Timeline for Is the average number of bugs per loc the same for different programming languages?
Current License: CC BY-SA 3.0
9 events
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| Nov 22, 2017 at 20:41 | comment | added | Bevan | I disagree - there were a number of languages in widespread use by 1993 that had rigorous type systems (I studied several of them while doing my Computer Science degree and 1993 was my final year). Perhaps the depth of programming language history is deeper than you think @ian | |
| Nov 22, 2017 at 10:17 | comment | added | Ian | At the time, there were no high level languages (in common usage) with very compact code and little compile time type checking. Hence I don’t think his results are still valid. | |
| Jul 28, 2015 at 8:27 | comment | added | Aryeh Leib Taurog | The quote is either wrong or outdated. In the second edition, it's on page 521: "Industry average experience is about 1 - 25 errors per 1000 lines of code for delivered software. The software has usually been developed using a hodgepodge of techniques." | |
| Aug 12, 2014 at 21:23 | comment | added | Parthian Shot | @RocMartí "errors increase dramatically as the project's size increases" Did he also point out that water is wet? Of course there are errors when things get more complicated. Because every new change has to keep in mind every possible piece that could be affected. Which grows as the project grows. | |
| Mar 26, 2013 at 17:59 | comment | added | GalacticCowboy | I think your edit (Update:) is the core of the problem. Or, as Mark Twain said, there's three kinds of lies: Lies, Damn Lies, and Statistics. | |
| Feb 3, 2013 at 3:08 | history | edited | Bevan | CC BY-SA 3.0 |
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| Feb 3, 2013 at 3:01 | comment | added | Bevan | Which edition of Code Complete do you have @RocMartí? I know that the second edition was a major update. Will have to dig it out and see what it says when I get to work Monday. | |
| Feb 3, 2013 at 0:09 | comment | added | Roc Martí | Don't have a copy of Software Estimation, but in Code Complete McConnel cites Capers Jones "Program Quality and Programmer Productivity" 1977 report as the source of a table of errors per LOC per project size. The point McConnel tries to make is that errors increase dramatically as the project's size increases, and notes that the data are only a "snapsot of the industry" and that "the numbers may bear little resemblance to those for the projects you’ve worked on". I don't really see anything in there that has anything to do with this question. | |
| Feb 2, 2013 at 21:34 | history | answered | Bevan | CC BY-SA 3.0 |