Software testing techniques (2nd ed.)
Software testing techniques (2nd ed.)
Software Engineering Economics
Software Engineering Economics
Software Cost Estimation with Cocomo II with Cdrom
Software Cost Estimation with Cocomo II with Cdrom
A Practitioner's Guide to Software Test Design
A Practitioner's Guide to Software Test Design
The Art of Software Testing
DART: directed automated random testing
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
CUTE: a concolic unit testing engine for C
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
EXE: automatically generating inputs of death
Proceedings of the 13th ACM conference on Computer and communications security
Heuristics for Scalable Dynamic Test Generation
ASE '08 Proceedings of the 2008 23rd IEEE/ACM International Conference on Automated Software Engineering
A generic measurement model for system data definition and database requirements
International Journal of Computer Applications in Technology
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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.