We demonstrate the generation of an engine test model using Genetic Programming. In particular, a two-phase modeling process is proposed to handle the high-dimensionality and sparseness natures of the engine test data. The resulting model gives high accuracy prediction on training data. It is also very good in predicting low range data values. However, at least partly due to limitations of the ...

This paper describes the input specification language of the WAG Sentence Generation system. The input is described in terms of Halliday’s (1978) three meaning components, ideational meaning (the propositional content to be expressed), interactional meaning (what the speaker intends the listener to do in making the utterance), and textual meaning (how the content is structured as a message, in ...

In this paper we are giving an overview of automatic test data generation. The basic objective of this paper is to acquire the basic concepts related to automated test data generation research. The different implementation techniques are described with their relative merits and demerits. The future challenges and problems of test data generation are explained. Finally we describe the area where...

This paper reports on an industrial study of the effectiveness of test data generation. In the literature on the automatic generation of test data a number of techniques stand out as having received a significant amount of interest. One area that has achieved considerable attention is the use of combinatorial techniques to construct data adequate test sets that ensure all pairs, triples etc. of...

The paper presents the Meaning-Text linguistic theory, a theoretical framework for the construction of models of natural languages, called Meaning-Text Models. Since its beginnings, in the 1960’s, the Meaning-Text theory has placed strong emphasis on semantics and considered natural language primarily as a tool for expressing meaning. This basic insight underlies its interest in linguistic synt...

This paper explores the importance of semantic integrity during data warehouse design and its impact on the successful use of the implemented warehouse. This was achieved through a detailed case study. Consequently, a conceptual framework for describing intersubjective meaning in data modelling has been developed. The purpose of the framework is to provide a theoretical basis for explaining how...

This paper summarizes eight types of error terminology in the patent text output Machine Translation from English into Chinese, including term being mistranslated as a verb, common noun, redundantly translated, homophone, wrong term, due to Chinese expression, without initial, and acronym. These errors can be solved by translator before identify correct these pre-editing source text.