有效性威胁的像素化世界中的证据俄罗斯方块
Evidence Tetris in the Pixelated World of Validity Threats
AI总结：
针对复杂实验中有效性威胁过多难以全面覆盖的问题，提出应利用关于威胁实际影响的证据来补充直觉，以更好地优先排序有效性威胁。
摘要：
有效的实证研究为科学发现建立信心。幸运的是，如今软件工程研究者在设计研究时考虑有效性威胁，并将其作为出版物的一部分进行讨论已变得很普遍。然而，在涉及人类参与者的复杂实验中，通常存在大量直觉上看似合理的有效性威胁——超出了研究者能够切实覆盖的范围。因此，优先考虑潜在的有效性威胁变得至关重要。我们建议不再仅仅依靠直觉来确定有效性威胁的优先级，并提出关于疑似有效性威胁实际影响的证据应作为直觉的补充。
英文摘要：
Valid empirical studies build confidence in scientific findings. Fortunately, it is now common for software engineering researchers to consider threats to validity when designing their studies and to discuss them as part of their publication. Yet, in complex experiments with human participants, there is often an overwhelming number of intuitively plausible threats to validity -- more than a researcher can feasibly cover. Therefore, prioritizing potential threats to validity becomes crucial. We suggest moving away from relying solely on intuition for prioritizing validity threats, and propose that evidence on the actual impact of suspected threats to validity should complement intuition.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
