Abstract
Existing research has shown that developers will use StackOverflow to answer programming questions: but what draws them to one particular answer over any other? The choice of answer they select can mean the difference between a secure application and insecure one, as the quality of supposedly secure answers can vary. Prior work has studied people posting on Stack Overflow—a two-way communication between the original poster and the Stack Overflow community. Instead, we study the situation of one-way communication, where people only read a Stack Overflow thread without being actively involved in it, sometimes long after a thread has closed. We report on a mixed-method study including a controlled between-groups experiment and qualitative analysis of participants' rationale (N=1188), investigating whether explanation detail, answer scoring, accepted answer marks, as well as the security of the code snippet itself affect the answers participants accept. Our findings indicate that explanation detail affects what answers participants reading a thread select (p<0.01), while answer score and acceptance do not (p>0.05)—the inverse of what research has shown for those asking and answering questions. The qualitative analysis of participants' rationale further explains how several cognitive biases underpin these findings. Correspondence bias, in particular, plays an important role in instilling readers with a false sense of confidence in an answer through the way it looks, regardless of whether it works, is secure, or if the community agrees with it. As a result, we argue that StackOverflow's use as a knowledge base by people not actively involved in threads'when there is only one-way-communication—may inadvertently contribute to the spread of insecure code, as the community's voting mechanisms hold little power to deter them from answers.
Original language | English |
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Pages (from-to) | 364-376 |
Number of pages | 18 |
Journal | IEEE Transactions on Software Engineering |
Volume | 48 |
Issue number | 2 |
Early online date | 20 Apr 2020 |
DOIs | |
Publication status | Published - 1 Feb 2022 |
Externally published | Yes |
Keywords
- Software security
- Stack Overflow
- Human Factors
- Rationale