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A typical software testing is performed by making and running test cases that consist of input pattern and expected output pattern. Because exhaustive testing requires billions of test cases and many labours, we can only perform hundreds of them in practice. As for a software logic testing, selecting test cases from many candidates to achieve enough programme path coverage is important, and specific software testing skills are required for it. In our study, we propose a knowledge creation method of software logic extracted automatically from programme source code. In our method, all possible programme paths are extracted from source code, then converted into a decision table, which is easy-readable table format for software testing engineer. The logic verification can be performed exhaustively in a short time by comparing the decision table with a specification of software. Our method would contribute to improve both efficiency and quality of software testing.

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Software testing often targets natural language specification documents. Creating test cases depends on engineer skills, then automation of creating test cases from natural language specification is important. Logics retrieval is a required technique to automate creating test cases, because once logics are retrieved we can transform them into decision tables and also create test cases from the decision tables. Furthermore, Japanese language structure is different from English. If we target Japanese natural language, a new technique is also required. We propose a Semantic Analysis Technique of Logics Retrieval for Software Testing from Japanese Public Sector's Specification Documents. This technique is a new logics retrieval from harmonization between natural language processing technique and software testing. Applying the analysis technique to total 25 files, 1,218 pages and a million double bytes characters, the precision reached 0.93 to 0.97 and recall reached 0.65 to 0.79.