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  • 1.
    Bohlin, markus
    et al.
    SICS.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Kreuger, Per
    SICS, Sweden.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Best-Effort Simulation-Based Timing Analysis using Hill-Climbing with Random Restarts2009In: In Proc. of RTCSA, Aug. 2009., 2009Conference paper (Refereed)
  • 2.
    Bohlin, Markus
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Kreuger, Per
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Simulation-Based Timing Analysis of Complex Real-Time Systems2009In: 2009 15TH IEEE INTERNATIONAL CONFERENCE ON EMBEDDED AND REAL-TIME COMPUTING SYSTEMS AND APPLICATIONS, PROCEEDINGS, 2009, p. 321-328Conference paper (Refereed)
    Abstract [en]

    This paper presents an efficient best-effort approach for simulation-based timing analysis of complex real- time systems. The method can handle in principle any software design that can be simulated, and is based on controlling simulation input using a simple yet novel hill- climbing algorithm. Unlike previous approaches, the new algorithm directly manipulates simulation parameters such as execution times, arrival jitter and input. An evaluation is presented using six different simulation models, and two other simulation methods as reference: Monte Carlo simulation and MABERA. The new method proposed in this paper was 4-11% more accurate while at the same time 42 times faster, on average, than the reference methods.

  • 3.
    Kraft, Johan
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering.
    Norström, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    Wall, Anders
    Mälardalen University, School of Innovation, Design and Engineering.
    A Metaheuristic Approach for Best Effort Timing Analysis targeting Complex Legacy Real-Time Systems2008In: PROCEEDINGS OF THE 14TH IEEE REAL-TIME AND EMBEDDED TECHNOLOGY AND APPLICATIONS SYMPOSIUM, 2008, p. 258-269Conference paper (Refereed)
    Abstract [en]

    Many companies developing real-time systems today have today no means for response time analysis, as their systems violate the assumptions of traditional analytical methods for response-time analysis and are too complex for exhaustive analysis using model checking.

    This paper presents a novel approach for best effort response time analysis targeting such systems, where probabilistic simulation is guided by a search algorithm of metaheuristic type, similar to genetic algorithms.

    The best effort approach means that the result is not guaranteed to be the worst-case response time, but also that the method scales to large industrial systems.

    The proposed method should be regarded as a form of testing, focusing on timing properties.

    An evaluation is presented which indicates that the proposed approach is significantly more efficient than traditional probabilistic simulation in finding extreme task response times. The paper also presents a method for finding good parameters for the search algorithm, in order to improve its efficiency.

  • 4.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering.
    Approximation Techniques for Timing Analysis of Complex Real-Time Embedded Systems2010Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    To date, many industrial embedded systems are very large, flexible, and highly configurable software systems, containing millions of lines of code and consisting of hundreds of tasks, many with real-time constraints, being triggered in complex, nested patterns. Furthermore, the temporal dependencies between tasks in such systems are difficult to determine analytically, and they vary the execution time and response time of tasks greatly. We refer to such systems as Complex Real-Time Embedded Systems (CRTES).

    To maintain, analyze and reuse such CRTES is very difficult and expensive, which, nevertheless, offers high business value in response to great concern in industry. Moreover, in such context, not only the functional behavior of systems has to be assured, but also non-functional properties such as the temporal behavior, i.e., Worst-Case Response Time (WCRT) of the adhering tasks in systems has to be known. However, due to high complexity of such systems and the nature of the problem, the exact WCRT of tasks is impossible to find in practice, but may only be bounded. In addition, the existing relatively well-developed theories for modeling and analysis of real-time systems are having problems, which limit their application in the context. In this thesis, we address this challenge, and present a framework for approximate timing analysis of CRTES that provides a tight interval of WCRT estimates of tasks by the usage of three novel contributions.

    The first contribution is a novel statistical approach to WCRT analysis of CRTES. The proposed algorithm combines Extreme Value Theory (EVT) with other statistical methods in order to produce a probabilistic WCRT estimate, using response time data from either Monte Carlo simulations of a detailed model of the system, or time-stamped traces of the real system execution. The focus of the method is to give a WCRT prediction with a given probability of being exceeded, which potentially could be considered as an upper bound on the WCRT estimate in systems, especially in the case where conventional timing analysis methods cannot be applied.

    The second contribution is to introduce a concrete process of formally obtaining the exact value of both Worst-Case Execution Time (WCET) and WCRT of tasks in the system model by using upper-part binary search algorithms together with a timed model checker, after a semantic-preserving model transformation. The underline premise is that the size and complexity of CRTES have to be reduced such that they can be manageable by the model checking tool.

    The third contribution is to apply an optimization algorithm, in this case a meta-heuristic search algorithm, on top of the traditional Monte Carlo simula-tion, which yields substantially better results with respect to tight lower bounds on WCRT estimates of tasks in CRTES.

    In addition, a number of tools have been implemented and used for the evaluation of the research results. These evaluations, using four simulation models depicting two fictive but representative industrial control applications, give clear indication that the proposed methods have the potential to be both applicable and useful in practice.

    Download full text (pdf)
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  • 5.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering.
    Pragmatic Approaches for Timing Analysis of Real-Time Embedded Systems2012Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Many industrial real-time embedded systems are very large, flexible and highly configurable software systems. Such systems are becoming ever more complex, and we are reaching the stage in which even if existing timing analysis was feasible from a cost and technical perspective, the analysis results are overly pessimistic, making them less useful to practitioners. When combined with the fact that most existing real-time embedded systems tend to be probabilistic in nature due to high complexity featured by advanced hardware and more flexible and/or adaptive software applications, this advocates moving toward pragmatic timing analysis, which is not specifically limited by constrains related to intricate task execution and temporal dependencies in systems. In this thesis, we address this challenge, and we present two pragmatic timing analysis techniques for real-time embedded systems.

    The first contribution is a simulation-based analysis using two simple yet novel search algorithms of meta-heuristic type, i.e., a form of genetic algorithms and hill-climbing with random restarts, yielding substantially better results, comparing traditional Monte Carlo simulation-based analysis methods.

    As the second contribution, we discuss one major issue when using simulation-based methods for timing analysis of real-time embedded systems, i.e., model validity, which determines whether a simulation model is an accurate representation of the target system at the certain level of satisfaction, from a task response time and execution time perspective.

    The third contribution is a statistical timing analysis, which, unlike the traditional timing analysis, does not require worst-case execution times of tasks as inputs, and computes a probabilistic task worst-case response time estimate pertaining to a configurable task reliability requirement.

    In addition, a number of tools have been implemented and used for the evaluation of our research results. Our evaluations, using different simulation models depicting fictive but representative industrial control applications, have shown a clear indication that our new timing analysis techniques have the potential to be both applicable and useful in practice, as well as being complementary to software testing focusing on timing properties of real-time embedded systems that are used in various domains of industrial automation, aerospace and defense, automotive telematics, etc.

    Download full text (pdf)
    fulltext
  • 6.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering.
    Trace-Based Statistical Timing Analysis of Complex Industrial Real-Time Embedded Systems2011In: Real-Time in Sweden 2011 (RTiS' 11), 2011Conference paper (Refereed)
    Abstract [en]

    Real-time embedded systems are becoming ever more complex, and we are reaching the stage where even if static Response-Time Analysis (RTA) was feasible from a cost and technical perspective, the results are overly pessimistic making them less useful to the practitioner. When combined with the fact that most timing analysis tends to be statistical in nature, this suggests there should be a move toward statistical RTA, which gives a task's worst-case response time estimate under a predictable probability of being exceeded. However, to make such analysis useful, it is imperative that we have evidence that the statistical RTA and the information analyzed is sufficiently accurate. In this project, we will address the above issue by presenting and validating a statistical RTA technique based around analyzing timing traces taken from real systems, which can cope with systems that are complex from both a size and tasks' dependencies perspective, as well as some typical case when the source code and/or object code of systems is/are withheld due to the protection of intellectual property.

  • 7.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Bohlin, Markus
    Swedish Institute of Computer Science, Kista, Sweden).
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Kreuger, Per
    Swedish Institute of Computer Science, Kista, Sweden).
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Norström, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    Approximate Timing Analysis of Complex Legacy Real-Time Systems using Simulation Optimization2008In: Proceedings of the Work-In-Progress (WIP) track of the 29th IEEE Real-Time Systems Symposium (RTSS), Barcelona, Spain, 2008Conference paper (Refereed)
  • 8.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Cicchetti, Antonio
    Mälardalen University, School of Innovation, Design and Engineering.
    Bygde, Stefan
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Norström, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    Transformational Specification of Complex Legacy Real-Time Systems via Semantic Anchoring2009In: 2nd IEEE International Workshop on Component-Based Design of Resource-Constrained Systems (CORCS 2009) @ COMPSAC, 2009, p. 1183-1188Conference paper (Refereed)
    Abstract [en]

    RTSSim is a framework for simulating models extracted from complex legacy real-time systems which are task-oriented, run on a single processor and are developed in C. Such RTSSim models describe functional and temporal behavior as well as the resource usage of the system. However, the semantics specification of RTSSim models remains a challenging problem indeed, especially with tractable complexity to obtain a formal model which can be analyzed for instance by a model checking tool. In this paper, we present an approach towards using semantic anchoring for the transformational specification of RTSSim models, by relying on units with well-defined operational semantics and tool support. Specifically, Timed Automata with Tasks (TAT) in TIMES is chosen as the semantic unit with the purpose of anchoring different behavioral concerns of RTSSim models in all aspects. In this respect, model transformations are conducted at the meta-model level allowing the original operational semantics of RTSSim models to be preserved, while at the same time it can be presented in TIMES models in terms of a network of TAT.

  • 9.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Cicchetti, Antonio
    Mälardalen University, School of Innovation, Design and Engineering.
    Sjödin, Mikael
    Mälardalen University, School of Innovation, Design and Engineering.
    Mäki-Turja, Jukka
    Mälardalen University, School of Innovation, Design and Engineering.
    Bygde, Stefan
    Mälardalen University, School of Innovation, Design and Engineering.
    Norström, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    Towards Response-Time Analysis of Complex Real-Time Systems by using ParametricWorst-Case Execution-Time Estimate on Tasks – A Case Study for Robotic Control System2009In: 21st Euromicro Conference on Real-Time Systems (ECRTS 09) Work-In-Progress (WIP) session, Dublin, Ireland, 2009Conference paper (Refereed)
  • 10.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Bate, Iain
    University of York.
    A statistical approach to simulation model validation in response-time analysis of complex real-time embedded systems2011In: Proceedings of the ACM Symposium on Applied Computing 2011, 2011, p. 711-716Conference paper (Refereed)
    Abstract [en]

    As simulation-based analysis methods make few restrictions on the system design and scale to very large and complex systems, they are widely used in, e.g., timing analysis of complex real-time embedded systems (CRTES) in industrial circles. However, before such methods are used, the analysis simulation models have to be validated in order to assess if they represent the actual system or not, which also matters to the confidence in the simulation results. This paper presents a statistical approach to validation of temporal simulation models extracted from CRTES, by introducing existing mature statistical hypothesis tests to the context. Moreover, our evaluation using simulation models depicting a fictive but representative industrial robotic control system indicates that the proposed method can successfully identify temporal differences between different simulation models, hence it has the potential to be considered as an effective simulation model validation technique. © 2011 ACM.

  • 11.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Norström, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    A Statistical Approach for Validation of Task Simulation Models with Intricate Temporal Execution Dependencies2010In: Proceedings of the Work-In-Progress (WIP) track of 16th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS2010), 2010Conference paper (Refereed)
  • 12.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Norström, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    On Validation of Simulation Models in Timing Analysis of Complex Real-Time Embedded Systems2010In: The 15th IEEE International Conference on Emerging Technologies and Factory Automation (EFTA'10), Work-In-Progress (WIP) session., Bilbao, 2010Conference paper (Refereed)
    Abstract [en]

    In this paper, we present work toward validating simulation models extracted from complex real-time embedded systems, from the perspective of response time and execution time of adhering tasks, by using the non-parametric two-sample Kolmogorov-Smirnov test. Moreover, we introduce a method of reducing the number of samples used in the analysis, while keeping the accuracy of results. The evaluation using a fictive but representative system model inspired by a real robotic control system with a set of change scenarios, shows a promising result: the proposed algorithm has the potential of assessing whether the extracted simulation model is a sufficiently accurate approximation of the target system.

  • 13.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    An Evaluation Framework for Complex Industrial Real-Time Embedded Systems2012Report (Other academic)
    Abstract [en]

    In this technical report, we introduce an evaluation framework which are centering around four base models, inspired by an industrial robotic control application. Specifically, such evaluation models are quite complicated from a task execution and temporal dependencies perspective, making difficult to perform the corresponding timing analysis.

  • 14.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    On Using Extreme Value Theory in Response-Time Analysis of Priority-Driven Periodic Real-Time Systems2010In: The 31st IEEE Real-Time Systems Symposium (RTSS'10), Work-In-Progress (WIP) session, San Diego, CA, USA, 2010Conference paper (Refereed)
  • 15.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Bate, Iain
    University of York.
    Cucu-Grosjean, Liliana
    INRIA Nancy-Grand Est, Nancy, France.
    A New Way about using Statistical Analysis of Worst-Case Execution Times2011In: ACM SIGBED Review, ISSN 1551-3688, Vol. 8, no 3, p. 11-14Article in journal (Refereed)
    Abstract [en]

    In this paper, we revisit the problem of using Extreme Value Theory (EVT) in the Worst-Case Execution Time (WCET) analysis of the programs running on a single processor. Our proposed statistical WCET analysis method consists of a novel sampling mechanism tackling with some problems that hindered the application of using EVT in the context, and a statistical inference about computation of a WCET estimate of the target program. To be specific, the presented sampling mechanism takes analysis samples from the target program based around end-to-end measurements. Next, the statistical inference using EVT together with other statistical techniques, analyzes such timing traces which contain the execution time data of the program, to compute a WCET estimate with a certain predictable probability of being exceeded.

  • 16.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Bate, Iain
    University of York.
    Cucu-Grosjean, Liliana
    INRIA Nancy-Grand Est.
    A statistical response-time analysis of complex real-time embedded systems by using timing traces2011In: SIES 2011 - 6th IEEE International Symposium on Industrial Embedded Systems, Conference Proceedings, 2011, p. 43-46Conference paper (Refereed)
    Abstract [en]

    Real-time embedded systems are becoming ever more complex, and we are reaching the stage where even if static Response-Time Analysis (RTA) was feasible from a cost and technical perspective, the results are overly pessimistic making them less useful to the practitioner. When combined with the fact that most timing analysis tends to be statistical in nature, this suggests there should be a move towardstatistical RTA. However, to make such analysis useful, it is imperative that we have evidence that the statistical RTA and the information analyzed is sufficiently accurate. In this paper we present and validatea technique for statistical RTA that can cope with systems that are complex from both a size and tasks' dependencies perspective. This claim is backed up by our evaluation using information from realindustrial control systems.

  • 17.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Bate, Iain
    Mälardalen University, School of Innovation, Design and Engineering.
    Cucu-Grosjean, Liliana
    INRIA Nancy-Grand Est.
    A statistical response-time analysis of real-time embedded systems2012In: Proceedings - Real-Time Systems Symposium, 2012, 2012, p. 351-362Conference paper (Refereed)
    Abstract [en]

    Real-time embedded systems are becoming ever more complex. We are reaching the stage where even if static Response-Time Analysis (RTA) was feasible from a cost and technical perspective, the results of such an analysis are overly pessimistic. This makes them less useful to the practitioner. In addition, the temporal validation and verification of such systems in some applications, e.g., aeronautics, requires the probability of obtaining a worst-case response time larger than a given value in order to support dependable system functions. All these facts advocate moving toward statistical RTA, which instead of calculating absolute worst-case timing guarantees, computes a probabilistic worst-case response time estimate. The contribution of this paper is to present and evaluate such a statistical RTA technique which uses a black box view of the systems under analysis, by not requiring estimates of parameters such as worst-case execution times of tasks. Furthermore, our analysis is applicable to real systems that are complex, e.g., from a task dependencies perspective.

  • 18.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Bate, Iain
    University of York.
    Cucu-Grosjean, Liliana
    INRIA Nancy-Grand Est, Nancy, France.
    A Trace-Based Statistical Worst-Case Execution Time Analysis of Component-Based Real-Time Embedded Systems2011In: 2011 IEEE 16TH CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA) / [ed] Mammeri, Z., New York: IEEE , 2011Conference paper (Refereed)
    Abstract [en]

    This paper describes the tool support for a framework for performing statistical WCET analysis of real-time embedded systems by using bootstrapping sampling and Extreme Value Theory (EVT). To be specific, bootstrapping sampling is used to generate timing traces, which not only fulfill the requirements given by statistics and probability theory, but also are robust to use in the context of estimating the WCET of programs. Next, our proposed statistical inference uses EVT to analyze such timing traces, and computes a WCET estimate of the target program, pertaining to a given predictable probability. The evaluation results show that our proposed method could have the potential of being able to provide a tighter upper bound on the WCET estimate of the programs under analysis, when compared to the estimates given by the referenced WCET analysis methods.

  • 19.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Bate, Iain
    University of York.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Norström, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    Assessment of trace-differences in timing analysis for Complex Real-Time Embedded Systems2011In: SIES 2011 - 6th IEEE International Symposium on Industrial Embedded Systems, Conference Proceedings, 2011, p. 284-293Conference paper (Refereed)
    Abstract [en]

    In this paper, we look at identifying temporal differences between different versions of Complex Real-Time Embedded Systems (CRTES) by using timing traces representing response times and executiontimes of tasks. In particular, we are interested in being able to reason about whether a particular change to CRTES will impact on their temporal performance, which is difficult to answer due to the complicatedtiming behavior such CRTES have. To be specific, we first propose a sampling mechanism to eliminate dependencies existing in tasks' response time and execution time data in the traces taken from CRTES, which makes any statistical inference in probability theory and statistics realistic. Next, we use a mature statistical method, i.e., the non-parametric two-sample Kolmogorov-Smirnov test, to assess the possible temporal differences between different versions of CRTES by using timing traces. Moreover, we introduce a method of reducing the number of samples used in the analysis, while keeping the accuracy ofanalysis results. This is not trivial, as collecting a large amount of samples in terms of executing real systems is often costly. Our evaluation using simulation models describing an industrial robotic controlsystem with complicated tasks' timing behavior, indicates that the proposed method can successfully identify temporal differences between different versions of CRTES, if there is any. Furthermore, our proposed method outperforms the other statistical methods, e.g., bootstrap and permutation tests, that are often widely used in contexts, in terms of bearing on the accuracy of results when other methods have failed.

  • 20.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Bate, Iain
    Mälardalen University, School of Innovation, Design and Engineering.
    Norström, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    Timing Analyzing for Systems with Execution Dependencies between Tasks2010In: Proceedings of the ACM Symposium on Applied Computing 201, 2010, p. 357-358Conference paper (Refereed)
    Abstract [en]

    In this paper, a novel approach to timing analysis of complex real-time systems with intricate execution dependencies between tasks, such as asynchronous message-passing and globally shared state variables, is presented. By applying the method to a model taken from a real robotic control system, we show the benefit, in terms of reduced pessimism, when compared to a combination of standard static WCET analysis and Response-Time Analysis.

  • 21.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Bate, Iain
    University of York.
    Norström, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    Timing analyzing for systems with task execution dependencies2010In: Proceedings - International Computer Software and Applications Conference, 2010, p. 515-524Conference paper (Refereed)
    Abstract [en]

    This paper presents a novel approach to timing analysis of complex real-time systems containing data-driven tasks with intricate executiondependencies. Using a system model inspired by industrial control systems, we show how the execution time of tasks can be represented as a mathematical expression instead of a single numeric value. Next, based on this more detailed modeling, we introduce a concrete process of formally obtaining the exact value of both Worst-Case Execution-Time (WCET) and Worst-Case Response-Time (WCRT) of tasks by using upper-part binary search and TIMES (a timed model checker). Finally, in order to show the potential of the proposed approach, we apply it to a model created from a real robotic control system for which the traditional way of obtaining a WCET estimate (through static WCET analysis) on tasks for usage in basic RTA is not appropriate. Our results indicate a significant reduction of pessimism when compared to basic RTA using WCET estimates on tasks given by a basic assumption.

  • 22.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering. INRIA Nancy-Grand Est, Nancy, France.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Cucu-Grosjean, Liliana
    INRIA Nancy-Grand Est, Nancy, France.
    Bate, Iain
    University of York, York, United Kingdom.
    RapidRT: A Tool For Statistical Response-Time Analysis of Complex Industrial Real-Time Embedded Systems2011Conference paper (Refereed)
    Abstract [en]

    RapidRT is a tool for statistical response time analysis of Complex Industrial Real-Time Embedded Systems (CIRTES). A key feature of this tool is that it does not require worst-case execution times of tasks to be known for the computation of a probabilistic task worst-case response time estimate. The presented tool is a step towards bridging the gap between academic research and industrial practice.

  • 23.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    An Approximate Timing Analysis Framework for Complex Real-Time Embedded Systems2010In: Proceedings - 2010 13th IEEE International Conference on Computational Science and Engineering, CSE 2010, 2010, p. 102-111Conference paper (Refereed)
    Abstract [en]

    To maintain, analyze and reuse many of today's Complex Real-Time Embedded Systems (CRTES) is very difficult and expensive, which, nevertheless, offers high business value in response to great concern in industry. In such context, not only functional behavior but also non-functional properties of systems have to be assured, i.e., Worst-Case Response Time (WCRT) of tasks has to be known. However, due to high complexity of such systems and the nature of the problem, the exact WCRT of tasks is impossible to find in practice, but may only be bounded. In addition, the existing relatively well developed theories for modeling and analysis of real-time systems are having problems which limit their application in the context. In this paper, we address this challenge by presenting a framework for approximate timing analysis of CRTES, namely AESIR-CORES, which provides a tight interval of WCRT estimates of tasks by the usage of two novel contributions. Our evaluation using three models inspired by two fictive but representative industrial CRTES indicates that AESIR-CORES can either successfully obtain the actual WCRT values, or have the potential to bound the unknown actual WCRT values from a statistical perspective.

  • 24.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Norström, Christer
    SICS.
    A Statistical Approach to Response-Time Analysis of Complex Real-Time Embedded Systems2010In: Proceedings of the 16th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA 2010), 2010, p. 153-160Conference paper (Refereed)
    Abstract [en]

    This paper presents RapidRT, a novel statistical approach to Worst-Case Response-Time (WCRT) analysis targeting complex embedded real-time systems. The proposed algorithm combines Extreme Value Theory (EVT) and other statistical methods in order to produce a probabilistic WCRT estimate. This estimate is calculated using response time data from either Monte Carlo simulations of a detailed model of the system, or from response-time measurements of the real system. The method could be considered as a pragmatic approach intended for complex industrial systems with real-time requirements. The target systems contain tasks with many intricate dependencies in theirtemporal behavior, which violates the assumptions of traditional analytical methods for response time analysis and thereby makes them overly pessimistic. An evaluation ispresented using two simulation models, inspired by an industrial robotic control system, and five other methods as reference.

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  • 25.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Norström, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    A Statistical Approach to Simulation Model Validation in Timing Analysis of Complex Real-Time Embedded Systems2010In: Proceedings - 16th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, RTCSA 2010, Brussels, 2010, p. -160, article id 5591317Conference paper (Refereed)
    Abstract [en]

    Simulation-based analysis methods make few restrictions on the system design and scale to very large and complex systems, therefore they are widely used in timing analysis of complex industrial embedded systems. This paper presents a statistical approach to validation of temporal simulation models extracted from complex embedded systems, by introducing existing mature statistical methods to the context. The proposed approach firstly collects sampling distributions of response time and execution time data of tasks in both the modeled system and the model, based on simple random samples (SRS). The second step of the approach is to compare the sampling distributions, regarding interesting timing properties, by using the non-parametric two-sample Kolmogorov-Smirnov test. The evaluation using a fictive system model inspired by a real robotic control system with a set of change scenarios, shows a promising result. The proposed algorithm can identify temporal differences between the target system and its extracted model, i.e., the algorithm can assess whether the extracted model is a sufficiently accurate approximation of the target system.

  • 26.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Norström, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    Statistical-based Response-Time Analysis of Systems with Execution Dependencies between Tasks2009In: Proceedings of the Work-In-Progress (WIP) track of the 30th IEEE Real-Time Systems Symposium (RTSS'09), Washington, DC, USA, 2009, p. 73-76Conference paper (Refereed)
  • 27.
    Lu, Yue
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nolte, Thomas
    Mälardalen University, School of Innovation, Design and Engineering.
    Kraft, Johan
    Mälardalen University, School of Innovation, Design and Engineering.
    Norström, Christer
    Mälardalen University, School of Innovation, Design and Engineering.
    Statistical-based Response-Time Analysis of Systems with Execution Dependencies between Tasks2010In: Proceedings of the IEEE International Conference on Engineering of Complex Computer Systems, ICECCS, 2010, p. 169-179Conference paper (Refereed)
    Abstract [en]

    This paper presents a novel statistical-based approach to Worst-Case Response-Time (WCRT) analysis of complex real-time system models. These system models have been tailored to capture intricate execution dependencies between tasks, inspired by real industrial control systems. The proposed WCRT estimation algorithm is based on Extreme Value Theory (EVT) and produces both WCRT estimates together with a probability of being exceeded. By using the tools developed, an evaluation is presented using three different simulation models, and four other methods as reference: Monte Carlo simulation, MABERA, HCRR and traditionalResponse-Time Analysis (basic RTA). Empirical results demonstrate that the benefit of the proposed approach, in terms of 1) reduced pessimism when compared to basic RTA and 2) validated guarantee of never being less than the actual response time values. The proposed approach also needs much fewer simulations compared to other three simulation-based methods.

  • 28.
    Zhou, Jiale
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Hänninen, Kaj
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lundqvist, Kristina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Provenzano, Luciana
    A Hazard Domain Ontology for Preliminary Hazard Analysis in Reuse Scenarios2016Report (Other academic)
  • 29.
    Zhou, Jiale
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Hänninen, Kaj
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lundqvist, Kristina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Provenzano, Luciana
    Bombardier Transportation AB, Sweden.
    Forsberg, Kristina
    Saab AB, Sweden.
    An Environment-Driven Ontological Approach to Requirements Elicitation for Safety-Critical Systems2015In: 23rd IEEE International Requirements Engineering Conference RE'15, 2015, p. 247-251Conference paper (Refereed)
    Abstract [en]

    The environment, where a safety critical system (SCS) operates, is an important source from which safety requirements of the SCS can originate. By treating the system under construction as a black box, the environment is typically documented as a number of assumptions, based on which a set of environmental safety requirements will be elicited. However, it is not a trivial task in practice to capture the environmental assumptions to elicit safety requirements. The lack of certain assumptions or too strict assumptions will either result in incomplete environmental safety requirements or waste many efforts on eliciting incorrect requirements. Moreover, the variety of operating environment for an SCS will further complicate the task, since the captured assumptions are at risk of invalidity, and consequently the elicited requirements need to be revisited to ensure safety has not been compromised by the change. This short paper presents an on-going work aiming to 1) systematically organize the knowledge of system operating environment and, 2) facilitate the elicitation of environmental safety requirements. We propose an ontological approach to achieve the objectives. In particular, we utilize conceptual ontologies to organize the environment knowledge in terms of relevant environment concepts, relations among them and axioms. Environmental assumptions are captured by instantiating the environment ontology. An ontological reasoning mechanism is also provided to support elicitation of safety requirements from the captured assumptions.

  • 30.
    Zhou, Jiale
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering.
    Lundqvist, Kristina
    Mälardalen University, School of Innovation, Design and Engineering.
    A Context-based Information Retrieval Technique for Recovering Use-Case-to-Source-Code Trace Links in Embedded Software Systems2013Conference paper (Refereed)
    Abstract [en]

    Post-requirements traceability is the ability to relate requirements (e.g., use cases) forward to corresponding design documents, source code and test cases by establishing trace links. This ability is becoming ever more crucial within embedded systems development, as a critical activity of testing, verification, validation and certification. However, semi-automatically or fullyautomatically generating accurate trace links remains an open research challenge, especially for legacy systems. Vector Space Model (VSM), a notably known Information Retrieval (IR) technique aims to remedy this situation. However, VSMÂ’s lowaccuracy level in practice is a limitation. The contribution of this paper is an improved VSM-based post-requirements traceability recovery approach using a novel context analysis. Specifically, the analysis method can better utilize context information extracted from use cases to discover relevant source code files. Our approach is evaluated by using three different embedded applications in the domains of industrial automation, automotive and mobile. The evaluation shows that our new approach can achieve better accuracy than VSM, in terms of higher values of three main IR metrics, i.e., recall, precision, and mean average precision, when it handles embedded software applications.

  • 31.
    Zhou, Jiale
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lundqvist, Kristina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A TASM-based requirements validation approach for safety-critical embedded systems2014In: 19th International Conference on Reliable Software Technologies, Ada-Europe 2014, 2014, p. 43-57Conference paper (Refereed)
    Abstract [en]

    Requirements validation is an essential activity to carry out in the system development life cycle, and it confirms the completeness and consistency of requirements through various levels. Model-based formal methods can provide a cost-effective solution to requirements validation in a wide range of domains such as safety-critical applications. In this paper, we extend a formal language Timed Abstract State Machine (TASM) with two newly defined constructs Event and Observer, and propose a novel requirements validation approach based on the extended TASM. Specifically, our approach can: 1) model both functional and non-functional (e.g. timing and resource consumption) requirements of the system at different levels and, 2) perform requirements validation by utilizing our developed toolset and a model checker. Finally, we demonstrate the applicability of our approach in real world usage through an industrial case study of a Brake-by-Wire system.

  • 32.
    Zhou, Jiale
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Lu, Yue
    Mälardalen University, School of Innovation, Design and Engineering.
    Lundqvist, Kristina
    Mälardalen University, School of Innovation, Design and Engineering.
    An Improved VSM-based Post-Requirements Traceability Recovery Approach Using Context Analysis2013Report (Other academic)
    Abstract [en]

    Automatically generating traceability links between software development artifacts existing throughout systems development life cycle, is becoming ever more important for requirements traceability. It remains an open software engineering challenge, especially for legacy systems, when the demand for minimizing human intervention is considered. The Vector Space Model (VSM), a notably known information retrieval technique, attempts to remedy the situation by reducing the required manual effort. One limitation of VSM is its low-level performance in practice, which can be improved by involving human intervention in the requirements traceability process earlier. The contribution of this paper is to present an improved VSM-based post/requirements traceability recovery approach by using a novel context analysis. This is done by firstly removing redundant information in the search space of the artifacts wrt a requirement, and then using both requirement and context queries to refine the results given by the standard VSM. In this way, the subsequent artifacts from the source requirement are more likely to be retrieved in the recovery process. Our approach is evaluated by using two chosen datasets (i.e., eTour and iTrust), of which results show that the proposed approach can achieve better performance in terms of discovering more true trace links and obtaining higher quality lists of traceability links than the standard VSM.

1 - 32 of 32
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