Exception cause analysis during computer program execution

1. A method for cause analysis of configuration exceptions during the execution of computer programs on a computer, the method comprising:

executing an object code of a first program on the computer, the object code built before execution;

extracting exception information associated with a configuration exception, the configuration exception occurring during execution of the object code of the first program on the computer, wherein the configuration exception interrupts the flow of program execution of the first program;

looking up a set of possible causes from a knowledge base, wherein looking up the set of possible causes is based on context information related to the first program,

wherein the context information includes a version of a development tool that was changed before execution of the first program, wherein the context information includes changes recorded from a timestamp of a last successful execution of the first program, wherein the context information is augmented by one or more time-dependent tags,

wherein looking up the set of possible causes comprises calculating a first similarity metric from the context information,

wherein the calculating is performed by a cognitive system configured to utilize unsupervised learning with clustering; and

providing, concurrently with the configuration exception and based on the set of possible causes, a solution from the knowledge base, wherein the solution is based on confidence levels of machine learning, wherein the solution is improved based on provided confirmation information.

2. The method of claim 1 , wherein the context information comprises at least one of characteristic of an execution environment where the first program is executed, characteristic of a development environment applied to generate the first program, or the object code of the first program.

3. The method of claim 1 , wherein the context information comprises change information, the change information describing at least one change carried out on an execution environment or a development environment or on the object code of the first program.

4. The method of claim 1 , wherein the first similarity metric from the context information is related to the first program and further context information stored in the knowledge base and associated with a possible cause stored in the knowledge base.

5. The method of claim 4 , wherein looking up the possible causes comprises calculating a second similarity metric from the extracted exception information and further exception information stored in the knowledge base and associated with the possible cause stored in the knowledge base.

6. The method of claim 4 , wherein the exception information comprises a character string and calculating the first similarity metric comprises determining a string similarity.

7. A computer program product comprising a computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code executed by a processor configured to:

execute an object code of a first program on a computer, the object code built before execution;

extract exception information associated with a configuration exception, the configuration exception occurring during execution of the object code of the first program on the computer, wherein the configuration exception interrupts the flow of program execution of the first program;

retrieve a set of possible causes from a knowledge base, wherein retrieving the set of possible causes is based on context information related to the first program,

wherein the context information includes a version of a development tool that was changed before execution of the first program, wherein the context information includes changes recorded from a timestamp of a last successful execution of the first program, wherein the context information is augmented by one or more time-dependent tags,

wherein retrieving the set of possible causes comprises calculating a first similarity metric from the context information,

wherein the calculating is performed by a cognitive system configured to utilize unsupervised learning with clustering; and

provide, concurrently with the configuration exception and based on the set of possible causes, a solution from the knowledge base, wherein the solution is based on confidence levels of machine learning, wherein the solution is improved based on provided confirmation information.

8. The computer program product of claim 7 , wherein the context information comprises at least one of characteristic of an execution environment where the first program is executed, characteristic of a development environment applied to generate the first program, or the object code of the first program.

9. The computer program product of claim 7 , wherein the context information comprises change information, the change information describing at least one change carried out on an execution environment or a development environment or on the object code of the first program.

10. The computer program product of claim 7 , wherein the first similarity metric from the context information is related to the first program and further context information stored in the knowledge base and associated with a possible cause stored in the knowledge base.

11. The computer program product of claim 10 , wherein retrieve the possible causes comprises calculating a second similarity metric from the extracted exception information and further exception information stored in the knowledge base and associated with the possible cause stored in the knowledge base.

12. The computer program product of claim 10 , wherein the exception information comprises a character string and calculating the first similarity metric comprises determining a string similarity.

13. A system for cause analysis of configuration exceptions during the execution of computer programs, the system comprising:

a memory; and

a processor, the processor communicatively coupled to the memory, the processor configured to:

execute an object code of a first program, the object code built before execution;

extract exception information associated with a configuration exception, the configuration exception occurring during execution of the object code of the first program, wherein the configuration exception interrupts the flow of program execution of the first program;

obtain a set of possible causes from a knowledge base, wherein obtaining the set of possible causes is based on context information related to the first program,

wherein the context information includes a version of a development tool that was changed before execution of the first program, wherein the context information includes changes recorded from a timestamp of a last successful execution of the first program, wherein the context information is augmented by one or more tags,

wherein obtaining the set of possible causes comprises calculating a first similarity metric from the context information,

wherein the calculating is performed by a cognitive system configured to utilize unsupervised learning with clustering; and

provide, concurrently with the configuration exception and based on the set of possible causes, a solution from the knowledge base, wherein the solution is based on confidence levels of machine learning, wherein the solution is improved based on provided confirmation information.

14. The system of claim 13 , wherein the context information comprises at least one of characteristic of an execution environment where the first program is executed, characteristic of a development environment applied to generate the first program, or the object code of the first program.

15. The system of claim 13 , wherein the context information comprises change information, the change information describing at least one change carried out on an execution environment or a development environment or on the object code of the first program.

16. The system of claim 13 , wherein the first similarity metric from the context information is related to the first program and further context information stored in the knowledge base and associated with a possible cause stored in the knowledge base.

17. The system of claim 16 , wherein obtain the set of possible causes comprises calculating a second similarity metric from the extracted exception information and further exception information stored in the knowledge base and associated with the possible cause stored in the knowledge base.

18. The system of claim 16 , wherein the exception information comprises a character string and calculating the first similarity metric comprises determining a string similarity.

19. The system of claim 13 , wherein the development tool is not present on the system.

20. The system of claim 13 , wherein the one or more tags include at least one time-dependent tag.