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When studying how software developers perform security tasks, researchers often ask participants to write code. These studies can be challenging because programming can be time-consuming and frustrating. This paper explores whether alternatives to code-writing can yield scientifically valid results while reducing participant stress. We conducted a remote study in which Python programmers completed two encryption tasks using an assigned library by either writing code from scratch, reading existing code and identifying issues, or fixing issues in existing code. We found that the read and fix conditions were less effective than the write condition in revealing security problems with APIs and their documentation, but still provided useful insights. Meanwhile, the read and especially fix conditions generally resulted in more positive participant experiences. Based on these findings, we make preliminary recommendations for how and when researchers might best use all three study design methods; we also recommend future work to further explore the uses and trade-offs of these approaches. 

Abstract The semiconductor tracker (SCT) is one of the tracking systems for charged particles in the ATLAS detector. It consists of 4088 silicon strip sensor modules.During Run 2 (2015–2018) the Large Hadron Collider delivered an integrated luminosity of 156 fb -1 to the ATLAS experiment at a centre-of-mass proton-proton collision energy of 13 TeV. The instantaneous luminosity and pile-up conditions were far in excess of those assumed in the original design of the SCT detector.Due to improvements to the data acquisition system, the SCT operated stably throughout Run 2.It was available for 99.9% of the integrated luminosity and achieved a data-quality efficiency of 99.85%.Detailed studies have been made of the leakage current in SCT modules and the evolution of the full depletion voltage, which are used to study the impact of radiation damage to the modules.