Methods, apparatus, systems, and articles of manufacture are disclosed to generate usage dependent code embeddings. An example apparatus includes parsing circuitry to select a usage context of a code snippet including at least one line of code (LOC) before the code snippet or an LOC at which the code snippet is called, the code snippet, and at least one LOC after the code snippet or the LOC. The example apparatus additionally includes embedding circuitry to generate a first list of token embedding vectors for first tokens of a second list of tokens for the code snippet and a third list of token embedding vectors for second tokens of a fourth list of tokens for the usage context. The example apparatus also includes concatenation circuitry to concatenate a transformed token embedding vector of a close token and a fifth list of transformed token embedding vectors for the first list.

In a dynamic computing environment, it is a nontrivial task to verify code running in the environment because most approaches to software similarity require extensive and time-consuming analysis of a binary, or the approaches fail to recognize executables that are similar but nonidentical. A biosequence-based method for quantifying similarity of executable binaries is used to identify allowed codes in a real-world multi-user environment.

In a code analysis method, a code analysis system obtains information about a service scenario that represents an objective of code analysis. The code analysis system generates a code analysis algorithm for the service scenario based on the information about the service scenario. When code analysis needs to be performed, the code analysis system obtains information about source code and object code that are specified by a user, and analyzes similarity between the source code and the object code according to the code analysis algorithm to obtain an analysis result. The similarity between the source code and the object code is analyzed according to the code analysis algorithm generated based on the information about the service scenario, to obtain the analysis result that meets a requirement of the service scenario.

Systems, computer program products, and methods are described herein for discovery and analysis of software distributed across an electronic network platform of an entity. The present invention is configured to continuously monitor one or more hardware devices associated with a technology environment; initiate an open source code discovery engine on the one or more hardware devices, wherein initiating further comprises automatically populating a first database with at least the portion of the one or more applications that match the attributes associated with open source code identifiers; and initiate an approval and enforcement engine on at least the portion of the one or more applications stored on the first database.

A method for the identification of similarities and dissimilarities of mappings between the elements of a first model and the elements of a second model, an element being one of: an object, a link, a node, a class, an attribute, an activity, a flow, etc., wherein the method uses a processor for performing a model mining of the elements of both models in accordance with pre-defined rules and through at least two of the following analyses: a semantic analysis of the elements; a syntactic and/or structural analysis of the elements; a data-based analysis of the elements; and wherein based on these analyses and potentially also based on pre-performed mappings, similarities and dissimilarities mappings between the elements of the first model and the second model are identified and are provided to a user.

An apparatus for detecting code cloning of software includes a memory in which a program configured to detect code cloning from software is stored; and a processor configured to execute the program. Wherein the processor extracts multiple functions from a source code corresponding to the software, performs normalization and abstraction and compares the normalized and abstracted multiple functions with a vulnerable code clone set to determine whether there is code cloning of the software, and the vulnerable code clone set includes multiple vulnerable codes which are extracted from multiple functions included in other software, and normalized, abstracted and then stored.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating signatures for source code elements. One of the methods includes generating a respective signature for each source code element of the plurality of source code elements, including obtaining a name of the source code element, obtaining one or more of a location of a compilation unit containing the source code element and contents of the compilation unit containing the source code element, and generating the signature including combining a first representation of the name of the source code element and one or more of a second representation of the location of the compilation unit and a third representation of the contents of the compilation unit containing the source code element, wherein at least two of the plurality of source code elements have a same name and different respective signatures.

Systems and methods for identifying a characteristic of an input code by converting the input code into simplified code and using the simplified code to generate snippets that can be compared to code in a database. Preferably, code is simplified by at least one of: unifying of capitalization, removing characters, and replacing at least one of a character and a keyword with an identifier.

According to some exemplary embodiments of the present disclosure, a method for identifying open source software (OSS) components using a processor of a computing device is disclosed. The method for identifying open source software (OSS) components may include: constructing a component database by performing redundancy elimination for each of a plurality of open source software; and identifying a component of target software by using the component database.

An embodiment of the present invention is directed to a code audit tool that intelligently analyzes and profiles code, such as Python code, based on a variety of previously unmeasured factors and metrics including a set of software dimensions, such as Algorithmic Complexities; Software Sizing Metrics; Anti-Pattern Implementations; Maintainability Metrics; Dependency Mappings; Runtime Metrics; Testing Metrics; and Security Metrics. Once this analysis is complete, a standardized report card or other scoring interface may be generated. This may include analytical findings as well as suggestions and recommend steps so that developers can make informed decisions, enhance their code bases and improve the score assigned to their code.