Impact analysis and adoption planning based on global where-used lists

• US 8,806,422 B2
• Filed: 10/27/2011
• Issued: 08/12/2014
• Est. Priority Date: 10/27/2011
• Status: Active Grant

• Current Assignee: SAP SE
• Original Assignee: SAP AG (SAP SE)
• Inventors: Brunswig, Frank, Klein, Udo, Meyringer, Michael, Gaiser, Tim, Handel, Holger, Renkes, Frank
• Primary Examiner(s): Khatri, Anil
• Application Number:
  US13/283,503
• Publication Number:
  US 20130111427A1
• Time in Patent Office: 1,020 Days
• Field of Search: 717100-102, 717/108, 717114-116
• US Class Current: 717/100
• CPC Class Codes: G06F 8/71 Version control security arrangements therefor G06F21/57; Configuration management

Abstract

Local dependency metadata can be collected from local metadata repositories of a plurality of development systems in a layered development system landscape, and a global where-used list that includes intra-layer and inter-layer dependencies between development entities in a layered development system landscape can be created, for example by aggregating the collected local dependency data. A usage metric quantifying how frequently each development entity is depended upon by other development entities in the layered development system landscape can be assigned to each development entity in the layered development system landscape. A measure of a relative effect of a change to one of the development entities on other development entities in the layered development system landscape can be promoted.

Claims

1. A computer program product comprising a non-transitory machine-readable medium storing instructions that, when executed by at least one programmable processor, cause the at least one programmable processor to perform operations comprising:

collecting local dependency metadata from local metadata repositories of a plurality of development entities in a layered development system landscape;

creating a global where-used list comprising intra-layer and inter-layer dependencies between development entities of the plurality of development entities, the creating comprising aggregating the local dependency metadata;

assigning a usage metric to each development entity of the plurality of development entities, the usage metric being optimized to calculate a global where-used list and adapted to quantify, based on the global where-used list, how frequently each development entity is depended upon by other development entities in the plurality of development entities; and

processing a measure of a relative effect of a change to one of the development entities on other development entities in the plurality of development entities, based on the usage metric for each development entity.

2. A computer program product as in claim 1, wherein the measure comprises at least one of a ranked list of most affected and most affecting development entities structure elements in the layered development system landscape corresponding to the development entities in the ranked list;

a visual depiction of relative impacts of changes to the development entities; and

a generated notification for delivery to one or more of a developer, a manager, and a development organization, the notification including a description of an impact that a proposed change to one of the development entities will have on a pre-defined key performance indicator for the layered development system landscape.

3. A computer program product as in claim 1, wherein the processing of the measure further comprises identifying a first development entity having a larger usage metric than a second development entity as having a greater potential error impact associated with changes to the first development entity.

4. A computer program product as in claim 1, wherein the usage metric comprises a number of direct and indirect usages of each development entity by other development entities in the layered development system landscape.

5. A computer program product as in claim 1, wherein the collecting comprises replicating the local dependency metadata to a global metadata repository, and the calculating further comprises reading the replicated local dependency metadata from the global metadata repository.

6. A computer program product as in claim 1, wherein the collecting comprises reading, at runtime, the local dependency metadata from the local metadata repositories, which are maintained in active system memory as part of a high performance in-memory database.

7. A system comprising:

at least one programmable processor; and

a machine-readable medium storing instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations comprising;

collecting local dependency metadata from local metadata repositories of a plurality of development entities in a layered development system landscape;

creating a global where-used list comprising intra-layer and inter-layer dependencies between development entities of the plurality of development entities, the creating comprising aggregating the local dependency metadata;

assigning a usage metric to each development entity of the plurality of development entities, the usage metric being optimized to calculate a global where-used list and adapted to quantify, based on the global where-used list, how frequently each development entity is depended upon by other development entities in the plurality of development entities; and

processing a measure of a relative effect of a change to one of the development entities on other development entities in the plurality of development entities, based on the usage metric for each development entity.

8. A system as in claim 7, wherein the measure comprises at least one of a ranked list of most affected and most affecting development entities structure elements in the layered development system landscape corresponding to the development entities in the ranked list;

a visual depiction of relative impacts of changes to the development entities; and

a generated notification for delivery to one or more of a developer, a manager, and a development organization, the notification including a description of an impact that a proposed change to one of the development entities will have on a pre-defined key performance indicator for the layered development system landscape.

9. A system as in claim 7, wherein the processing of the measure further comprises identifying a first development entity having a larger usage metric than a second development entity as having a greater potential error impact associated with changes to the first development entity.

10. A system as in claim 7, wherein the usage metric comprises a number of direct and indirect usages of each development entity by other development entities in the layered development system landscape.

11. A system as in claim 7, wherein the collecting comprises replicating the local dependency metadata to a global metadata repository, and the calculating further comprises reading the replicated local dependency metadata from the global metadata repository.

12. A system as in claim 7, wherein the collecting comprises reading, at runtime, the local dependency metadata from the local metadata repositories, which are maintained in active system memory as part of a high performance in-memory database.

13. A computer implemented method comprising:

collecting local dependency metadata from local metadata repositories of a plurality of development entities in a layered development system landscape;

creating a global where-used list comprising intra-layer and inter-layer dependencies between development entities of the plurality of development entities, the creating comprising aggregating the local dependency metadata;

assigning a usage metric to each development entity of the plurality of development entities, the usage metric being optimized to calculate a global where-used list and adapted to quantify, based on the global where-used list, how frequently each development entity is depended upon by other development entities in the plurality of development entities; and

processing a measure of a relative effect of a change to one of the development entities on other development entities in the plurality of development entities, based on the usage metric for each development entity;

wherein the collecting, creating, assigning and processing are performed by at least one system comprising computer hardware.

14. A computer implemented method as in claim 13, wherein the measure comprises at least one of a ranked list of most affected and most affecting development entities structure elements in the layered development system landscape corresponding to the development entities in the ranked list;

a visual depiction of relative impacts of changes to the development entities; and

a generated notification for delivery to one or more of a developer, a manager, and a development organization, the notification including a description of an impact that a proposed change to one of the development entities will have on a pre-defined key performance indicator for the layered development system landscape.

15. A computer implemented method as in claim 13, further comprising identifying a first development entity having a larger usage metric than a second development entity as having a greater potential error impact associated with changes to the first development entity.

16. A computer implemented method as in claim 13, wherein the usage metric comprises a number of direct and indirect usages of each development entity by other development entities in the layered development system landscape.

17. A computer implemented method as in claim 13, wherein the collecting comprises replicating the local dependency metadata to a global metadata repository, and the calculating further comprises reading the replicated local dependency metadata from the global metadata repository.

18. A computer implemented method as in claim 13, wherein the collecting comprises reading, at runtime, the local dependency metadata from the local metadata repositories, which are maintained in active system memory as part of a high performance in-memory database.

19. A computer implemented method as in claim 13, wherein at least one of the collecting, the creating, the assigning, and the promoting are performed by at least one programmable processor.