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This special issue of Software Tools for Technology Transfer presents extended versions of two selected papers from the 23rd edition of TACAS, the International Conference on Tools and Algorithms for the Construction and Analysis of Systems that took place in April 2017 in Uppsala. The papers included in this special issue concern various aspects of automated design and formal verification; they therefore contribute to the development of more reliable computer systems. [ABSTRACT FROM AUTHOR]

The Catalyst HD (C‐RAD Positioning AB, Uppsala, Sweden) optical surface imaging (OSI) system is able to manage interfractional patient positioning, intrafractional motion monitoring, and non‐contact respiratory gating without x‐ray exposure for radiation therapy. In recent years, a novel high‐precision surface registration algorithm for stereotactic radiosurgery (SRS algorithm) has been released. This study aimed to evaluate the technical performance of the OSI system using rigid phantoms, by comparing the conventional and SRS algorithms. To determine the system's technical performance, isocenter displacements were calculated by surface image registration via the OSI system using head, thorax, and pelvis rigid phantoms. The reproducibility of positioning was evaluated by the mean value calculated by repeating the registration 10 times, without moving each phantom. The accuracy of positioning was evaluated by the mean value of the residual error, where the 10 offset values given to each phantom were subtracted from the isocenter displacement values. The stability of motion monitoring was evaluated by measuring isocenter drift during 20 min and averaging it over 10 measurements. For the head phantom, all tests were compared with the mask types and algorithms. As a result, for all sites and both algorithms, the reproducibility, accuracy, and stability for translation and rotation were <0.1 mm and <0.1°, <1.0 mm and <1.0°, and <0.1 mm and <0.1°, respectively. In particular, the SRS algorithm had a small absolute error and standard deviation of calculated isocenter displacement, and a significantly higher reproducibility and accuracy than the conventional algorithm (P < 0.01). There was no difference in the stability between the algorithms (P = 0.0280). The SRS algorithm was found to be suitable for the treatment of rigid body sites with less deformation and small area, such as the head and face. [ABSTRACT FROM AUTHOR]

Introduction: A new method to assess causality of suspected adverse drug reactions, the Liverpool Adverse Drug Reaction Causality Assessment Tool (LCAT), showed high interrater agreement when used by its developers. Our aim was to compare the interrater agreement achieved by LCAT to that achieved by another causality assessment method, the World Health Organization-Uppsala Monitoring Centre system for standardised case causality assessment (WHO-UMC system), in our setting. Methods: Four raters independently assessed adverse drug reaction causality of 48 drug-event pairs, identified during a hospital-based survey. A randomised design ensured that no washout period was required between assessments with the two methods. We compared the methods’ interrater agreement by calculating agreement proportions, kappa statistics, and the intraclass correlation coefficient. We identified potentially problematic questions in the LCAT by comparing raters’ responses to individual questions. Results: Overall unweighted kappa was 0.61 (95% CI 0.43 to 0.80) on the WHO-UMC system and 0.27 (95% CI 0.074 to 0.46) on the LCAT. Pairwise unweighted Cohen kappa ranged from 0.33 to 1.0 on the WHO-UMC system and from 0.094 to 0.71 on the LCAT. The intraclass correlation coefficient was 0.86 (95% CI 0.74 to 0.92) on the WHO-UMC system and 0.61 (95% CI 0.39 to 0.77) on the LCAT. Two LCAT questions were identified as significant points of disagreement. Discussion: We were unable to replicate the high interrater agreement achieved by the LCAT developers and instead found its interrater agreement to be lower than that achieved when using the WHO-UMC system. We identified potential reasons for this and recommend priority areas for improving the LCAT. [ABSTRACT FROM AUTHOR]