Most of the important aspects of the design process can be effectively supported if such expertise can be identified, acquired, and reused. This paper presents a design environment that supports this knowledge-based approach to software design. The design approach may be viewed as knowledge-driven refinement of abstract/specific design models. The design environment consists of a design subsystem, an acquisition and refinement subsystem, and a retrieval mechanism for the retrieval of abstract/specific design models. This paper also describes the interactive aspects required in such an environment. The design representation used in the environment consists of leveled dataflow diagrams and entity-relationship based data models supporting structured analysis and dataflow-oriented software design.>

SPECIFIER, an interactive system which derives formal specifications of data types and programs from their informal descriptions, is described. The process of deriving formal specifications is viewed as a problem-solving process. The system uses common problem-solving techniques such as schemas, analogy, and difference-based reasoning to derive formal specifications. If an informal description is a commonly occurring operation for which the system has a schema, then the formal specification is derived by instantiating the schema. If there is a no such schema, SPECIFIER tries to find a previously solved problem which is analogous to the current problem. If the problem found is directly analogous to the current problem, it applies an analogy mapping to obtain a formal specification. On the other hand, if the analogy found is only approximate, it solves the directly analogous part of the problem by analogy and performs difference-based reasoning using the remaining (unmatched) parts to transform the formal specification obtained by analogy to a formal specification for the entire original problem.>

No abstract available.

Summary form only given. The author examines the problems of traditional software development paradigms, identifying areas that can be helped by knowledge-based techniques. He discusses fundamental software issues that relate to knowledge-based approaches to software development. Based on these discussions, a framework for knowledge-based software development paradigms and tools is provided.>

Summary form only given. Considers the kinds of software-engineering problems that can be solved by expert systems, as well as how to acquire and represent software knowledge. Other questions addressed are: (1) can expert systems development benefit from the experience in software engineering; (2) is a special design methodology required for expert systems developed; and (3) how to apply current software engineering techniques to facilitate the development of expert systems.>

The authors address the use of knowledge-based techniques in providing high-level support for program understanding and debugging activities. An intelligent program analysis/debugging tool, called PAT, is described which is expected to provide human-expert-level assistance to programmers in general program understanding and debugging tasks. PAT is characterized by its use of a knowledge base of coding and debugging heuristics represented as program plans. With the help of the encoded expert knowledge, this tool comprehends a given program without a separate specification from the programmer or an execution of the program. PAT then generates paraphrases about the intentions implied in the given code and diagnoses bugs that are commonly related to those intentions.>

The problems of traditional software-development paradigms are examined, identifying areas which can be helped by knowledge-based techniques. A discussion on fundamental software issues which relate to knowledge-based approaches to software development is presented. Based on this discussion, a framework for knowledge-based software development paradigms and tools, and a development environment to support the paradigm are provided.>

This paper describes the rule base management strategy of an expert system environment. The environment includes a set of integrated tools which facilitate acquisition, manipulation and maintenance of knowledge. The rule base management component of the system, called RBM, assists these tasks by organizing global semantic information within the rule base. RBM extracts this semantic information from the texts included in “rule structures” and builds a semantic network of the concepts found in the rule base. The rule base is then divided into rulesets which are clusters of rules that refer to the same atomic concept. Construction of this meta knowledge is achieved through a keyword matching mechanism. The paper includes a brief description of the RBM system, the dictionary it uses for building meta-level knowledge, and its keyword matching technique.

The advent of the next version of ANSI COBOL focusses attention again on the portability of COBOL. The present ANSI standard allows more then 100,000 permissible implementations. This paper argues that COBOL needs a more rigorously defined implementation scheme which specifically allows for portability, taking cognisance of the user's operating environment and allowing many fewer implementation variants. The need for a more rational subsetting policy is also argued and how this complements the implementation scheme proposed to provide better portability is shown.