1. Software Architecture Risk Assessment (SARA) Tool Khader Shaik, Wallid Abdelmoez, Dr. Hanny Ammar Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV 26506-6109 This work is funded in part by grants to West Virginia University Research Corp. from the National Science Foundation (NSF-ITR) Program, and from the NASA Office of Safety and Mission Assurance (OSMA) through the NASA Independent Verification and Validation (IV&V) Facility, Fairmont, West Virginia.

2. Outline Introduction Functional Requirements Architecture Demo Conclusion and Future Work

3. Introduction A sound architecture is the means to build a software system with high quality attributes. As architecture became a more significant artifact in developing software systems, the need to quantitatively analyze the architecture has become eminent. Risk assessment helps projects to avoid unpredicted catastrophic problems. Also, it largely prevents wrong allocation of resources.

4. According to NASA-STD-8719.13A standard, risk is a function of the anticipated frequency of occurrence of an undesired event, the potential severity of resulting consequences, and the uncertainties associated with the frequency and severity. In this paper, we present a tool that support architectural level model-based risk assessment, which includes –Maintainability based risk –Reliability based risk and –Requirements based risk. Introduction (contd..)

5. Maintainability-based risk – takes into account the probability that the software product will need to endure a certain type of maintenance and the consequences of performing this maintenance on the system. Reliability-based risk: – takes into account the probability that the software product will fail in the operational environment and the consequences of that failure.. Requirements-based risk – deals with the probability that the software will experience a requirement failure and the consequences of such failures.

6. Functional Requirements It extends our earlier Architectural-level Risk Assessment Tool (ARAT) by providing support for more architectural models and different perspective of risk assessment other than reliability- based risk. The tool accepts different type of inputs. It parses these input files and produce quantitative metrics that are used to estimate the required risk factors.

7. The input formats are from: –StarUML models (XMI Files) –Rose RealTime models (.txt Files) and –Java Understand models (.txt and.PUX static analysis files). As software architecture explicates the structure of the system in terms of components and interactions among them to accomplish the desired requirements, we have considered Class Diagrams, Sequence Diagrams, Use Case Diagrams and State Chart Diagrams. Functional Requirements (contd..)

8. Architecture

9. DEMO The demo of the SARA Tool is provided by taking Maintainability Risk with CM-1 as Case Study for StarUML format. The inputs required for this module are – XMI (XML Metadata Interchange) file of the Design from StarUML –.txt document for estimating Initial Change Probability (Optional) The Evaluations: All are Component level – Change Propagation Probability Metrics – Size of Change Probability Metrics – Initial Change Probabilities both for Corrective and Adaptive cases – Corrective Maintainability Risk and – Adaptive Maintainability Risk Creating a new Model Import file(XML) for Maintainability Risk: File imported: Case Study-1: Class Diagram of CM-1 Model: Sequence Diagrams of CM-1 Model For Size of Change: Results for SC For ICP: Two Options: 1.Import File 2.Choose Options: calculating ICP both Corrective ICP and Adaptive ICP Now Calculating Maintainability Risk: Results for Corrective MR Results for Adaptive MR:

10. Case Study:CM-1: Class Diagram from StarUML

11. Some of the Sequence Diagrams of CM-1 Model :

12. HK TIMESYNC Some of the Sequence Diagrams of CM-1 Model :

13. XMI file exported from StarUML ------The following slides takes us to the tour of the Tool demo

14. DEMO of the SARA Tool…… Creating a new Model Import file(XML) for Maintainability Risk: File imported: Case Study-1: Class Diagram of CM-1 Model: Sequence Diagrams of CM-1 Model For Size of Change: Results for SC For ICP: Two Options: 1.Import File 2.Choose Options: calculating ICP both Corrective ICP and Adaptive ICP Now Calculating Maintainability Risk: Results for Corrective MR Results for Adaptive MR:

15. Basic concepts for Assessing Maintainability Risk Change Propagation Probability metric: Change propagation probability (CP) for an architecture is the conditional probability that a change originating in one component of the architecture requires changes to be made to other components. Size of Change metric (SC): Size of Change, SC is defined as the ratio of the number of affected methods of component due to the changes in the interface of component to the number of methods Mi in the receiving component. Initial Change Probability (ICP): ICP is a scalar that reflects the potential of an architecture to insulate its components from each other’s changes. It speaks how close we are to the idealistic matrix and how far we are from the worst possible matrix.

16. StarUML StarUML - The Open Source UML/MDA Platform StarUML is an open source project to develop fast, flexible, extensible, featureful, and freely-available UML/MDA platform running on Win32 platform. The goal of the StarUML project is to build a software modeling tool and also platform that is a compelling replacement of commercial UML tools such as Rational Rose, Together and so on. Creating a new Model Import file(XML) for Maintainability Risk: File imported: Case Study-1: Class Diagram of CM-1 Model: Sequence Diagrams of CM-1 Model For Size of Change: Results for SC For ICP: Two Options: 1.Import File 2.Choose Options: calculating ICP both Corrective ICP and Adaptive ICP Now Calculating Maintainability Risk: Results for Corrective MR Results for Adaptive MR:

17. Creating a new Model

18. Import file (XML) for Maintainability Risk: File imported:

19. Creating a new Model Import file(XML) for Maintainability Risk: File imported: Case Study-1: Class Diagram of CM-1 Model: Sequence Diagrams of CM-1 Model TIMESYNC TRANSFER TRANSFER2 TRANSFER3 TRANSFER4 calculating Change Propagation Demo for Maintainability Risk Calculating Change Propagation Metrics:

20. Chart of Change Propagation Probabilities :

21. TRANSFER TRANSFER2 TRANSFER3 TRANSFER4 calculating Change Propagation For Size of Change: For Size of Change Metrics:

22. Creating a new Model Import file(XML) for Maintainability Risk: File imported: Case Study-1: Class Diagram of CM-1 Model: Sequence Diagrams of CM-1 Model HK TIMESYNC TRANSFER TRANSFER2 TRANSFER3 For ICP: Two Options: 1.Import File 2.Choose Options: calculating ICP both Corrective ICP and Adaptive ICP Corrective ICP Adaptive ICP Now Calculating Maintainability Risk: Results for Corrective MR Results for Adaptive MR: For ICP (Initial Change Probability): Two Options: 1.Import File 2.Choose Options:

23. Creating a new Model Import file(XML) for Maintainability Risk: File imported: Case Study-1: Class Diagram of CM-1 Model: Sequence Diagrams of CM-1 Model HK TIMESYNC TRANSFER TRANSFER2 TRANSFER3 For Size of Change: Results for SC For ICP: Two Options: 1.Import File 2.Choose Options: calculating ICP both Corrective ICP and Adaptive ICP Corrective ICP Adaptive ICP Now Calculating Maintainability Risk: Results for Corrective MR Results for Adaptive MR: Calculating Corrective ICP and Adaptive ICP

24. Creating a new Model Import file(XML) for Maintainability Risk: File imported: Case Study-1: Class Diagram of CM-1 Model: Sequence Diagrams of CM-1 Model HK TIMESYNC TRANSFER TRANSFER2 TRANSFER3 For Size of Change: Results for SC For ICP: Two Options: 1.Import File 2.Choose Options: calculating ICP both Corrective ICP and Adaptive ICP Corrective ICP Adaptive ICP Now Calculating Maintainability Risk: Results for Corrective MR Results for Adaptive MR: Corrective ICP

25. Results for Corrective Maintainability Risk

26. Conclusion and Future Work Software Architecture Risk Assessment (SARA) Tool is designed and implemented as a tool for computing and analyzing architectural level risk factors like Maintainability Risk, Reliability Risk and Requirement Risk. Among our venues of further research, we are considering –to support more input formats for the tool and test with multiple case studies. –to add other risk assessment perspectives like performance-based risk. –to support evaluation of Product Line Architectures (PLA). –to make it a web based open source tool.

27. Thank You