A Maple Toolchain for Rigid Body Dynamics of Serial, Hybrid and Parallel Robots

A new Maple toolchain for generating rigid body dynamics in symbolic form for robot manipulators is presented. The peculiarity compared to existing tools lies in the framework of Bash scripts controlling the full workflow of the toolchain with a high degree of automation. The optimized Matlab code generated by Maple is automatically converted to function files with proper documentation and input assertions. This renders manual post-processing of the results unnecessarily. The focus of the paper is on the implemented unit-testing framework according to the method of test-driven development. By providing the test framework together with the generated code in a stand-alone version, a good test coverage and a good software quality can be achieved. The results of the open source project provide a basis for dynamics simulations for robot dimensional synthesis or in model-based control of robot manipulators in research or in industrial context. The general software approach can be applied to other fields where theoretical models are derived with Maple

CTGEN - a Unit Test Generator for C

We present a new unit test generator for C code, CTGEN. It generates test data for C1 structural coverage and functional coverage based on pre-/post-condition specifications or internal assertions. The generator supports automated stub generation, and data to be returned by the stub to the unit under test (UUT) may be specified by means of constraints. The typical application field for CTGEN is embedded systems testing; therefore the tool can cope with the typical aliasing problems present in low-level C, including pointer arithmetics, structures and unions. CTGEN creates complete test procedures which are ready to be compiled and run against the UUT. In this paper we describe the main features of CTGEN, their technical realisation, and we elaborate on its performance in comparison to a list of competing test generation tools. Since 2011, CTGEN is used in industrial scale test campaigns for embedded systems code in the automotive domain.Comment: In Proceedings SSV 2012, arXiv:1211.587

Incremental bounded model checking for embedded software

Program analysis is on the brink of mainstream usage in embedded systems development. Formal verification of behavioural requirements, finding runtime errors and test case generation are some of the most common applications of automated verification tools based on bounded model checking (BMC). Existing industrial tools for embedded software use an off-the-shelf bounded model checker and apply it iteratively to verify the program with an increasing number of unwindings. This approach unnecessarily wastes time repeating work that has already been done and fails to exploit the power of incremental SAT solving. This article reports on the extension of the software model checker CBMC to support incremental BMC and its successful integration with the industrial embedded software verification tool BTC EMBEDDED TESTER. We present an extensive evaluation over large industrial embedded programs, mainly from the automotive industry. We show that incremental BMC cuts runtimes by one order of magnitude in comparison to the standard non-incremental approach, enabling the application of formal verification to large and complex embedded software. We furthermore report promising results on analysing programs with arbitrary loop structure using incremental BMC, demonstrating its applicability and potential to verify general software beyond the embedded domain

Semantics-based Automated Web Testing

We present TAO, a software testing tool performing automated test and oracle generation based on a semantic approach. TAO entangles grammar-based test generation with automated semantics evaluation using a denotational semantics framework. We show how TAO can be incorporated with the Selenium automation tool for automated web testing, and how TAO can be further extended to support automated delta debugging, where a failing web test script can be systematically reduced based on grammar-directed strategies. A real-life parking website is adopted throughout the paper to demonstrate the effectivity of our semantics-based web testing approach.Comment: In Proceedings WWV 2015, arXiv:1508.0338

SmartUnit: Empirical Evaluations for Automated Unit Testing of Embedded Software in Industry

In this paper, we aim at the automated unit coverage-based testing for embedded software. To achieve the goal, by analyzing the industrial requirements and our previous work on automated unit testing tool CAUT, we rebuild a new tool, SmartUnit, to solve the engineering requirements that take place in our partner companies. SmartUnit is a dynamic symbolic execution implementation, which supports statement, branch, boundary value and MC/DC coverage. SmartUnit has been used to test more than one million lines of code in real projects. For confidentiality motives, we select three in-house real projects for the empirical evaluations. We also carry out our evaluations on two open source database projects, SQLite and PostgreSQL, to test the scalability of our tool since the scale of the embedded software project is mostly not large, 5K-50K lines of code on average. From our experimental results, in general, more than 90% of functions in commercial embedded software achieve 100% statement, branch, MC/DC coverage, more than 80% of functions in SQLite achieve 100% MC/DC coverage, and more than 60% of functions in PostgreSQL achieve 100% MC/DC coverage. Moreover, SmartUnit is able to find the runtime exceptions at the unit testing level. We also have reported exceptions like array index out of bounds and divided-by-zero in SQLite. Furthermore, we analyze the reasons of low coverage in automated unit testing in our setting and give a survey on the situation of manual unit testing with respect to automated unit testing in industry.Comment: In Proceedings of 40th International Conference on Software Engineering: Software Engineering in Practice Track, Gothenburg, Sweden, May 27-June 3, 2018 (ICSE-SEIP '18), 10 page