On Hardware Variability and the Relation to Software Variability

Brink, Christopher; Kamsties, Erik; Peters, Martin; Sachweh, Sabine

doi:10.1109/seaa.2014.15

Cited by 14 publications

(5 citation statements)

References 9 publications

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“…Hardware variability. Resarch work has been investigating the effect of hardware on software performance [4,9,11,14,27,28]. In particular, Valov et al [27,28] suggest that changing the hardware has reasonable impacts on software configurations since linear functions are highly accurate when reusing prediction models.…”

Section: Related Workmentioning

confidence: 99%

Beware of the Interactions of Variability Layers When Reasoning about Evolution of MongoDB

Lesoil

Acher

Blouin

et al. 2022

Companion of the 2022 ACM/SPEC International Conference on Performance Engineering

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With commits and releases, hundreds of tests are run on varying conditions (e.g., over different hardware and workloads) that can help to understand evolution and ensure non-regression of software performance. We hypothesize that performance is not only sensitive to evolution of software, but also to different variability layers of its execution environment, spanning the hardware, the operating system, the build, or the workload processed by the software. Leveraging the MongoDB dataset, our results show that changes in hardware and workload can drastically impact performance evolution and thus should be taken into account when reasoning about evolution. An open problem resulting from this study is how to manage the variability layers in order to efficiently test the performance evolution of a software.

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Section: Related Workmentioning

confidence: 99%

Beware of the Interactions of Variability Layers When Reasoning about Evolution of MongoDB

Lesoil

Acher

Blouin

et al. 2022

Companion of the 2022 ACM/SPEC International Conference on Performance Engineering

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“…This section discusses studies P8 [40], P220 [54], P279 [57], P332 [63], P365 [65], P468 [68], P493 [69], P580 [71], P588 [72], P589 [73], E127 [79], and E230 [90], which were assigned to the (general) variability management category. Managing the variability within a software product line constitutes a challenging task and is addressed by nearly one third of the studies from the result set.…”

Section: Variability Managementmentioning

confidence: 99%

“…Brink et al [63] propose an approach to link hardware and software variability models. Their approach distinguishes between software and hardware variants using separate variability models.…”

Section: Variability Managementmentioning

confidence: 99%

“…Summarized, variability management is addressed by the selected studies in different ways using different methods and techniques. Several studies deal with the modeling of variability (e.g., [40,54,57,63,65,68,69,79] and with the tracing of variability information across different levels of abstraction, such as requirements and design [65], hardware and software [63], or safety analysis assets and design assets [71][72][73]. Three studies focus on the combination of variability management and safety analysis and are thus also classified in category safety analysis [71][72][73] (Section 4.3.4).…”

Section: Variability Managementmentioning

confidence: 99%

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Managed Evolution of Automotive Software Product Line Architectures: A Systematic Literature Study

et al. 2022

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The rapidly growing number of software-based features in the automotive domain as well as the special requirements in this domain ask for dedicated engineering approaches, models, and processes. Nowadays, software development in the automotive sector is generally developed as product line development, in which major parts of the software are kept adaptable in order to enable reusability of the software in different vehicle variants. In addition, reuse also plays an important role in the development of new vehicle generations in order to reduce development costs. Today, a high number of methods and techniques exist to support the product line driven development of software in the automotive sector. However, these approaches generally consider only partial aspects of development. In this paper, we present an in-depth literature study based on a conceptual model of artifacts and activities for the managed evolution of automotive software product line architectures. We are interested in the coverage of the particular aspects of the conceptual model and, thus, the fields covered in current research and research gaps, respectively. Furthermore, we aim to identify the methods and techniques used to implement automotive software product lines in general, and their usage scope in particular. As a result, this in-depth review reveals that none of the studies represent a holistic approach for the managed evolution of automotive software product lines. In addition, approaches from agile software development are of growing interest in this field.

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“…(2) The real-time in such systems depends on the interactions with other tasks, which are managed by RTOS. The time spent at the system calls during the management of RTOS is directly determined by the hardware in a deployment environment [17][18]. (3) As the functions in a task have not been refined (only annotated by the worst-case execution time [19]) at the early stages of design, the design decision for a task is only the priority class [20] at this stage.…”

Section: Introductionmentioning

confidence: 99%

Time-Oriented Modeling and Analysis for Real-Time System under Variability

Xu¹

2019

IJPE

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With the advent of MDA, there is an urge to analyze the time performance in real-time systems under various design decisions at the very early stages of design. With the wide application of customized real-time operating system (RTOS) based on a microkernel, we propose a time-oriented modeling and analysis approach for real-time systems based on RTOS at the early stages of design. According to the commonality and variability in the system, a modeling approach for analyzing the time under variable design decisions is presented. These design decisions include various hardware environment, user-level services adopted in RTOS, and the task settings. In the analysis approach, a timing tree with the operating and timing rules is defined and used based on the time annotations of the basic system call of RTOS and worst-case execution time (WCET) of the functional block in a task to analyze the execution time. The modeling and analysis approach proposed is capable of analyzing new decisions without any changes in the model, which is helpful to find the best design decision to improve the real-time in the system. Finally, a real-life aircraft landing control system is taken as an example to evaluate this approach.

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On Hardware Variability and the Relation to Software Variability

Cited by 14 publications

References 9 publications

Beware of the Interactions of Variability Layers When Reasoning about Evolution of MongoDB

Beware of the Interactions of Variability Layers When Reasoning about Evolution of MongoDB

Managed Evolution of Automotive Software Product Line Architectures: A Systematic Literature Study

Time-Oriented Modeling and Analysis for Real-Time System under Variability

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