Papers about various studies comparing programmer/language performance:
- Haskell vs. Ada vs. C++ vs. Awk vs. ... An Experiment in Software Prototyping Productivity, P. Hudak, Mark P. Jones, Yale University.
- An empirical comparison of C, C++, Java, Perl, Python, Rexx, and Tcl for a search/string-processing program, Lutz Prechelt, Technical Repor t 2000-5
- Lisp as an Alternative to Java, Erann Gat, Winter 2000 ? intelligence
- ICFP 2006 VM in Common Lisp, run-time within 20% of C implementations (but quite a bit shorter) by adding a few declarations.
- Are All Programming Languages The Same?. Blog entry about a chart in "Code Complete" that compares the productivity of working in different languages.
- DNS Message Decoding - A Case Study Comparing Java and Common Lisp by Dave Roberts.
- An Experiment About Static and Dynamic Type Systems Doubts about the positive impact of static type systems on development time.
- A Quantitative Analysis Of Whether Unit Testing Obviates Static Type Checking For Error Detection Evan R. Farrer's Master thesis. (Summary).
- The Empirical Evidence That Types Affect Productivity and Correctness
In summary, the experiences tend to show that with lisp you get faster development times, at least as fast execution times, and less variance amongst developers (so there's less risk in using lisp than other programming languages).
- CLOS efficiency: Instantiation (on the Behavior and Performance of Lisp, Part 2.1) , Didier Verna, EPITA Research and Development Laboratory (LRDE).
- Beating C in Scientific Computing Applications (on the Behavior and Performacne of Lisp, Part 1) , Didier Verna, EPITA Research and Development Laboratory (LRDE).
- When lisp is faster than C, Børge Svingen, Genetic And Evolutionary Computation Conference archive, Proceedings of the 8th annual conference on Genetic and evolutionary computation. PDF
- Novak's Lisp Style and Efficiency.
- teepeedee2 achieves 10k requests/second.
Number crunching: Why you should never, ever, EVER use linked-list in your code again. Just for number crunching. ==> Use (coerce list 'vector).
See benchmark for programs trying to measure the performance of Lisp systems.
In the "program quality" aspect of things:
- Extra, Extra - Read All About It: Nearly All Binary Searches and Mergesorts are Broken.
and inumerous other pitfalls in program written in "normal" programming languages.
That should give a lot of reasons to use CL.
Algorithm and Algorithm Implementation Performance