Bioinformatics Zen

What's the point of writing good scientific software?

// Fri February 8 2013

Software written by academics has a reputation of being poorer quality than that of software written by professional software developers. This poorer quality can be quantified by a lack of documentation, a non-intuitive interface, or bug-ridden with a tendency to crash.

I assume, since you're reading a bioinformatics blog, that you've experienced trying to use code that you can't download, won't compile, won't run on your system, isn't documented, won't work on your data, or just crashes without explanation. Speaking from personal experience this can be frustrating in the extreme. Consequently there are efforts to increase the quality of academic software including journals focused on publishing software with minimum standards and workshops to help academics write better software.

What then does good quality software look like? I think this includes both unit and integration tests to ensure the software works as expected. Revision control to ensure that bugs can be removed by reverting to the last working version. Continuous integration to make sure that software always passes tests when new changes are committed. Finally documentation of available options with examples helps users understand how to use the software. A question I have been recently asking myself however is what's the point of spending the extra time to create better software?

Pubmed shows the number of articles published by two journals, 'BMC Bioinformatics' and 'Bioinformatics,' containing the word 'software' in the title or abstract is ~350 each year. I think this may an underestimate though since other journals also publish software articles and the terms 'pipeline', 'package' and 'system' may also be used instead of 'software.'

Considering around 1700 bioinformatics software articles published in the last five years, this represents a significant corpus. This leads me to the question what is the point of writing good quality software if the chances are small that anyone will read about, or download it? For every highly cited tool, such as SAM Tools or PAML, there are likely many other tools which are never downloaded or used. Does it make sense to invest the extra time in the documentation and interface if there is a good chance that no one else will ever use it?

Let me illustrate with a concrete example. I'm a post-doc working in microbial genomics. I found that I had to write various scripts to help with the finishing of my genome and the subsequent upload to GenBank. I have previously believed that converting any code you've created into a open-source library benefits the community and prevents reinvention of the wheel. Therefore I converted my scripts first into a tool called scaffolder and then a subsequent tool called genomer. Both of these are tested with integration and unit tests, and I create documentation and screencasts.

I have however started to realise that perhaps something I thought would be very useful may be of little interest to anyone else. Furthermore the effort I have put into testing and documentation may not have been the best use of my time if no one but I will use it. As my time as a post doc is limited, the extra time effort spent on improving these tools could have instead have been spent elsewhere. Would it have been better if I have just completed the minimum to get them published then moved on to another project?

I have begun to think now that the most important thing when writing software is to write the usable minimum. If then the tool becomes popular and other people begin to use it, then I should I work on the documentation and interface. This will then ensure then I make the best use of my time without sinking effort onto something that could have little interest. Given the choice I like writing robust, well documented software but this takes extra time and in a competitive academic job market I feel like this is a luxury.