While high-level languages come with significant readability and maintainability benefits, their performance remains difficult to predict. For example, programmers may unknowingly use language features inappropriately, which cause their programs to run slower than expected. To address this issue, we introduce feature-specific profiling , a technique that reports performance costs in terms of linguistic constructs. Feature-specific profilers help programmers find expensive uses of specific features of their language. We describe the architecture of a profiler that implements our approach, explain prototypes of the profiler for two languages with different characteristics and implementation strategies, and provide empirical evidence for the approach’s general usefulness as a performance debugging tool.

@article{paperbot306,
  title = {Feature-Specific Profiling},
  author = {Leif Andersen and Vincent St-Amour and Jan Vitek and Matthias Felleisen},
  journal = {ACM Transactions on Programming Languages and Systems},
  volume = {41},
  number = {1},
  year = {2018},
  doi = {10.1145/3275519}
}