We present RETA (Relative Timing Analysis), a differential timing analysis technique to verify the impact of an update on the execution time of embedded software. Timing analysis is computationally expensive and labor intensive. Software updates render repeating the analysis from scratch a waste of resources and time, because their impact is inherently confined. To determine this boundary, in RETA we apply a slicing procedure that identifies all relevant code segments and a statement categorization that determines how to analyze each such line of code. We adapt a subset of RETA for integration into aiT, an industrial timing analysis tool, and also develop a complete implementation in a tool called DELTA. Based on staple benchmarks and realistic code updates from official repositories, we test the accuracy by analyzing the worst-case execution time (WCET) before and after an update, comparing the measures with the use of the unmodified aiT as well as real executions on embedded hardware. DELTA returns WCET information that ranges from exactly the WCET of real hardware to 148% of the new version's measured WCET. With the same benchmarks, the unmodified aiT estimates are 112% and 149% of the actual executions; therefore, even when DELTA is pessimistic, an industry-strength tool such as aiT cannot do better. Crucially, we also show that RETA decreases aiT's analysis time by 45% and its memory consumption by 8.9%, whereas removing RETA from DELTA, effectively rendering it a regular timing analysis tool, increases its analysis time by 27%.

翻译：我们提出RETA（相对时序分析），一种差分时序分析技术，用于验证软件更新对嵌入式系统执行时间的影响。时序分析在计算上开销高昂且劳动密集，而软件更新使得从头重复分析成为资源和时间的浪费，因为其影响本质上是局部的。为确定该边界，RETA采用切片程序识别所有相关代码段，并通过语句分类确定如何分析每一行代码。我们将RETA子集适配集成到工业级时序分析工具aiT中，并在名为DELTA的工具中实现完整方案。基于标准基准测试与来自官方仓库的真实代码更新，我们通过分析更新前后的最坏情况执行时间（WCET）来测试精度，将测量结果与未修改的aiT及嵌入式硬件实际执行结果进行对比。DELTA返回的WCET信息范围从与真实硬件WCET完全一致到新版本测量WCET的148%。在相同基准测试下，未修改的aiT估算值为实际执行的112%和149%；因此即使DELTA给出悲观结果，aiT这类工业级工具也无法表现更优。关键的是，我们证明RETA使aiT分析时间减少45%，内存消耗降低8.9%；而从DELTA中移除RETA（使其退化为常规时序分析工具）会增加27%的分析时间。