1. West Virginia University Sherif Yacoub, Hany H. Ammar, and Ali Mili A UML Model for Analyzing Software Quality Sherif Yacoub, Hany H. Ammar, and Ali Mili Computer Sc. and Electrical Engineering Department West Virginia University yacoub@csee.wvu.edu, hammar@wvu.edu,amili@csee.wvu.edu 6 th ISSAT Conference on Reliability and Quality in Design August 2000

2. West Virginia University Outlines  Introduction  Objective and Approach  The UML Model of Software Quality  External Quality Attributes  Quantitative factors  Computable metrics  Conclusions  Current and Future Work  Questions

3. West Virginia University Introduction  In building a model for a successful software measurement process, one has to address the following concerns: a) Distinguish between what we can measure and what we want to measure b) Conduct theoretical or empirical evaluation c) Defining the artifacts to be measured  In a model for software product quality, Dromey (TSE’95) distinguishes between (internal) product characteristics and (externally observable) quality attributes  Morasca and Briand in their theoretical framework for measuring software attributes (metrics’97), distinguish between characterizing (internal) software qualities and predicting (external) attributes

4. West Virginia University Introduction  Fenton and Neil [Journal of Systems and Software, July 1999]  The credibility of metrics as a whole has been lowered because of the crude way in which these metrics have been used.  We need models that can handle the following range of features: diverse processes and products; genuine cause and effect relationships

5. West Virginia University Objective  Develop formal understanding of the relationships between quality attributes, computable metrics, and quality factors Approach  Develop an Object-Oriented model using UML Define the objects in the software quality measurement model Define the relationships between these objects

6. West Virginia University Product Artifacts Architecture, Design, Code, External Attributes: Maintainability,Testa bility, Reliabiblity, Computable Metrics: Coupling, cohesion, complexity, etc. Error Propagation, ChangePropagation, Requirements Propagation impacts computed for Analytical Definitions Mathematic al Formula have Historical Data MeasurementValues produce Validation Analytical Derivations Quantified The UML Model McCall's model of software quality [McCall 1977], Three-level hierarchy of software attributes

7. West Virginia University The UML Model

8. West Virginia University External Quality Attributes  Maintainability Corrective Maintenance, Adaptive Maintenance, Preventive Maintenance, and Perfective Maintenance  Directly related to change propagation and requirements propagation

9. West Virginia University External Quality Attributes  Reusability Genericity of a component, usage dependency, and requirements propagation between components Price and Demurjian [October 97], assumes that a set of related components in an architecture is more reusable if it has less dependencies to other parts of the system

10. West Virginia University External Quality Attributes  Reilability The probability of occurrence of a fault, the probability of executing that fault to produce an error, and the probability that the error causes a failure  Directly related to error propagation as a quantitative factor

11. West Virginia University Defining Quantitative Factors  Focus on quantitative factors for software architectures  Error Propagation The error propagation from component A to component B in system S, EP(A;B), is the mean of probability EPP (x; x') = P (B(x)  B(x')| x  x'), for all information x and x' in the channel X connecting A and B, Error propagation from A to B reflects the likelihood that an error in unit A causes an error in unit B, given that A feeds information to B

12. West Virginia University Defining Quantitative Factors  Change Propagation The change propagation from A to B in S is the mean of probability CPP (A'; B') = P(B  B' | A  A' ^ S = S' ), for all units A' and B' Change propagation from A to B reflects the likelihood that a change in unit A requires a change in unit B in order to preserve the overall function of system S

13. West Virginia University Defining Quantitative Factors  Requirements Propagation The requirements propagation from A to B in S is the mean of probability RPP(A' ; B' ; S' ) = P(B'  B | A'  A ^ S'  S); where S' is obtained from S by replacing A and B by (respectively) A' and B', for all values of A', B' and S' reflects the likelihood that a change of A to accommodate the new system requirement S' requires a change of B as well

14. West Virginia University Defining Computable Metrics  Computable metrics are those that we can measure from a product artifact given well-defined mathematical formulae  Coupling, cohesion, and complexity are some of the most well-known and well defined computable metrics at the architecture level  coupling and cohesion can be used to assess the likelihood of error propagation, change propagation, and requirements propagation from one module to its neighbors.

15. West Virginia University Conclusions  We proposed a UML model for software quality measurement  The model helps us to distinguish what we want to measure (external attributes) and what we are able to measure (internal attributes),  Distinguish which product artifacts that we use in the measurement process  Distinguish between theoretical and empirical approaches to correlate computable metrics (such as coupling and cohesion) with quantifiable factors (such as error propagation and change propagation).

16. West Virginia University Future Work  Establishing the analytical relationship between the Quantitative Factors and the Computable Metrics  Empirical Validation of the Proposed Metrics  Automate the computation of metrics from a formal description of the architecture

17. West Virginia University Questions...