Automatic Evaluation of ECU Software Tests

Conrad, Mirko; Sadeghipour, Sadegh; Wiesbrock, Hans-Werner

doi:10.4271/2005-01-1659

Cited by 9 publications

(7 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…a given comparison algorithm is less or equal a given threshold. The selection of the comparison algorithm and the definition of the threshold value depend on the application under consideration or even on the characteristics of a given output signal (comparing boolean outputs, for example, may require different algorithms and thresholds than comparing floating point outputs with potentially denormalized values) and need to be documented; see [10] for an overview of algorithms to consider. IEC 61508-3 does not provide specific guidance here.…”

Section: Signal Comparison After Test Execution the Results Vectors (mentioning

confidence: 99%

“…There is a broad variety of potential comparison algorithms ranging from elementary algorithms like absolute or relative differencing to more elaborated ones such as the difference matrix method [10].…”

Section: Signal Comparison After Test Execution the Results Vectors (mentioning

confidence: 99%

“…Technically speaking, the algorithm calculates a reparameterization (temporal reordering) of o CODE (t) such that o CODE (t) matches o SIM (t) as well as possible. After using difference matrix preprocessing to better match the time axes of the two signals, elementary algorithms such as absolute or relative differencing can be used to assess the remaining deviations on the value axis [10].…”

Section: Signal Comparison After Test Execution the Results Vectors (mentioning

confidence: 99%

See 2 more Smart Citations

Testing-based translation validation of generated code in the context of IEC 61508

Conrad

2009

Form Methods Syst Des

Self Cite

View full text Add to dashboard Cite

Production code generation with Model-Based Design has successfully replaced manual coding across various industries and application domains. Furthermore, code generated from executable graphical models is increasingly being deployed in high-integrity embedded applications.To validate the model-to-code translation process, generated software components and its precursory stages (i.e. models) should be subjected to an appropriate combination of quality assurance measures. For high-integrity applications, compliance with safety standards such as IEC 61508 needs to be demonstrated as well.On principle, translation validation of generated code could be carried out in the same manner as for manually written code. However, this would not leverage the advantages of Model-Based Design and w.r.t. process efficiency this would leave something to be desired. Therefore, engineering methods and tools for effective and efficient translation validation of generated code are highly desirable. As a step towards this goal, a workflow for verification and validation of models and generated code will be proposed and as far as possible mapped onto the objectives of IEC 61508-3. A cornerstone of this workflow is testing for numerical equivalence between models and generated code.

show abstract

Section: Signal Comparison After Test Execution the Results Vectors (mentioning

confidence: 99%

Section: Signal Comparison After Test Execution the Results Vectors (mentioning

confidence: 99%

Section: Signal Comparison After Test Execution the Results Vectors (mentioning

confidence: 99%

See 1 more Smart Citation

Testing-based translation validation of generated code in the context of IEC 61508

Conrad

2009

Form Methods Syst Des

Self Cite

View full text Add to dashboard Cite

show abstract

“…Conrad, for example, exploited a testing‐based approach to gauging the functional equivalence of the model and the resulting code. In a previous work, Conrad et al [42] emphasized test case generation in the context of back‐to‐back testing of electronic control unit (ECU) software. This type of test emphasizes the equivalence between the test object (i.e.…”

Section: Analysis Based On the Research Questionsmentioning

confidence: 99%

On transforming model‐based tests into code: A systematic literature review

Ferrari,

Durelli,

Andler

et al. 2023

Software Testing Verif & Rel

View full text Add to dashboard Cite

SummaryModel‐based test design is increasingly being applied in practice and studied in research. Model‐based testing (MBT) exploits abstract models of the software behaviour to generate abstract tests, which are then transformed into concrete tests ready to run on the code. Given that abstract tests are designed to cover models but are run on code (after transformation), the effectiveness of MBT is dependent on whether model coverage also ensures coverage of key functional code. In this article, we investigate how MBT approaches generate tests from model specifications and how the coverage of tests designed strictly based on the model translates to code coverage. We used snowballing to conduct a systematic literature review. We started with three primary studies, which we refer to as the initial seeds. At the end of our search iterations, we analysed 30 studies that helped answer our research questions. More specifically, this article characterizes how test sets generated at the model level are mapped and applied to the source code level, discusses how tests are generated from the model specifications, analyses how the test coverage of models relates to the test coverage of the code when the same test set is executed and identifies the technologies and software development tasks that are on focus in the selected studies. Finally, we identify common characteristics and limitations that impact the research and practice of MBT: (i) some studies did not fully describe how tools transform abstract tests into concrete tests, (ii) some studies overlooked the computational cost of model‐based approaches and (iii) some studies found evidence that bears out a robust correlation between decision coverage at the model level and branch coverage at the code level. We also noted that most primary studies omitted essential details about the experiments.

show abstract

“…All model test sequences can be reused for testing the control software generated from the model and the control unit within the framework of back-to-back tests. In this way, the functional equivalence between the executable model and derived forms of representation can be verified ([BCS03], [CSW04]).…”

Section: Model-based Test Strategymentioning

confidence: 99%

Evolutionary Safety Testing of Embedded Control Software by Automatically Generating Compact Test Data Sequences

Pohlheim

Conrad

Griep

2005

SAE Technical Paper Series

Self Cite

View full text Add to dashboard Cite

Whereas the verification of non-safety-related, embedded software typically focuses on demonstrating that the implementation fulfills its functional requirements, this is not sufficient for safety-relevant systems. In this case, the control software must also meet application-specific safety requirements.Safety requirements typically arise from the application of hazard and/or safety analysis techniques, e.g. FMEA, FTA or SHARD. During the downstream development process it must be shown that these requirements cannot be violated. This can be achieved utilizing different techniques. One way of providing evidence that violations of the safety properties identified cannot occur is to thoroughly test each of the safety requirements. This paper introduces Evolutionary Safety Testing (EST), a fully automated procedure for the safety testing of embedded control software. EST employs extended evolutionary algorithms in an optimization process which aggressively tries to find test data sequences that cause the test object to violate a given safety requirement.A compact description formalism for input sequences for safety testing is presented, which is compatible with description techniques used during other test process stages. This compact description allows 1) an efficient application of evolutionary algorithms (and other optimization techniques) and 2) the description of long test sequences necessary for the adequate stimulation of real-world systems. The objective function is designed in such a way that optimal values represent test data sequences which violate a given safety requirement. By means of repeated input sequence generation, software execution and the subsequent evaluation of the objective function each safety requirement is extensively tested.The use of EST for the safety testing of automotive control software is demonstrated using safety requirements of an adaptive cruise control (ACC) system.The EST approach can easily be integrated into an overall software test strategy which combines different test design techniques with specific test objectives.

show abstract

Automatic Evaluation of ECU Software Tests

Cited by 9 publications

References 7 publications

Testing-based translation validation of generated code in the context of IEC 61508

Testing-based translation validation of generated code in the context of IEC 61508

On transforming model‐based tests into code: A systematic literature review

Evolutionary Safety Testing of Embedded Control Software by Automatically Generating Compact Test Data Sequences

Contact Info

Product

Resources

About