In order to facilitate deterministic behavior; industrial real-time communication stacks need another design than non-real-time communication stacks typically found in e.g., Internet of Things and Cloud solutions. We propose a flexible stack design that enable code reuse between testbeds and simulators, as well as how stack layers are driven and prioritized. The design can be generalized and used for non-real-time bare-metal solutions like battery powered Internet of Things. Our approach aims at extending the use of simulation during development of industrial systems in order to find logical errors and wrong assumptions earlier in the development. Conducted and evaluated experiments show that the proposed solutions are able to extend the use of simulation during development of real-time communication software. This is achieved by reusing the same code on an industrial testbed and in a discrete event simulator. In addition, the experiments show that the stack design is generalizable and enable reuse with other non-real-time embedded systems. The contribution consists of a set of building blocks for real-time systems that enable control over the system timing when executing on a simulation host while reusing the source code from an industrial testbed. Overall, this will improve the engineering situation, with respect to code reuse, flexibility and debugging. © 2023 The Author(s)

Embedded systems are today often self-sufficient systems with limited communication. However, this traditional view of an embedded system is changing rapidly. Embedded systems are nowadays evolving, e.g., an evolution pushed by the increased functional gain introduced with the concept of System of Systems (SoS) that is connecting multiple subsystems to achieve a combined functionality and/or information of a higher value. In such a SoS the subsystems will have to serve a dual purpose in a) the initial purpose that the subsystem was originally designed and deployed for, e.g., control and protection of the physical assets of a critical infrastructure system that could be up and running for 30-40 years, and b) at the same time provide information to a higher-level system for a potential future increase of system functionality as technology matures and/or new opportunities are provided by, e.g., greater analytics capabilities. In this paper, within the context of a “dual purpose use” of a) and b), we bring up three central challenges related to i) information gathering, ii) life-cycle management, and iii) data governance, and we propose directions for solutions to these challenges that need to be evaluated already at design time.

Embedded systems are today often self-sufficient with limited and predefined communication. However, this traditional view of embedded systems is changing through advancements in technologies such as, communication, cloud technologies, and advanced analytics including machine learning. These advancements have increased the benefits of building Systems of Systems (SoS) that can provide a functionality with unique capabilities that none of the included subsystems can accomplish separately. By this gain of functionality the embedded system is evolving towards a “dual use” purpose¹¹In this paper we define dual usage as a control system having two purposes. In other contexts such as politics, diplomacy and export control, the term “dual-use” refers to technology that can be used for both peaceful and military aims, e.g., nuclear power technology., The use is dual in the sense that the system still needs to handle its original task, e.g., control and protect of an asset, and it must provide information for creating the SoS. Larger installations, e.g., industry plants, power systems and generation, have in most cases a long expected life-cycle, some up to 30–40 years without significant updates, compared to analytical functions that evolve and change much faster, i.e., requiring new types of data sets from the subsystems, not know at its first deployment. This difference in development cycles calls for new solutions supporting updates related to new requirements inherent in analytical functions. In this paper, within the context of “dual usage” of systems and subsystems, we analyze the impact on an embedded system, new or legacy, when it is required to provide analytic data with high quality. We compare a reference system, implementing all functions in one CPU core, to three other alternative solutions: a) a multi-core system where we are using a separate core for analytics, b) using a separate analytics CPU and c) analytics functionality located in a separate subsystem. Our conclusion is that the choice of analytics information collection method should to be based on intended usage, along with resulting complexity and cost of updates compared to hardware cost.

Industrial real-time software is commonly evaluated on real embedded systems, while simulators are less used, since the abstraction level and purpose vary with for example, different programming languages and run-time contexts. This paper extends, applies, and evaluates previous work on a flexible task design that improve code reuse between discrete event simulators and embedded real-time systems. The paper focuses on two parts: (i) The performance cost of the proposed design in practice, by comparing the flexible task design with a traditional threaded approach. (ii) The potential of an alternative way to support legacy code in combination with discrete event simulation. The experiments indicate an almost negligible performance cost with respect to the real-time behavior, i.e., latency and jitter, while enabling improved code reuse between discrete event simulation and industrial embedded real-time systems.

Most evaluations of industrial real-time software are conducted on real embedded systems. The use of simulators that provides easily reproducible evaluations is often limited, due to different levels of abstraction, e.g., programming languages and run-time contexts. This paper extends previous work on a flexible task design, enabling tasks to be agnostic to run-time context, with evaluations conducted on bare-metal and real-time operating systems. Based on the same design and experiments we extend the proof-of-concept implementation in a discrete event simulation context, executing on a Windows based simulation host. Our experiments show that the flexible task design can be driven in a simulation run-time context, and still support typical industrial constructs. The result indicates that improved code reuse between discrete event simulators and industrial embedded systems is feasible.

The run-time context in industrial embedded systems varies from bare-metal microcontrollers, to multicore-processors running real-time operating systems. Due to the longevity of industrial systems, reusability and evolvability are often considered crucial quality attributes. This paper presents a new flexible task design that enables tasks to be agnostic to run-time context. Evaluations of the design were made by conducting experiments using a proof of concept implementation of the proposed design. The experiments were based on typical industrial constructs, such as periodic tasks, and event signaling from interrupts. Findings from the experiments show that tasks can be more agnostic to run-time context and still deliver functionality normally used within industry. The results indicate that it is feasible to improve reusability and evolvability between different run-time contexts, and in addition, support hybrid configurations that can reduce resource usage, since e.g. a thread can be easily shared among several tasks.

De närmaste 15 åren kommer svenskindustri att med förnyad kraft fortsätta sin digitala omställning, ta tillsig en rad nya material, utveckla nyaaffärsmodeller och öka sin transformationsförmåga. Allt för att stärkasin konkurrenskraft, i symbios medhållbarhet – ekonomisk, ekologisk ochsocial. Coronapandemin medför förvisso enorma utmaningar för industrin,men efter den akuta kris hanteringenkommer med all sannolikhetindustriomställningen att ta ny fart.

Denna broschyr är en förkortad sammanställning av RISE rapport 2020:46 som finns på länken:http://urn.kb.se/resolve?urn=urn:nbn:se:ri:diva-44978

In software system development, testing can take considerable time and resources, and there are numerous examples in the literature of how to improve the testing process. In particular, methods for selection and prioritization of test cases can play a critical role in efficient use of testing resources. This paper focuses on the problem of selection and ordering of integration-level test cases. Integration testing is performed to evaluate the correctness of several units in composition. Further, for reasons of both effectiveness and safety, many embedded systems are still tested manually. To this end, we propose a process, supported by an online decision support system, for ordering and selection of test cases based on the test result of previously executed test cases. To analyze the economic efficiency of such a system, a customized return on investment (ROI) metric tailored for system integration testing is introduced. Using data collected from the development process of a large-scale safety-critical embedded system, we perform Monte Carlo simulations to evaluate the expected ROI of three variants of the proposed new process. The results show that our proposed decision support system is beneficial in terms of ROI at system integration testing and thus qualifies as an important element in improving the integration testing process.

Prioritization, selection and minimization of test cases are well-known problems in software testing. Test case prioritization deals with the problem of ordering an existing set of test cases, typically with respect to the estimated likelihood of detecting faults. Test case selection addresses the problem of selecting a subset of an existing set of test cases, typically by discarding test cases that do not add any value in improving the quality of the software under test. Most existing approaches for test case prioritization and selection suffer from one or several drawbacks. For example, they to a large extent utilize static analysis of code for that purpose, making them unfit for higher levels of testing such as integration testing. Moreover, they do not exploit the possibility of dynamically changing the prioritization or selection of test cases based on the execution results of prior test cases. Such dynamic analysis allows for discarding test cases that do not need to be executed and are thus redundant. This paper proposes a generic method for prioritization and selection of test cases in integration testing that addresses the above issues. We also present the results of an industrial case study where initial evidence suggests the potential usefulness of our approach in testing a safety-critical train control management subsystem.