Improving the State of Automotive Software Engineering

Haghighatkhah, Alireza; Oivo, Markku; Banijamali, Ahmad; Kuvaja, Pasi

doi:10.1109/ms.2017.3571571

Cited by 14 publications

(5 citation statements)

References 18 publications

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“…Based on that work, they argue that the automotive industry "should adopt modelbased RE." [22]. However, they back this argument using opinion papers only.…”

Section: Modelling In the Embedded Domain And During Rementioning

confidence: 98%

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Use, potential, and showstoppers of models in automotive requirements engineering

2018

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Several studies report that the use of model-centric methods in the automotive domain is widespread and offers several benefits. However, existing work indicates that few modelling frameworks explicitly include requirements engineering (RE), and that natural language descriptions are still the status quo in RE. Therefore, we aim to increase the understanding of current and potential future use of models in RE, with respect to the automotive domain. In this paper, we report our findings from a multiple-case study with two automotive companies, collecting interview data from 14 practitioners. Our results show that models are used for a variety of different purposes during RE in the automotive domain, e.g. to improve communication and to handle complexity. However, these models are often used in an unsystematic fashion and restricted to few experts. A more widespread use of models is prevented by various challenges, most of which align with existing work on model use in a general sense. Furthermore, our results indicate that there are many potential benefits associated with future use of models during RE. Interestingly, existing research does not align well with several of the proposed use cases, e.g. restricting the use of models to informal notations for communication purposes. Based on our findings, we recommend a stronger focus on informal modelling and on using models for multidisciplinary environments. Additionally, we see the need for future work in the area of model use, i.e. information extraction from models by non-expert modellers.

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“…Based on that work, they argue that the automotive industry "should adopt modelbased RE." [22]. However, they back this argument using opinion papers only.…”

Section: Modelling In the Embedded Domain And During Rementioning

confidence: 98%

“…Recently, Haghighatkhah et al [22] reviewed the literature on automotive SE. The authors find 33 papers covering RE in the automotive domain.…”

Section: Modelling In the Embedded Domain And During Rementioning

confidence: 99%

Use, potential, and showstoppers of models in automotive requirements engineering

2018

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“…Several practices exist for the development of reference architectures (i.e., [127,128]) that can be adopted and applied in CoT domain. Future academic studies can emphasise collaborations with industrial partners and be driven by the specific needs of stakeholders in different contexts to establish reliable, scalable, and secure architectures in the context of CoT, as previous researchers [129,130] have already realised this need in the automotive domain.…”

Section: Recommendations For Future Studymentioning

confidence: 99%

Software architectures of the convergence of cloud computing and the Internet of Things: A systematic literature review

Banijamali

Pakanen

Kuvaja

et al. 2020

Information and Software Technology

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“…SBTP can be applied in different contexts and during initial testing where no information about the system under test is available (e.g., code coverage or historical data). SBTP is an especially interesting approach when code instrumentation is too costly or impossible (e.g., in automotive system testing where source-code is not always available [10,8]). SBPT can also be applied in a complementary fashion and combined with other TCP techniques (e.g., historybased diversity proposed in our previous work [9]).…”

Section: Overview Of Findings Their Implications and Future Workmentioning

confidence: 99%

Test Case Prioritization Using Test Similarities

Haghighatkhah

Mäntylä

Oivo

et al. 2018

Product-Focused Software Process Improvement

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A classical heuristic in software testing is to reward diversity, which implies that a higher priority must be assigned to test cases that differ the most from those already prioritized. This approach is commonly known as similarity-based test prioritization (SBTP) and can be realized using a variety of techniques. The objective of our study is to investigate whether SBTP is more effective at finding defects than random permutation, as well as determine which SBTP implementations lead to better results. To achieve our objective, we implemented five different techniques from the literature and conducted an experiment using the defects4j dataset, which contains 395 real faults from six real-world open-source Java programs. Findings indicate that running the most dissimilar test cases early in the process is largely more effective than random permutation (Vargha-Delaney A [VDA]: 0.76-0.99 observed using normalized compression distance). No technique was found to be superior with respect to the effectiveness. Locality-sensitive hashing was, to a small extent, less effective than other SBTP techniques (VDA: 0.38 observed in comparison to normalized compression distance), but its speed largely outperformed the other techniques (i.e., it was approximately 5-111 times faster). Our results bring to mind the well-known adage, "don't put all your eggs in one basket". To effectively consume a limited testing budget, one should spread it evenly across different parts of the system by running the most dissimilar test cases early in the testing process.

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Improving the State of Automotive Software Engineering

Cited by 14 publications

References 18 publications

Use, potential, and showstoppers of models in automotive requirements engineering

Use, potential, and showstoppers of models in automotive requirements engineering

Software architectures of the convergence of cloud computing and the Internet of Things: A systematic literature review

Test Case Prioritization Using Test Similarities

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