Selective diagnostics for computing systems
Method and systems for generating an adjacency matrix A and a directional relation graph representing a relationship between one or more diagnostics. The adjacency matrix with all zero's is initialized. One or more entries in the adjacency matrix A are revised by, for each source diagnostic s, decreasing a corresponding count A(s,d) in the adjacency matrix A to decrease a corresponding directional relation in response to the diagnostic s failing and one or more other diagnostics d passing; increasing the corresponding count A(s,d) in the adjacency matrix A to increase the corresponding directional relation in response to the diagnostic s failing and one or more other diagnostics d failing; and maintaining a current value of the corresponding count A(s,d) in the adjacency matrix A in response to the diagnostic s passing or having no corresponding data. The directional relation graph is generated based on the adjacency matrix A.
1. A method for generating an adjacency matrix A and a directional relation graph representing a relationship between one or more diagnostics, the method comprising:
initializing the adjacency matrix with all zero's, where a row of the adjacency matrix A corresponds to a source diagnostic s of the one or more diagnostics, a column of the adjacency matrix A corresponds to a destination diagnostic d of the one or more diagnostics, and m represents a total count of the diagnostics;
revising one or more entries in the adjacency matrix A by, for each source diagnostics, decreasing a corresponding count A(s,d) in the adjacency matrix A to decrease a corresponding directional relation in response to the diagnostic s failing and one or more other diagnostics d passing; increasing the corresponding count A(s,d) in the adjacency matrix A to increase the corresponding directional relation in response to the diagnostic s failing and one or more other diagnostics d failing; and maintaining a current value of the corresponding count A(s,d) in the adjacency matrix A in response to the diagnostics passing or having no corresponding data; and
generating the directional relation graph based on the adjacency matrix A.
2. The method of claim 1 , further comprising repeating the revising operation for each of two or more time-stamped results in a user-defined time window.
3. The method of claim 1 , wherein a diagnostic result is represented in the adjacency matrix A by a one if the diagnostic passed, a −1 if the diagnostic failed, and a 0 in any other case.
4. The method of claim 1 , wherein a size of each node in the directional relation graph represents a frequency of failure of a corresponding diagnostic within a certain time window.
5. The method of claim 1 , wherein an edge weight in the directional relation graph represents a strength of a relation between two of the diagnostics.
6. The method of claim 5 , wherein the edge weight is based on a count of mutual diagnostic failures.
7. The method of claim 1 , further comprising identifying one or more clusters of nodes in the directional relation graph.
8. The method of claim 7 , further comprising analyzing the one or more clusters to determine a potential source of a diagnostic failure.
9. A non-transitory computer readable medium comprising computer executable instructions which when executed by a computer cause the computer to perform the method of:
initializing the adjacency matrix with all zero's, where a row of the adjacency matrix A corresponds to a source diagnostic s of the one or more diagnostics, a column of the adjacency matrix A corresponds to a destination diagnostic d of the one or more diagnostics, and m represents a total count of the diagnostics;
revising one or more entries in the adjacency matrix A by, for each source diagnostics, decreasing a corresponding count A(s,d) in the adjacency matrix A to decrease a corresponding directional relation in response to the diagnostic s failing and one or more other diagnostics d passing; increasing the corresponding count A(s,d) in the adjacency matrix A to increase the corresponding directional relation in response to the diagnostic s failing and one or more other diagnostics d failing; and maintaining a current value of the corresponding count A(s,d) in the adjacency matrix A in response to the diagnostics passing or having no corresponding data; and
generating the directional relation graph based on the adjacency matrix A.
10. The non-transitory computer readable medium of claim 9 , the method further comprising identifying one or more clusters of nodes in the directional relation graph.
11. The non-transitory computer readable medium of claim 10 , the method further comprising analyzing the one or more clusters to determine a potential source of a diagnostic failure.
12. An apparatus for generating an adjacency matrix A and a directional relation graph representing a relationship between one or more diagnostics, the apparatus comprising:
at least one processor; and
a memory storing instructions which, when executed by the at least one processor, cause the mobile device to perform a method comprising:
initializing the adjacency matrix with all zero's, where a row of the adjacency matrix A corresponds to a source diagnostic s of the one or more diagnostics, a column of the adjacency matrix A corresponds to a destination diagnostic d of the one or more diagnostics, and m represents a total count of the diagnostics;
revising one or more entries in the adjacency matrix A by, for each source diagnostics, decreasing a corresponding count A(s,d) in the adjacency matrix A to decrease a corresponding directional relation in response to the diagnostic s failing and one or more other diagnostics d passing; increasing the corresponding count A(s,d) in the adjacency matrix A to increase the corresponding directional relation in response to the diagnostic s failing and one or more other diagnostics d failing; and maintaining a current value of the corresponding count A(s,d) in the adjacency matrix A in response to the diagnostics passing or having no corresponding data; and
generating the directional relation graph based on the adjacency matrix A.
13. The apparatus of claim 12 , the method further comprising repeating the revising operation for each of two or more time-stamped results in a user-defined time window.
14. The apparatus of claim 12 , wherein a diagnostic result is represented in the adjacency matrix A by a one if the diagnostic passed, a −1 if the diagnostic failed, and a 0 in any other case.
15. The apparatus of claim 12 , wherein a size of each node in the directional relation graph represents a frequency of failure of a corresponding diagnostic within a certain time window.
16. The apparatus of claim 12 , wherein an edge weight in the directional relation graph represents a strength of a relation between two of the diagnostics.
17. The apparatus of claim 16 , wherein the edge weight is based on a count of mutual diagnostic failures.
18. The apparatus of claim 12 , the method further comprising identifying one or more clusters of nodes in the directional relation graph.
19. The apparatus of claim 18 , the method further comprising analyzing the one or more clusters to determine a potential source of a diagnostic failure.