Automatic Test Generation for Space

The European Space Agency (ESA) uses an engine to perform tests in the Ground Segment infrastructure, specially the Operational Simulator. This engine uses many different tools to ensure the development of regression testing infrastructure and these tests perform black-box testing to the C++ simulator implementation. VST (VisionSpace Technologies) is one of the companies that provides these services to ESA and they need a tool to infer automatically tests from the existing C++ code, instead of writing manually scripts to perform tests. With this motivation in mind, this paper explores automatic testing approaches and tools in order to propose a system that satisfies VST needs

Automated Oracle Generation via Denotational Semantics

Software failure detection is typically done by comparing the running behaviors from a software under test (SUT) against its expected behaviors, called test oracles. In this paper, we present a formal approach to specifying test oracles in denotational semantics for systems with structured inputs. The approach introduces formal semantic evaluation rules, based on the denotational semantics methodology, defined on each productive grammar rule. We extend our grammar-based test generator, GENA, with automated test oracle generation. We provide three case studies of software testing: (i) a benchmark of Java programs on arithmetic calculations, (ii) an open source software on license identification, and (ii) selenium-based web testing. Experimental results demonstrate the effectiveness of our approach and illustrate the success of the application on the software testing

Comparison of Context-free Grammars Based on Parsing Generated Test Data

There exist a number of software engineering scenarios that essentially involve equivalence or correspondence assertions for some of the context-free grammars in the scenarios. For instance, when applying grammar transformations during parser development—be it for the sake of disambiguation or grammar-class compliance—one would like to preserve the generated language. Even though equivalence is generally undecidable for context-free grammars, we have developed an automated approach that is practically useful in revealing evidence of nonequivalence of grammars and discovering correspondence mappings for grammar nonterminals. Our approach is based on systematic test data generation and parsing. We discuss two studies that show how the approach is used in comparing grammars of open source Java parsers as well as grammars from the course work for a compiler construction class

Comparison of Context-free Grammars Based on Parsing Generated Test Data

There exist a number of software engineering scenarios that essentially involve equivalence or correspondence assertions for some of the context-free grammars in the scenarios. For instance, when applying grammar transformations during parser development---be it for the sake of disambiguation or grammar-class compliance---one would like to preserve the generated language. Even though equivalence is generally undecidable for context-free grammars, we have developed an automated approach that is practically useful in revealing evidence of nonequivalence of grammars and discovering correspondence mappings for grammar nonterminals. The approach is based on systematic test data generation and parsing. We discuss two studies that show how the approach is used in comparing grammars of open source Java parsers as well as grammars from the course work for a compiler construction class