Auto-coding UML statecharts for flight software

Statecharts have been used as a means to communicate behaviors in a precise manner between system engineers and software engineers. Handtranslating a statechart to code, as done on some previous space missions, introduces the possibility of errors in the transformation from chart to code. To improve auto-coding, we have developed a process that generates flight code from UML statecharts. Our process is being used for the flight software on the Space Interferometer Mission (SIM)

Model Based Analysis and Test Generation for Flight Software

We describe a framework for model-based analysis and test case generation in the context of a heterogeneous model-based development paradigm that uses and combines Math- Works and UML 2.0 models and the associated code generation tools. This paradigm poses novel challenges to analysis and test case generation that, to the best of our knowledge, have not been addressed before. The framework is based on a common intermediate representation for different modeling formalisms and leverages and extends model checking and symbolic execution tools for model analysis and test case generation, respectively. We discuss the application of our framework to software models for a NASA flight mission

Semantic mutation testing

This is the Pre-print version of the Article. The official published version can be obtained from the link below - Copyright @ 2011 ElsevierMutation testing is a powerful and flexible test technique. Traditional mutation testing makes a small change to the syntax of a description (usually a program) in order to create a mutant. A test suite is considered to be good if it distinguishes between the original description and all of the (functionally non-equivalent) mutants. These mutants can be seen as representing potential small slips and thus mutation testing aims to produce a test suite that is good at finding such slips. It has also been argued that a test suite that finds such small changes is likely to find larger changes. This paper describes a new approach to mutation testing, called semantic mutation testing. Rather than mutate the description, semantic mutation testing mutates the semantics of the language in which the description is written. The mutations of the semantics of the language represent possible misunderstandings of the description language and thus capture a different class of faults. Since the likely misunderstandings are highly context dependent, this context should be used to determine which semantic mutants should be produced. The approach is illustrated through examples with statecharts and C code. The paper also describes a semantic mutation testing tool for C and the results of experiments that investigated the nature of some semantic mutation operators for C

Generating Test Sequences and Slices for Simulink/Stateflow Models

In a typical software development project more than 50 percent of software development effort is spent in testing phase. Test case design as well as execution consumes a lot of time. So automated generation of test cases is highly required. In our thesis we generated test sequences from Simulink/Stateflow, which is used to develop Embedded control systems. Testing of these systems is very important in order to provide error free systems as well as quality assurance. For these purpose Test cases are used to test the systems. We developed the test sequences which are use to generate test cases. First, we represent the System using Simulink/Stateflow models. For this purpose normally we use Simulink tool, which is available in the MATLAB. We developed the dependency graph from the SL/SF model. For Simulink part of the model we use Out put dependency and for the Stateflow part of the model we use Control dependency graph. From those graphs we generate the test sequences. Simulink/Stateflow models often consist of more than ten thousand blocks and a large number of hierarchi-cal levels. In this, we present an approach for slicing Simulink/Stateflow models using dependence graphs from the automotive and avionics do-main. With slicing, the complexity of a model can be reduced to a given point of interest by removing unrelated model elements

Search based algorithms for test sequence generation in functional testing

Information and Software Technology (DOI: 10.1016/j.infsof.2014.07.014)The generation of dynamic test sequences from a formal specification, complementing traditional testing methods in order to find errors in the source code. Objective In this paper we extend one specific combinatorial test approach, the Classification Tree Method (CTM), with transition information to generate test sequences. Although we use CTM, this extension is also possible for any combinatorial testing method. Method The generation of minimal test sequences that fulfill the demanded coverage criteria is an NP-hard problem. Therefore, search-based approaches are required to find such (near) optimal test sequences. Results The experimental analysis compares the search-based technique with a greedy algorithm on a set of 12 hierarchical concurrent models of programs extracted from the literature. Our proposed search-based approaches (GTSG and ACOts) are able to generate test sequences by finding the shortest valid path to achieve full class (state) and transition coverage. Conclusion The extended classification tree is useful for generating of test sequences. Moreover, the experimental analysis reveals that our search-based approaches are better than the greedy deterministic approach, especially in the most complex instances. All presented algorithms are actually integrated into a professional tool for functional testing.Spanish Ministry of Economy and Competitiveness and FEDER under contract TIN2011-28194 and fellowship BES-2012-055967. Project 8.06/5.47.4142 in collaboration with the VSB-Tech. Univ. of Ostrava, Universidad de Málaga, Andalucía Tech. and EU Grant ICT-257574 (FITTEST project)