Googling a bit for stuff by Sommerville, I come across a pie chart for “distribution of maintenance effort” which has all the hallmarks of a software engineering meme: old study, derived from a survey (such self-reports are often unreliable owing to selection bias and measurement bias), but still held to be current and generally applicable and cited in many books even though more recent research casts doubt on it.
Here’s a neat quote from the linked paper (LST is the old study):
(Possibly) participants in the survey from which LST was derived simply did not have adequate data to respond to the survey. The participating software maintenance managers were asked whether their response to each question was based on reasonably accurate data, minimal data, or no data. In the case of the LST question, 49.3% stated that their answer was based on reasonably accurate data, 37.7% on minimal data, and 8.7% on no data. In fact, we seriously question whether any respondents had ‘‘reasonably accurate data’’ regarding the percentage of effort devoted to the categories of maintenance included in the survey, and most of them may not have had even ‘‘minimal data.’’
I love it that 10% of managers can provide a survey response based on “no data”. :)
I’ve read the paper you refer to, very interesting data indeed. The quote is one of five possible explenations of why the results differ so much, but it certainly is a good possibility.
This post sparked my interest/doubt knob for now. I will question more ‘facts’ in the SE world from now on.
I have based my findings on the presentations now, since I haven’t got the book nearby. You can look them up yourself (download the chapters from the above link).
Chapter 7 says:
Requirements error costs are high so validation is very important
• Fixing a requirements error after delivery may
cost up to 100 times the cost of fixing an
implementation error.
Chapter 21, refers to Software Maintanance, claiming (might need to verify this as well? ;)) :
[Maintanance costs are] Usually greater than development costs (2 to 100 depending on the application).
Because I don’t have the book nearby I cannot tell for certain where it was stated. But I was pretty certain it was stated in that book.
I’m interested in your source for that graph.
Googling a bit for stuff by Sommerville, I come across a pie chart for “distribution of maintenance effort” which has all the hallmarks of a software engineering meme: old study, derived from a survey (such self-reports are often unreliable owing to selection bias and measurement bias), but still held to be current and generally applicable and cited in many books even though more recent research casts doubt on it.
Here’s a neat quote from the linked paper (LST is the old study):
I love it that 10% of managers can provide a survey response based on “no data”. :)
I’ve read the paper you refer to, very interesting data indeed. The quote is one of five possible explenations of why the results differ so much, but it certainly is a good possibility.
This post sparked my interest/doubt knob for now. I will question more ‘facts’ in the SE world from now on.
About sommerville: Sommerville website: http://www.comp.lancs.ac.uk/computing/resources/IanS/
The book I refer to: http://www.comp.lancs.ac.uk/computing/resources/IanS/SE8/index.html
You can download presentations of his chapters here: http://www.comp.lancs.ac.uk/computing/resources/IanS/SE8/Presentations/index.html
I have based my findings on the presentations now, since I haven’t got the book nearby. You can look them up yourself (download the chapters from the above link).
Chapter 7 says:
Chapter 21, refers to Software Maintanance, claiming (might need to verify this as well? ;)) :
Because I don’t have the book nearby I cannot tell for certain where it was stated. But I was pretty certain it was stated in that book.
Far more than 10% of managers do that routinely. The interesting thing is that as many as 10% admitted it.