What makes a good code example?: A study of programming Q&A in StackOverflow
By Seyed Mehdi Nasehi, Jonathan Sillito, Frank Maurer, Chris Burns. International Conference on Smart Multimedia, 2012
351 citations recorded by the source corpus.
Subfields: Computer Science Applications, Information Systems
View Paper: https://www.semanticscholar.org/paper/b8f9539d145638ac93957da4f653e238a4e9d413
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Science Applications
- Jaroslav M. Fowkes
- Daniel S. Weld
- Christoffer Rosen
- Emad Shihab
- Charles Sutton
- Miltiadis Allamanis
- Premkumar T. Devanbu
- Michael Pradel
In Information Systems
- Jaroslav M. Fowkes
- Charles Sutton
- Ziyu Yao
- Huan Sun
- Shing-Chi Cheung
- Lu Zhang
- Foutse Khomh
- Daniel S. Weld
Citations in the corpus
- What are mobile developers asking about? A large scale study using stack overflow (2015, background): “Nasehi et al. (2012) investigate what makes an effective code example through a qualitative analysis of Stack Overflow posts.”
- An Empirical Study of C++ Vulnerabilities in Crowd-Sourced Code Examples (2019, background): “Sharing code snippets and code examples is also a common learning practice [6].”
- Parameter-free probabilistic API mining across GitHub (2015, background): “Although previous work has explored what it means for a single API example to be useful [42, 34], there seems to be much less work about what it means for a set of examples to be useful, and how well example directories in popular projects reflect all of the actual common uses of an API.”
- StaQC: A Systematically Mined Question-Code Dataset from Stack Overflow (2018, methodology): “We follow [12, 13, 32] to categorize SO questions into 5 classes but only focus on the “how-to-do-it” type (Section 2).”
- Parameter-Free Probabilistic API Mining at GitHub Scale (2015, background): “Although previous work has explored what it means for a single API example to be useful [38, 30], there seems to be”
- An empirical study on TensorFlow program bugs (2018, result): “…of our dataset is similar to other existing studies that require manual inspection, e.g., Jin et al. conducted a study of performance bugs and inspected 109 performance bugs [19], and Nasehi et al. conducted a study on what makes a good code example and analyzed 163 StackOver ow QA pages [26].”