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Predictive Modeling: 15th COW workshop
I was at a very interesting workshop on Predictive Modelling and Search Based Software Engineering on Monday/Tuesday this week, and I am going to say something about the talks that interested me. The talks were recorded, and the videos will appear on the website in a few weeks. The CREST Open Workshop (COW) runs roughly once a month and the group leader, Mark Harman, is always on the lookout for speakers, do let him know if you are in the area.
- Tim Menzies talked about how models built from one data set did well on that dataset but often not nearly as well on another (i.e., local vs global applicability of models). Academics papers usually fail to point out that any results might not be applicable outside the limited domain examined, in fact they often give the impression of being generally applicable.
Me: Industry likes global solutions because it makes life simpler and because local data is often not available. It is a serious problem if, for existing methods, data on one part of a companies’ software development activity is of limited use in predicting something about a different development activity in the same company and completely useless at predicting things at a different company.
- Yuriy Brun talked about something that is so obviously a good idea, it is hard to believe that it had not been done years ago. The idea is to have your development environment be aware of what changes other software developers have made to their local copies of source files you also have checked out from version control. You are warned as soon your local copy conflicts with somebody else’s local copy, i.e., a conflict would occur if you both check in your local copy to the central repository. This warning has the potential to save lots of time by having developers talk to each about resolving the conflict before doing any more work that depends on the conflicting change.
Crystal is a plug-in for Eclipse that implements this functionality, and Visual Studio support is expected in a couple of releases time.
I have previously written about how multi-core processors will change software development tools, and I think this idea falls into that category.
- Martin Shepperd presented a very worrying finding. An analysis of the results published in 18 papers dealing with fault prediction found that the best predictor (over 60%) of agreement between results in different papers was co-authorship. That is, when somebody co-authored a paper with another person, any other papers they published were more likely to agree with other results published by that person than with results published by somebody they had not co-authored a paper with. This suggests that each separate group of authors is doing something different that significantly affects their results; this might be differences in software packages being used, differences in configuration options or tuning parameters, so something else.
It might be expected that agreement between results would depend on the techniques used, but Shepperd et al’s analysis found this kind of dependency to be very small.
An effect is occurring that is not documented in the published papers; this is not how things are supposed to be. There was lots of interest in obtaining the raw data to replicate the analysis.
- Camilo Fitzgerald talked about predicting various kinds of feature request ‘failures’ and presented initial results based on data mined from various open source projects; possible ‘failures’ included a new feature being added and later removed and significant delay (e.g., 1 year) in implementing a requested feature. I have previously written about empirical software engineering only being a few years old and this research is a great example of how whole new areas of research are being opened up by the availability of huge amounts of data on open source projects.
One hint for PhD students: It is no good doing very interesting work if you don’t keep your web page up to date, so people can find out more about it
I talked to people who found other presentations very interesting. They might have failed to catch my eye because my interest or knowledge of the subject is low or I did not understand their presentation (a few gave no background or rationale and almost instantly lost me); sometimes the talks during coffee were much more informative.
What I know of Dennis Ritchie’s involvement with C
News that Dennis Ritchie died last weekend surfaced today. This private man was involved in many ground breaking developments; I know something about one of the languages he designed, C, so I will write about that. Ritchie has written about the development of C language.
Like many language designers the book he wrote “The C Programming Language” (coauthored with Brian Kernighan in 1978) was the definitive reference for users; universally known as K&R. The rapid growth in C’s popularity led to lots of compilers being written, exposing the multiple ways it was possible to interpret some of the wording in K&R.
In 1983 ANSI set up a committee, X3J11, to create a standard for C. With one exception Ritchie was happy to keep out of the fray of standardization; on only one occasion did he feel strongly enough to step in and express an opinion and the noalias keyword disappeared from the draft (the restrict keyword surfaced in C99 as a different kind of beast).
A major contribution to the success of the C Standard was the publication of an “ANSI Standard” version of K&R (there was a red “ANSI C” stamp on the front cover and the text made use of updated constructs like function prototypes and enumeration types), its second edition in 1988. Fans of the C Standard could, and did, claim that K&R C and ANSI C were the same language (anybody using the original K&R was clearly not keeping up with the times).
Ritchie publicly admitted to making one mistake in the design of C. He thinks that the precedence of the & and | binary operators should have been greater than the == operator. I can see his point, but an experiment I ran a few years ago suggested it is amount of experience using a set of operator precedence rules that is the primary contributor to developer knowledge of the subject.
Some language designers stick with their language, enhancing it over the years (e.g., Stroustrup with C++), while others move on to other languages (e.g., Wirth with Pascal, Modula-2 and Oberon). Ritchie had plenty of other interesting projects to spend his time on and took neither approach. As far as I can tell he made little or no direct contribution to C99. As head of the research department that created Plan 9 he must have had some input to the non-Standard features of their C compiler (e.g., no support for #if and support for unnamed structures).
While the modern C world may not be affected by his passing, his ability to find simple solutions to complicated problems will be a loss to the projects he was currently working on.
Memory capacity and commercial compiler development
When I started out in the compiler business in the 80s many commercial compilers were originally written by one person. A very good person who dedicated himself (I have never heard of a woman doing this) to the job (i.e., minimal social life) could produce a commercially viable product for a non-huge language (e.g., Fortran, Pascal, C, etc and not C++, Ada, etc) in 12-18 months. Companies who decide to develop a compiler in-house tend to use a team of people and take longer because that is how they work, and they don’t want to depend on one person and anyway such a person might not be available to them.
Commercially viable compiler development stayed within the realm of an individual effort until sometime in the early 90s. What put the single individual out of business was the growth in computer memory capacity into the hundreds of megabytes and beyond. Compilers have to be able to run within the limits of developer machines; you won’t sell many compilers that require 100M of memory if most of your customers don’t have machines with 100M+ of memory.
Code optimizers eat memory and this prevented many optimizations that had been known about for years appearing in commercial products. Once the machines used for software development commonly contained 100M+ of memory compiler vendors could start to incorporate these optimizations into their products.
Improvements in processor speed also helped. But developers are usually willing to let the compiler take a long time to optimize the code going into a final build, provided development compiles run at a reasonable speed.
The increase in memory capacity created the opportunity for compilers to improve and when some did improve they made it harder for others to compete. Suddenly an individual had to spend that 12-18 months, plus many more months implementing fancy optimizations; developing a commercially viable compiler outgrew the realm of individual effort.
Some people claim that the open source model was the primary driver in killing off commercial C compiler development. I disagree. My experience of licensing compiler source was that companies preferred a commercial model they were familiar with and reacted strongly against the idea of having to make available any changes they made to the code of an open source program. GCC (and recently llvm) succeeded because many talented people contributed fancy optimizations and these could be incorporated because developer machines contained lots of memory. If storage had not dramatically increased gcc would probably not be the market leader it is today.
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