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Archive for December, 2009

The changing shape of code in the next decade

December 29th, 2009 No comments

I think there are two forces that will have a major impact on the shape of code in the next decade:

  • Asian developers. China and India each have a population that is more than twice as large as Europe and the US combined, and software development has been kick started in these countries by a significant amount of IT out sourcing. I have one comparative data point for software developers who might be of the hacker ilk. A discussion of my C book on a Chinese blog resulted in a download volume that was 50% of the size of the one that occurred when the book appeared as a news item on Slashdot.
  • Scripting languages. Software is written to solve a problem and there are only so many packaged applications (COTS or bespoke) that can profitably be supported. Scripting languages are generally designed to operate within one application domain, e.g., Bash, numerical analysis languages such as R and graphical plotting languages such as gnuplot.

While markup languages are very widely used they tend to be read and written by programs not people.

Having to read code containing non-alphabetic characters is always a shock the first time. Simply having to compare two sequences of symbols for equality is hard work. My first experience of having to do this in real time was checking train station names once I had traveled outside central Tokyo and the names were no longer also given in Romaji.

其中,ul分别是bootmap_size(bit map的size),start_pfn(开始的页框)
                                max_low_pfn(被内核直接映射的最后一个页框的页框号) ;

Developers based in China and India have many different cultural conventions compared to the West (and each other) and I suspect that these will effect the code they write (my favorite potential effect involves treating time vertically rather than horizontally). Many coding conventions used by a given programming language community exist because of the habits adopted by early users of that language, these being passed on to subsequent users. How many Chinese and Indian developers are being taught to use these conventions, are the influential teachers spreading different conventions? I don’t have a problem with different conventions being adopted other than that having different communities using different conventions increases the cost for one community to adopt another community’s source.

Programs written in a scripting language tend to be much shorter (often being contained within a single file) and make use of much more application knowledge than programs written in general purpose languages. Their data flow tends to be relatively simple (e.g., some values are read/calculated and passed to a function that has some external effect), while the relative complexity of the control flow seems to depend on the language (I only have a few data points for both assertions).

Because of their specialized nature most scripting languages will not have enough users to support any kind of third party support tool market, e.g., testing tools. Does this mean that programs written in a scripting language will contain proportionally more faults? Perhaps their small size means that only a small number of execution paths are possible and these are quickly exercised by everyday usage (I don’t know of any research on this topic).

The Met Office ‘climategate’ Perl code

December 25th, 2009 3 comments

In response to the Climategate goings on the UK Meteorological Office has released a subset of its land surface climate station records and some code to process it. The code consists of 397 lines of Perl (station_gridder.perl and make_global_average_ts_ascii.perl).

At various times I have been asked to suggest which part of an application’s or product’s source code should be made available to a third party. The third party may have been interested in evaluating the quality, getting a feel for the complexity or felt that they ought at least be able to say they had seen some code. In these situations there is always a trade-off between impressing the customer (e.g., well structured code containing lots of comments) and not revealing too much (e.g., impenetrable code with no comments).

Have the Met Office released the code they have used over a period of time or have they release newly written code?

The source does not have the characteristics often seen in well worn, ‘old’, code. There is no revision history (that may be due to poor programming practices or may have been stripped off prior to release; I discuss pretty printing below), the visual layout is generally consistent (this may be because the same small group of people have worked on it over time), there are no obvious hacks used to get around previous design decisions that have changed and unscientifically it just feels to me like newly written code.

Was the original code written in another language (e.g., Fortran), perhaps as part of a larger program and been rewritten in Perl?

The code does not have a Fortran ‘accent’ to it. The code was written by people who are fluent in Perl; perhaps they do not know Fortran very well and were given time to craft something presentable, hence no Fortran accent.

Why have I been referring to the code authors, plural, when writing 397 lines is well within the capabilities of a competent developer working for a day (I bet the authors spent longer in meetings about this code than actually writing it)? Developers tend to have very fixed habits when it comes to bracketing statements with curly braces, there are those who always put the open brace at the end of the line and those who always put it on a newline. The Met Office code contains both usages, sometimes within the same subroutine. Also the use of whitespace around punctuators and operators does not follow a consistent pattern, which for me rules out the use of an automated pretty printer and kind of implies more than one person doing the editing. And why are some variables names capitalized and other not (the names in subroutine read_station are all lower case while the names in the surrounding subroutines are mostly upper case)? More than one author is the simplest answer.

One Perl usage caught my eye, the construct unless is rarely used and often recommended against. Without a lot more code being available for analysis there are no obviously conclusions to draw from this usage (apart from it being an indicator of somebody who knows Perl well, most mainstream languages do not support this construct and developers have to use a ‘positive’ construct containing a negated condition rather than a ‘negative’ construct containing a positive condition).

Compiler writing in the next decade

December 22nd, 2009 No comments

What will be the big issues in compiler writing in the next decade? Compilers sit between languages and hardware, with the hardware side usually providing the economic incentive.

Before we set off to follow the money, what about the side that developers prefer to talk about. The last decade has not seen any convergence to a very small number of commonly used languages, if anything there seems to have been a divergence with more languages in widespread use. I will not attempt to predict whether there will be a new (in the sense of previously limited to a few research projects) concept that is widely integrated and used in many languages (i.e., the integrating of object oriented features into languages in the 90s).

Where is hardware going?

  • Moore’s law stops being followed. Moore’s law is an economic one that has a number of technical consequences (e.g., less power consumed and until recently increasing clock rates). Will the x86 architecture evolution dramatically slow down once processor manufacturers are no longer able to cram more transistors onto the same amount of chip real estate? Perhaps processor designers will start looking to compiler writers to suggest functionality that could be made use of by compilers to generate more optimal code. To date my experience of processor designers is that they look to Moore’s law to get a ‘free’ performance boost.

    There are a number of things a compiler code tell the processor, such as when a read or write to a cache line is the last one that will occur for a long time (enabling that line to be moved to the top of the reuse list).

  • Not plugged into the mains. When I made a living writing optimizers the only two optimizations choices were code size and performance. There are a surprising number of functional areas in which a compiler, given processor support, can potentially generate code that consumes less power. More on this issue in a later post.
  • More than one processor. Figuring out how to distribute a program across multiple, loosely coupled, processors remains a difficult research topic. If anybody ever comes up with a solution to this problem it might make more commercial sense for them to keep it secret, selling a compiling service rather than selling compilers.
  • Application Specific Instruction-set Processors. Most processors in embedded systems only ever run a single program. The idea of each program being executed on a processor optimized to its requirements sounds seductive. At the moment the economics are such that it is cheaper to take an existing, very low cost, processor and shoe-horn the application onto it. If the economics change the compiler used for each processor is likely to be automatically generated.

Enough of the hardware, this site is supposed to be about code:

  • New implementation techniques. These include GLR parsing and genetic algorithms to improve the generated code quality. The general availability of development machines containing more than 4G of memory will make it worthwhile for compiler writers to implement more whole program optimizations (which are currently being hemmed in by storage limits)
  • gcc will continue its rise to world domination. The main force at work here is not the quality of gcc but the disappearance of the competition. Compiler writing is not a big bucks business and compiler companies are regularly bought up by much larger hardware outfits looking to gain some edge. A few years go by, plans change, the compiler group are not making enough profit to warrant the time being spent on them by upper management and they are closed down. One less compiler vendor and a bunch of developers are forced to migrate to another compiler, which may or may not be gcc.
  • Figuring out what the developer meant to write based on what they actually wrote, and some mental model of software developers, is my own research interest. This is somewhat leading edge stuff, in other words nothing major has been achieved so far. Knowledge of developer intent looks like it will open the door to whole classes of new optimization techniques.

Parsing Fortran 95

December 20th, 2009 No comments

I have been looking at doing some dimensional analysis of the Climategate code and so needed a Fortran parser.

The last time I used Fortran in anger the modern compilers were claiming conformance to the 1977 standard and since then we have had Fortran 90 (with a minor revision in 95) and Fortran 03. I decided to take the opportunity to learn something about the new features by writing a Fortran parser that did not require a symbol table.

The Eli project had a Fortran 90 grammar that was close to having a form acceptable to bison and a few hours editing and debugging got me a grammar containing 6 shift/reduce conflicts and 1 reduce/reduce conflict. These conflicts looked like they could all be handled using glr parsing. The grammar contained 922 productions, somewhat large but I was only interested in actively making use of parts of it.

For my lexer I planned to cut and paste an existing C/C++/Java lexer I have used for many projects. Now this sounds like a fundamental mistake, these languages treat whitespace as being significant while Fortran does not. This important difference is illustrated by the well known situation where a Fortran lexer needs to lookahead in the character stream to decide whether the next token is the keyword do or the identifier do5i (if 1 is followed by a comma it must be a keyword):

      do 5 i = 1 , 10
      do 5 i = 1 . 10        ! assign 1.10 to do5i
5     continue

In my experience developers don’t break up literals or identifier names with whitespace and so I planned to mostly ignore the whitespace issue (it would simplify things if some adjacent keywords were merged to create a single keyword).

In Fortran the I/O is specified in the language syntax while in C like languages it is a runtime library call involving a string whose contents are interpreted at runtime. I decided to to ignore I/O statements by skipping to the end of line (Fortran is line oriented).

Then the number of keywords hit me, around 190. Even with the simplifications I had made writing a Fortran lexer looked like it would be a lot of work; some of the keywords only had this status when followed by a = and I kept uncovering new issues. Cutting and pasting somebody else’s lexer would probably also involve a lot of work.

I went back and looked at some of the Fortran front ends I had found on the Internet. The GNU Fortran front-end was a huge beast and would need serious cutting back to be of use. moware was written in Fortran and used the traditional six character abbreviated names seen in ‘old-style’ Fortran source and not a lot of commenting. The Eli project seemed a lot more interested in the formalism side of things and Fortran was just one of the languages they claimed to support.

The Open Fortran Parser looked very interesting. It was designed to be used as a parsing skeleton that could be used to produce tools that processed source and already contained hooks that output diagnostic output when each language production was reduced during a parse. Tests showed that it did a good job of parsing the source I had, although there was one vendor extension used quiet often (an not documented in their manual). The tool source, in Java, looked straightforward to follow and it was obvious where my code needed to be added. This tool was exactly what I needed :-)

Information content of expressions

December 11th, 2009 No comments

Software developers read source code to obtain information. How might the information content of source code be quantified?

Both of the following functions assign the same value to x and if that is the only information a reader of that code is interested in, then the information content of both assignment statements could be said to be the same.

int foo(void)
{
x = 5;
...
}
 
int bar(void)
{
x = 2 + 3;
...

A reader seeking deeper understanding of the above code would ask why the value 5 is built from two values in bar. One reason might be that the author of the function wanted to explicitly call out background information about how the value 5 was derived (this is often done using symbolic names, but the use of literals themselves is sometimes encountered). Perhaps the author of foo did not see the need to expose this information or perhaps the shared value is purely coincidental.

If the two representations denote the same quantity doesn’t the second have a greater information content for a reader seeking deeper understanding?

In the following example:

... x + y & z ...
 
...
 
... num_red + num_white & lower_bits ...

an experienced developer with a knowledge of English is likely to interpret the expression as adding the number of occurrences of two quantities and using bit-wise AND to extract the lower bits. For some readers the second expression has a higher information content. Would use of the names number_of_red further increase the information content?

In the following example the first expression has not added any information that was not already present in the first expression above (except perhaps that the author was not certain of the precedence or perhaps did not expect subsequent readers to be certain).

... ( x + y ) & z ...
 
...
 
... x + ( y & z ) ...

The second expression uses parenthesis to achieve an operand/operator binding that is different from the default. Has this changed the information content of the expression?

There is experimental evidence that developers extract information from the names of variables to help them make decisions about operator precedence. To me the name all_32_bits_one suggests a sequence of bits and I would expect such a representation to be associated with the bit-wise AND operator, not binary plus. With no knowledge of the relative precedence of the two operators in the following expression the name of the middle operand would cause me to misinterpret the code. Does this change the information content of the expression? Does knowledge of the experimental evidence and the correct operator precedence change the information content (i.e., there is a potential fault in the code because the author may have assumed the incorrect precedence)?

... num_red + all_32_bits_one & sign_bit ...

There is experimental evidence that people use the amount of whitespace appearing between operands and their operators to visually highlight operator precedence

The relative quantities of whitespace used in the following two expressions appear to tell very different stories. Do the two expressions have a different information content?

... x  +  y & z ...
 
...
 
... x + y  &  z ...

The idea of measuring the information content of source code is very enticing. However, an accurate measure requires knowledge of the kind of information a reader is trying to obtain and of information that already exists in their brain.

Another question is the easy with which information can be extracted from code. Something that might be labeled as readability, except that readability has connotations of there being an abundant supply of information to extract.

Christmas books for 2009

December 7th, 2009 No comments

I thought it would be useful to list the books that gripped me one way or another this year (and may be last year since I don’t usually track such things closely); perhaps they will give you some ideas to add to your Christmas present wish list (please make your own suggestions in the Comments). Most of the books were published a few years ago, I maintain piles of books ordered by when I plan to read them and books migrate between piles until eventually read. Looking at the list I don’t seem to have read many good books this year, perhaps I am spending too much time reading blogs.

These books contain plenty of facts backed up by numbers and an analytic approach and are ordered by physical size.

The New Science of Strong Materials by J. E. Gordon. Ideal for train journeys since it is a small book that can be read in small chunks and is not too taxing. Offers lots of insight into those properties of various materials that are needed to build things (‘new’ here means postwar).

Europe at War 1939-1945 by Norman Davies. A fascinating analysis of the war from a numbers perspective. It is hard to escape the conclusion that in the grand scheme of things us plucky Brits made a rather small contribution, although subsequent Hollywood output has suggested otherwise. Also a contender for a train book.

Japanese English language and culture contact by James Stanlaw. If you are into Japanese culture you will love this, otherwise avoid.

Evolutionary Dynamics by Martin A. Nowak. For the more mathematical folk and plenty of thought power needed. Some very powerful general results from simple processes.

Analytic Combinatorics by Philippe Flajolet and Robert Sedgewick. Probably the toughest mathematical book I have kept at (yet to get close to the end) in a few years. If number sequences fascinate you then give it a try (a pdf is available).

Probability and Computing by Michael Mitzenmacher and Eli Upfal. For the more mathematical folk and plenty of thought power needed. Don’t let the density of Theorems put you off, the approach is broad brush. Plenty of interesting results with applications to solving problems using algorithms containing a randomizing component.

Network Algorithmics by George Varghese. A real hackers book. Not so much a book about algorithms used to solve networking problems but a book about making engineering trade-offs and using every ounce of computing functionality to solve problems having severe resource and real-time constraints.

Virtual Machines by James E. Smith and Ravi Nair. Everything you every wanted to know about virtual machines and more.

Biological Psychology by James W. Kalat. This might be a coffee table book for scientists. Great illustrations, concise explanations, the nuts and bolts of how our bodies runs at the protein/DNA level.