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 6 th ISSAT Conference on Reliability and Quality in Design August 2000

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

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

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

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

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

West Virginia University The UML Model

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

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

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

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

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

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

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.

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).

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

West Virginia University Questions...