxiv.org/abs/2401.07356
Fuzz testing (fuzzing) is a well-known method for exposing bugs/vulnerabilities in software systems. Popular fuzzers, such as AFL, use a biased random search over the domain of program inputs, where 100s or 1000s of inputs (test cases) are executed p
Externí odkaz:
http://arxiv.org/abs/2308.00666
Automated Program Repair (APR) techniques typically rely on a given test-suite to guide the repair process. Apart from the need to provide test oracles, this makes the produced patches prone to test data over-fitting. In this work, instead of relying
Externí odkaz:
http://arxiv.org/abs/2308.00294
Malware detection plays a crucial role in cyber-security with the increase in malware growth and advancements in cyber-attacks. Previously unseen malware which is not determined by security vendors are often used in these attacks and it is becoming i
Externí odkaz:
http://arxiv.org/abs/2208.07049
Autor:
Seneviratne, Sachith, Kasthuriarachchi, Nuran, Rasnayaka, Sanka, Hettiachchi, Danula, Shariffdeen, Ridwan
Contactless and efficient systems are implemented rapidly to advocate preventive methods in the fight against the COVID-19 pandemic. Despite the positive benefits of such systems, there is potential for exploitation by invading user privacy. In this
Externí odkaz:
http://arxiv.org/abs/2112.07879
Automated program repair is an emerging technology that seeks to automatically rectify bugs and vulnerabilities using learning, search, and semantic analysis. Trust in automatically generated patches is necessary for achieving greater adoption of pro
Externí odkaz:
http://arxiv.org/abs/2108.13064
Akademický článek
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Publikováno v:
ACM Transactions on Software Engineering & Methodology; Dec2020, Vol. 30 Issue 1, p1-36, 36p
