Calculating WCET Estimates from Timed Traces

© The Author(s) 2015. This article is published with open access at Springerlink.comReal-time systems engineers face a daunting duty: They must ensure that each task in their system can always meet its deadline. To analyse schedulability they must know the worst-case execution time (WCET) of each task. However, determining exact WCETs is practically infeasible in cost-constrained industrial settings involving real-life code and COTS hardware. Static analysis tools that could yield sufficiently tight WCET bounds are often unavailable. As a result, interest in portable analysis approaches like measurement-based timing analysis (MBTA) is growing. We present an approach based on integer linear programming (ILP) for calculating a WCET estimate from a given database of timed execution traces. Unlike previous work, our method specifically aims at reducing overestimation, by means of an automatic classification of code executions into scenarios with differing worst-case behaviour. To ease the integration into existing analysis tool chains, our method is based on the implicit path enumeration technique (IPET). It can thus reuse flow facts from other analysis tools and produces ILP problems that can be solved by off-the-shelf solvers.Peer reviewe

Enhanced genome assembly and a new official gene set for Tribolium castaneum

Background. The red flour beetle Tribolium castaneum has emerged as an important model organism for the study of gene function in development and physiology, for ecological and evolutionary genomics, for pest control and a plethora of other topics. RNA interference (RNAi), transgenesis and genome editing are well established and the resources for genome-wide RNAi screening have become available in this model. All these techniques depend on a high quality genome assembly and precise gene models. However, the first version of the genome assembly was generated by Sanger sequencing, and with a small set of RNA sequence data limiting annotation quality. Results. Here, we present an improved genome assembly (Tcas5.2) and an enhanced genome annotation resulting in a new official gene set (OGS3) for Tribolium castaneum, which significantly increase the quality of the genomic resources. By adding large-distance jumping library DNA sequencing to join scaffolds and fill small gaps, the gaps in the genome assembly were reduced and the N50 increased to 4753kbp. The precision of the gene models was enhanced by the use of a large body of RNA-Seq reads of different life history stages and tissue types, leading to the discovery of 1452 novel gene sequences. We also added new features such as alternative splicing, well defined UTRs and microRNA target predictions. For quality control, 399 gene models were evaluated by manual inspection. The current gene set was submitted to Genbank and accepted as a RefSeq genome by NCBI. Conclusions. The new genome assembly (Tcas5.2) and the official gene set (OGS3) provide enhanced genomic resources for genetic work in Tribolium castaneum. The much improved information on transcription start sites supports transgenic and gene editing approaches. Further, novel types of information such as splice variants and microRNA target genes open additional possibilities for analysis