A computer system includes a processor and a memory device. The computer system is configured to execute a function that builds a software instance definition object. The software instance definition object includes one or more configuration items, attributes, permissions, and linkages to other objects, which define a software instance. The computer system temporarily stores the software instance definition object in the memory device. The computer system updates at least one of the configuration items, attributes, permissions, and linkages to other objects of the stored software instance definition object, thereby creating an updated software instance definition object. A fix command is then executed to update the software instance based on the updated software instance definition object, thereby creating an updated software instance. After creating the updated software instance, the software instance definition object is deleted from the memory device.

A computer device is provided that includes a processor configured to receive a source code for a program including at least two code files, and process the source code for the program to generate a machine-level code file for each of the at least two code files of the source code. The processor is further configured to generate control flow graph data for each machine-level code file generated for the at least two code files of the source code, generate a machine-level intermediate representation for each machine-level code file using a machine-level code file and the generated control flow graph data for that machine-level code file, merge the machine-level intermediate representations into a merged machine-level intermediate representation, and perform machine-level optimizations on the merged machine-level intermediate representation and output an optimized merged machine-level intermediate representation.

A system including at least one processor programmed to translate a policy into policy code, wherein: the policy is provided in a policy language; the policy code is in a programming language that is different from the policy language; and the policy includes a statement that maps an entity name to one or more metadata symbols to be associated with an entity in a target system against which the policy is to be enforced

A system including at least one processor programmed to translate a policy into policy code, wherein: the policy is provided in a policy language; the policy code is in a programming language that is different from the policy language; and the policy includes a statement that maps an entity name to one or more metadata symbols to be associated with an entity in a target system against which the policy is to be enforced

A system including at least one processor programmed to identify, based on a policy to be enforced, one or more metadata symbols corresponding to an entity name; identify, from a target description describing a target system, an entity description matching the entity name, wherein the entity description describes an entity of the target system; and apply a metadata label to the entity of the target system, wherein the metadata label is based on the one or more metadata symbols corresponding to the entity name, as identified based on the policy.

A system including at least one processor programmed to identify, based on a policy to be enforced, one or more metadata symbols corresponding to an entity name; identify, from a target description describing a target system, an entity description matching the entity name, wherein the entity description describes an entity of the target system; and apply a metadata label to the entity of the target system, wherein the metadata label is based on the one or more metadata symbols corresponding to the entity name, as identified based on the policy.

This application discloses an image file obtaining method, including: determining a first value of each of N tasks in program source code (501), where the first value is first duration required for executing each of the N tasks or the first value is a ratio of the first duration to second duration, the second duration is duration required for loading each of the N tasks, and N is a positive integer; sorting the N tasks in descending order of the first values (502); and linking the sorted N tasks to obtain an image file (503). According to the method, after downloading the image file, an embedded apparatus successively loads and executes the N tasks, thereby shortening a startup time period of the embedded apparatus.

This application discloses an image file obtaining method, including: determining a first value of each of N tasks in program source code (501), where the first value is first duration required for executing each of the N tasks or the first value is a ratio of the first duration to second duration, the second duration is duration required for loading each of the N tasks, and N is a positive integer; sorting the N tasks in descending order of the first values (502); and linking the sorted N tasks to obtain an image file (503). According to the method, after downloading the image file, an embedded apparatus successively loads and executes the N tasks, thereby shortening a startup time period of the embedded apparatus.

A computer device is provided that includes a processor configured to receive a source code for a program including at least two code files, and process the source code for the program to generate a machine-level code file for each of the at least two code files of the source code. The processor is further configured to generate control flow graph data for each machine-level code file generated for the at least two code files of the source code, generate a machine-level intermediate representation for each machine-level code file using a machine-level code file and the generated control flow graph data for that machine-level code file, merge the machine-level intermediate representations into a merged machine-level intermediate representation, and perform machine-level optimizations on the merged machine-level intermediate representation and output an optimized merged machine-level intermediate representation.

Specific images of an OS are built using only the driver bindings that are necessary to link the OS to the particular hardware of a client device. A device tree of the client device is analyzed to identify the hardware components. Databases of different hardware source code for various hardware drivers are maintained and used to craft the driver bindings and instances for the hardware of the client device. The device tree is also analyzed to identify compatibility strings of the various hardware on the client device. The hardware source code is searched for these compatibility strings to see if a driver exists in the databases of hardware source code. Specific driver bindings and driver instances with the actual variable names and configuration parameters of the identified hardware drivers are then generated and included in an image of the OS that may be installed on the client device.