Selecting Software Test Data Using Data Flow Information
IEEE Transactions on Software Engineering
Interprocedural slicing using dependence graphs
ACM Transactions on Programming Languages and Systems (TOPLAS)
An overview and comparative classification of program slicing techniques
Journal of Systems and Software
Software unit test coverage and adequacy
ACM Computing Surveys (CSUR)
The program dependence graph in a software development environment
SDE 1 Proceedings of the first ACM SIGSOFT/SIGPLAN software engineering symposium on Practical software development environments
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Generating effective test data to show that a faulty structure could produce a failure poses many complexity problems. Code reviews are known as an effective method for detecting potential critical program structures. But detecting this structures in a code review takes a lot of effort and is error prone.This paper presents a method to detect potential faulty structures by program modeling. Therefore we build a database containing informations about classified faults. For analyzing the program we generate a first order predicate logic model implemented in horn clauses. We show how to detect the fault structures defined in the database and how to reduce the effort for the code review by slicing the relevant parts of the program.