Will Tracz, our esteemed editor and Used-Program salesman, has written an entertaining, non-technical book dealing with the practice (and lack of) of software reuse. Its a collection of essays, mostly rehashed (reused?) and updated from various columns and papers published over the years.. Its a short (a bit over 200 pages) easy reading and enjoyable book (I read most of it in one sitting). Some of the essays discuss what was printed in the past and a discussion of the current status of the points.

Safeware: System Safety and Computers

Static timing analysis is the state-of-the-art practice of ascertaining the timing behavior of current-generation real-time embedded systems. The adoption of more complex hardware to respond to the increasing demand for computing power in next-generation systems exacerbates some of the limitations of static timing analysis. In particular, the effort of acquiring (1) detailed information on the hardware to develop an accurate model of its execution latency as well as (2) knowledge of the timing behavior of the program in the presence of varying hardware conditions, such as those dependent on the history of previously executed instructions. We call these problems the timing analysis walls.In this vision-statement article, we present probabilistic timing analysis, a novel approach to the analysis of the timing behavior of next-generation real-time embedded systems. We show how probabilistic timing analysis attacks the timing analysis walls; we then illustrate the mathematical foundations on which this method is based and the challenges we face in the effort of efficiently implementing it. We also present experimental evidence that shows how probabilistic timing analysis reduces the extent of knowledge about the execution platform required to produce probabilistically accurate WCET estimations.

PROARTIS: Probabilistically Analyzable Real-Time Systems

In safety critical domains, system test cases are often derived from functional requirements in natural language (NL) and traceability between requirements and their corresponding test cases is usually mandatory. The definition of test cases is therefore time-consuming and error prone, especially so given the quickly rising complexity of embedded systems in many critical domains. Though considerable research has been devoted to automatic generation of system test cases from NL requirements, most of the proposed approaches re- quire significant manual intervention or additional, complex behavioral modelling. This significantly hinders their applicability in practice. In this paper, we propose Use Case Modelling for System Tests Generation (UMTG), an approach that automatically generates executable system test cases from use case spec- ifications and a domain model, the latter including a class diagram and constraints. Our rationale and motivation are that, in many environments, including that of our industry partner in the reported case study, both use case specifica- tions and domain modelling are common and accepted prac- tice, whereas behavioural modelling is considered a difficult and expensive exercise if it is to be complete and precise. In order to extract behavioral information from use cases and enable test automation, UMTG employs Natural Language Processing (NLP), a restricted form of use case specifica- tions, and constraint solving.

Automatic generation of system test cases from use case specifications

Probabilistic Timing Analysis (PTA) in general and its measurement-based variant called MBPTA in particular can mitigate some of the problems that impair current worst-case execution time (WCET) analysis techniques. MBPTA computes tight WCET bounds expressed as probabilistic exceedance functions, without needing much information on the hardware and software internals of the system. Classic WCET analysis has information needs that may be costly and difficult to satisfy, and their omission increases pessimism. Previous work has shown that MBPTA does well with benchmark programs. Real-world applications however place more demanding requirements on timing analysis than simple benchmarks. It is interesting to see how PTA responds to them. This paper discusses the application of MBPTA to a real avionics system and presents lessons learned in that process.

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Measurement-based probabilistic timing analysis: Lessons from an integrated-modular avionics case study

Selecting proper wireless network interfaces for user experience enhancement with guaranteed probability

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.

A Statistical Response-Time Analysis of Real-Time Embedded Systems

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.

/pdf/a-new-way-about-using-statistical-analysis-of-worst-case-meby19dr90.pdf

A new way about using statistical analysis of worst-case execution times

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.

A Metaheuristic Approach for Best Effort Timing Analysis Targeting Complex Legacy Real-Time Systems

This paper presents Rapid RT, 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 their temporal behavior, which violates the assumptions of traditional analytical methods for response time analysis and thereby makes them overly pessimistic. An evaluation is presented using two simulation models, inspired by an industrial robotic control system, and five other methods as reference.

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A Statistical Approach to Response-Time Analysis of Complex Embedded Real-Time Systems

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.

/pdf/simulation-based-timing-analysis-of-complex-real-time-2xlfd357h3.pdf

Yue Lu

Papers

A Statistical Response-Time Analysis of Real-Time Embedded Systems

A new way about using statistical analysis of worst-case execution times

A Metaheuristic Approach for Best Effort Timing Analysis Targeting Complex Legacy Real-Time Systems

A Statistical Approach to Response-Time Analysis of Complex Embedded Real-Time Systems

Simulation-Based Timing Analysis of Complex Real-Time Systems