Benchmark Generation for Timing Analysis

Worst case execution time (WCET) analysis is essential for exposing timeliness defects when developing hard real-time systems. However, it is too late to fix timeliness defects cheaply since developers generally perform WCET analysis in a final verification phase. To help developers quickly identify real timeliness defects in an early programming phase, a novel interactive WCET prediction with warning for timeout risk is proposed. The novelty is that the approach not only fast estimates WCET based on a control flow tree (CFT), but also assesses the estimated WCET with a trusted level by a lightweight false path analysis. According to the trusted levels, corresponding warnings will be triggered once the estimated WCET exceeds a preset safe threshold. Hence developers can identify real timeliness defects more timely and efficiently. To this end, we first analyze the reasons of the overestimation of CFT-based WCET calculation; then we propose a trusted level model of timeout risks; for recognizing the structural patterns of timeout risks, we develop a risk data counting algorithm; and we also give some tactics for applying our approach more effectively. Experimental results show that our approach has almost the same running speed compared with the fast and interactive WCET analysis, but it saves more time in identifying real timeliness defects.

In this article we give an overview of the worst-case execution time (WCET) analysis research performed by the WCET group of the ASTEC Competence Centre at Uppsala University. Knowing the WCET of a program is necessary when designing and verifying real-time systems. The WCET depends both on the program flow, such as loop iterations and function calls, and on hardware factors, such as caches and pipelines. WCET estimates should be both safe (no underestimation allowed) and tight (as little overestimation as possible). We have defined a modular architecture for a WCET tool, used both to identify the components of the overall WCET analysis problem, and as a starting point for the development of a WCET tool prototype. Within this framework we have proposed solutions to several key problems in WCET analysis, including representation and analysis of the control flow of programs, modeling of the behavior and timing of pipelines and other low-level timing aspects, integration of control flow information and low-level timing to obtain a safe and tight WCET estimate, and validation of our tools and methods. We have focussed on the needs of embedded real-time systems in designing our tools and directing our research. Our long-term goal is to provide WCET analysis as a part of the standard tool chain for embedded development (together with compilers, debuggers, and simulators). This is facilitated by our cooperation with the embedded systems programming-tools vendor IAR Systems.

Worst-case execution time (WCET) analysis of systems with data caches is one of the key challenges in real-time systems. Caches exploit the inherent reuse properties of programs by temporarily storing certain memory contents near the processor, in order that further accesses to such contents do not require costly memory transfers. Current worst-case data cache analysis methods focus on specific cache organizations (set-associative LRU, locked, ACDC, etc.), most of the times adapting techniques designed to analyze instruction caches. On the other hand, there are methodologies to analyze the data reuse of a program, independently of the data cache. In this paper we propose a generic WCET analysis framework to analyze data caches taking profit of such reuse information. It includes the categorization of data references and their integration in an IPET model. We apply it to a conventional LRU cache, an ACDC, and other baseline systems, and compare them using the TACLeBench benchmark suite. Our results show that persistence-based LRU analyses dismiss essential information on data, and a reuse-based analysis improves the WCET bound around 17% in average. In general, the best WCET estimations are obtained with optimization level 2, where the ACDC cache performs 39% better than a set-associative LRU.

Timing correctness of hard real-time systems is guaranteed by schedulability analysis and worst-case execution time (WCET) analysis of programs. Traditional WCET analysis mainly deals with application programs and has achieved success in industry. Timing analysis of application programs along cannot guarantee correctness of complete systems consisting RTOS. WCET tools designed for application program analysis have been applied to analyze RTOS routines by several research groups, but poor WCET estimations have been reported. Timing analysis of real-time systems considering both applications and RTOS has not been fully studied. So we intend to give a survey of related work on WCET analysis of RTOS. By summarizing previous work, challenges of WCET analysis of complete real-time systems are presented, and some possible further research potentials are unleashed.

The steadily growing embedded-systems market comprises many application domains in which real-time constraints must be satisfied. To guarantee that these constraints are met, the analysis of the worst-case execution time (WCET) of software components is mandatory. In general WCET analysis needs additional control-flow information, which may be provided manually by the user or calculated automatically by program analysis. For flexibility and simplicity reasons it is desirable to specify the flow information at the same level at which the program is developed, i.e., at the source level. In contrast, to obtain precise WCET bounds the WCET analysis has to be performed at machine-code level. Mapping and transforming the flow information from the source-level down to the machine code, where flow information is used in the WCET analysis, is challenging, even more so if the compiler generates highly optimized code. In this article we present a method for transforming flow information from source code to machine code. To obtain a mapping that is safe and accurate, flow information is transformed in parallel to code transformations performed by an optimizing compiler. This mapping is not only useful for transforming manual code annotations but also if platform-independent flow information is automatically calculated at the source level. We show that our method can be applied to every type of semantics-preserving code transformation. The precision of this flow-information transformation allows its users to calculate tight WCET bounds.

Real-time control systems must adequately react to changes in system state within a time limit determined by the dynamics of the controlled system, otherwise their stability might be compromised. It is therefore essential to determine the Worst-Case Execution Time (WCET) of the control algorithms to verify that they will always be able to satisfy that constraint. However, WCET analysis is a complex process, requiring manual intervention, and the computed bounds are often grossly overestimated. We avoid the difficulties of WCET estimation by making use of the single-path paradigm for the implementation of the control algorithm for a quadcopter. By using single-path code we do not only replace the cumbersome WCET analysis with a single measurement, we simultaneously avoid the detrimental effects of response-time variability. We show that single-path code can be applied to real-time controllers and that it is practical for dramatically simplifying WCET analysis as well as eliminating variability in the execution time. Our results show that despite its apparent inefficiency, the WCET of single-path code on a time-predictable soft microprocessor rivals that of a state-of-the-art superscalar processor.

For hard real-time systems, static code analysis is needed to derive a safe bound on the worst-case execution time (WCET). Virtually all prior work has focused on the accuracy of WCET analysis without regard to the speed of analysis. The resulting algorithms are often too slow to be integrated into the development cycle, requiring WCET analysis to be postponed until a final verification phase. In this paper we propose interactive WCET analysis as a new method to provide near-instantaneous WCET feedback to the developer during software programming. We show that interactive WCET analysis is feasible using tree-based WCET calculation. The feedback is realized with a plugin for the Java editor jEdit, where the WCET values are back-annotated to the Java source at the statement level. Comparison of this tree- based approach with the implicit path enumeration technique (IPET) shows that tree-based analysis scales better with respect to program size and gives similar WCET values.

Operating systems offering virtual memory and protected address spaces have been an elusive target of static worst-case execution time (WCET) analysis. This is due to a combination of size, unstructured code and tight coupling with hardware. As a result, hard real-time systems are usually developed without memory protection, perhaps utilizing a lightweight real-time executive to provide OS abstractions. This paper presents a WCET analysis of seL4, a third-generation micro kernel. seL4 is the world's first formally-verified operating-system kernel, featuring machine-checked correctness proofs of its complete functionality. This makes seL4 an ideal platform for security-critical systems. Adding temporal guarantees makes seL4 also a compelling platform for safety- and timing-critical systems. It creates a foundation for integrating hard real-time systems with less critical time-sharing components on the same processor, supporting enhanced functionality while keeping hardware and development costs low. We believe this is one of the largest code bases on which a fully context-aware WCET analysis has been performed. This analysis is made possible due to the minimalistic nature of modern micro kernels, and properties of seL4's source code arising from the requirements of formal verification.

The determination of the execution time upper bound, commonly called Worst-Case Execution Time (WCET), is a necessary step in the development and validation process for real-time systems.The WCET analysis techniques can be classified as static or dynamic.While a high-level language code suffices for the static techniques, for a precise WCET analysis a target architecture or its authentic simulator able to run the final machine-level code of an analyzed application is needed by the dynamic techniques.In the paper, we have decided not only to present a novel hybrid timing analysis technique, but also to show its practical applicability in the area of WCET analysis over particular embedded architecture (MSP430) and real-time operating system (FreeRTOS).Novelty of the presented method can be seen in the fact the operating system model is reflected during the analysis in order to facilitate the process of derivating schedulability test formulas, create detail task/stack analysis etc. Applicability of the method was tested using the MSPsim simulator of the MSP430 architecture.

Different cores typically share the last-level cache in a multi-core processor. Threads running on different cores may interfere with each other. Therefore, the multi-core worst-case execution time (WCET) analyzer must be able to safely and accurately estimate the worst-case inter-thread cache interference. This is not supported by current WCET analysis techniques that manly focus on single thread analysis. This paper presents a novel approach to analyze the worst-case cache interference and bounding the WCET for threads running on multi-core processors with shared L2 instruction caches. We propose to use an interference matrix to model inter-thread interference, on which basis we can calculate the worst-case inter-thread cache interference. Our experiments indicate that the proposed approach can give a worst-case bound less than 1%, as in benchmark fib-call, and an average 16.4% overestimate for threads running on a dual-core processor with shared-L2 cache. Our approach dramatically improves the accuracy of WCET overestimatation by on average 20.0% compared to work.

The schedulability analysis of real-time embedded systems requires worst case execution time (WCET) analysis for the individual tasks. Bounding WCET involves not only language-level program path analysis, but also modeling the performance impact of complex micro-architectural features present in modern processors. In this paper, we statically analyze the execution time of embedded software on processors with speculative execution. The speculation of conditional branch outcomes (branch prediction) significantly improves a program's execution time. Thus, accurate modeling of control speculation is important for calculating tight WCET estimates. We present a parameterized framework to model the different branch prediction schemes. We further consider the complex interaction between speculative execution and instruction cache performance, that is, the fact that speculatively executed blocks can generate additional cache hits/misses. We extend our modeling to capture this effect of branch prediction on cache performance. Starting with the control flow graph of a program, our technique uses integer linear programming to estimate the program's WCET. The accuracy of our method is demonstrated by tight estimates obtained on realistic benchmarks.

Worst-case execution time (WCET) analysis of real-time code needs to be performed on the executable binary code for soundness. Determination of loop bounds and elimination of infeasible paths, essential for obtaining tight bounds, frequently depends on program state that is difficult to extract from static analysis of the binary. Obtaining this information generally requires manual intervention, or compiler modifications to preserve more semantic information from the source program. We propose an alternative approach, which leverages an existing translation-validation framework, to enable high-assurance, automatic determination of loop bounds and infeasible paths. We show that this approach automatically determines all loop bounds and many (possibly all) infeasible paths in the seL4 microkernel, as well as in standard WCET benchmarks which are in the language subset of our C parser.

The Worst-Case Execution Time (WCET) computed by a WCET analyzer is usually not tight, leaving a gap between the actual and the computed WCET of a program. In this article we present a novel on-demand WCET feasibility refinement technique, called WCET Squeezing, for minimizing this gap.

This paper presents techniques to integrate worst-case execution time (WCET) data into a compiler. Currently, a tight integration of WCET into compilers is strongly desired, but only some ad-hoc approaches were reported currently. Previous work mainly used self-written WCET estimators with limited functionality and preciseness during compilation. A very tight integration of a high quality WCET analyzer into a compiler was not yet achieved. This work is the first to present such a tight coupling between a compiler and the WCET analyzer aiT. This is done by automatically translating the assembly-like contents of the compiler's low-level format (LLIR) to aiT's exchange format CRL2. Additionally, the results produced by aiT are automatically collected and re-imported into the compiler infrastructure. The work described in this paper is smoothly integrated into a C compiler for the Infineon TriCore processor. It opens up new possibilities for the design of WCET-aware optimizations in the future. The concepts for extending the compiler structure are kept very general so that they are not limited to WCET information. Rather, it is possible to use our concepts also for multi-objective optimization of e. g. best-case execution time (BCET) or energy dissipation

The authors present co-transformation, a novel approach to the mapping of execution information from the source code of a program to the object code for the purpose of worst-case execution time (WCET) analysis. Their approach is designed to handle the problems introduced by optimizing compilers, i.e. that the structure of the object code is very different from the structure of the source code. The co-transformer allows one to keep track of how different compiler transformations, including optimizations, influence the execution time of a program. This allows one to statically calculate the execution time of a program at the object code level, using information about the program execution obtained at the source code level.