Knowledge-Based Automation of a Design Method for Concurrent Systems
Kevin L. Mills, H Gomaa
This paper describes a knowledge-based approach to automate a software design method for concurrent and real-time systems. The approach uses multiple paradigms to represent knowledge embedded within the design method. Semantic data modeling provides the means to represent concepts from a behavioral modeling technique, called Concurrent Object-Based Real-time Analysis (COBRA), which defines system behavior using data flow/control flow diagrams. Entity-Relationship modeling is used to represent a design meta-model based on a design method, called Concurrent Design Approach for Real-Time Systems (CODARTS), which represents concurrent designs as software architecture diagrams, task behavior specifications, and module specifications. Production rules provide the mechanism for codifying a set of CODARTS heuristics that can generate concurrent designs based on semantic concepts included in COBRA behavioral models and on entities and relationships included in CODARTS design meta-models. Other forms of automated reasoning, such as knowledge-based queries, can be used to check the correctness and completeness of generated designs with respect to properties defined in the CODARTS design meta-model. Together, the semantic data model, the entity-relationship model, the production rules, and the knowledge-based queries, when encoded using an expert-system shell, compose CODA, an automated designer s assistant. CODA is applied to generate ten concurrent designs for four real-time problems. The paper reports the degree of automation achieved by CODA. The paper also evaluates the quality of generated designs by comparing the similarity between designs produced by CODA and human designs reported in the literature for the same problems. The paper also compares CODA with four other approaches used to automate software design methods.
and Gomaa, H.
Knowledge-Based Automation of a Design Method for Concurrent Systems, IEEE Transactions on Software Engineering, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=151047
(Accessed June 8, 2023)