Abstract: A method and an apparatus for implementing a derivative NFT and a computer-readable storage medium are disclosed, and the method includes providing a smart contract and changing an owner of each of one or more source NFTs to the provided smart contract, minting a derivative NFT in the provided smart contract, with the derivative NFT representing derivative works derived from works represented by the one or more source NFTs, and recording a derivation relationship between the derivative NFT and the one or more source NFTs. With the use of the method, there is provided a way of representing the derivative works on the blockchain in such a way that the derivation of the derivative works from the source works is clearly indicated, thereby enabling the on-chain transaction of the derivative works.

Abstract: A method and an apparatus for minting an NFT, as well as a method and an apparatus for verifying a role associated with an NFT are disclosed. The method for minting an NFT includes: acquiring metadata of an NFT to be minted, where the metadata includes a role type of each of at least one role associated with the NFT to be minted and a common name corresponding to the role type; signing the metadata, by each of the at least one role, using a private key that corresponds to a public key contained in a digital identity certificate of the role, to obtain a signature by the role; and minting an NFT on chain based on the metadata. As such, the authenticity of information in the metadata can be verified by the signatures.

Abstract: Mechanisms for analyzing computer instructions implementing a program in which typestate analysis is informed by concurrency analysis. The concurrency-guided typestate analysis may simulate the “worst case” scenario due to thread interleaving by transitioning a simulated state of the variable to a special state whenever the variable is not guarded by its intended guarding lock. While in the special state, the analysis may assume that the state of the simulated variable is the worst possible state with respect to processing operations that may lead to an error depending on the state of the variable. Thus, the analysis performed may assume that referencing the variable in a state-dependent operation while the simulated state of the variable is in the special state may lead to an error, and the analysis may generate a warning, accordingly. The analysis may process the computer instructions to infer which lock is intended to guard a shared variable.

Abstract: Mechanisms for analyzing computer instructions implementing a program in which typestate analysis is informed by concurrency analysis. The concurrency-guided typestate analysis may simulate the “worst case” scenario due to thread interleaving by transitioning a simulated state of the variable to a special state whenever the variable is not guarded by its intended guarding lock. While in the special state, the analysis may assume that the state of the simulated variable is the worst possible state with respect to processing operations that may lead to an error depending on the state of the variable. Thus, the analysis performed may assume that referencing the variable in a state-dependent operation while the simulated state of the variable is in the special state may lead to an error, and the analysis may generate a warning, accordingly. The analysis may process the computer instructions to infer which lock is intended to guard a shared variable.

Abstract: A concurrent program is analyzed for the presence of data races by the creation of a sequential program from the concurrent program. The sequential program contains assertions which can be verified by a sequential program analysis tool, and which, when violated, indicate the presence of a data race. The sequential program emulates multiple executions of the concurrent program by nondeterministically scheduling asynchronous threads of the concurrent program on a single runtime stack and nondeterministically removing the currently-executing thread from the stack before instructions of the program. Checking functions are used to provide assertions for data races, along with a global access variable, which indicates if a variable being analyzed for data races is currently being accessed by any threads.

Abstract: A concurrent program is analyzed for the presence of data races by the creation of a sequential program from the concurrent program. The sequential program contains assertions which can be verified by a sequential program analysis tool, and which, when violated, indicate the presence of a data race. The sequential program emulates multiple executions of the concurrent program by nondeterministically scheduling asynchronous threads of the concurrent program on a single runtime stack and nondeterministically removing the currently-executing thread from the stack before instructions of the program. Checking functions are used to provide assertions for data races, along with a global access variable, which indicates if a variable being analyzed for data races is currently being accessed by any threads.