The shape of code electricity flow direction


Conditional statements are a fundamental constituent of programs. gas after eating dairy Conditions are driven by the requirements of the problem being solved, e.g., if the water level is below the minimum, then add more water. As the problem being solved gets more complicated, dependencies between subproblems grow, requiring an increasing number of situations to be checked.

A while back I read a paper studying this problem (“What to expect of predicates: An empirical analysis of predicates in real world programs”; Google currently not finding a copy online, grrr, you will have to hassle the first author:, or perhaps it will get added to a list of favorite publications {be nice, they did publish some very interesting data}) it contained a table of numbers and yesterday my analysis of the data revealed a surprising pattern.

What grows with SLOC? Number of global variables and number of dependencies. There are more things available to be checked in larger programs, and an increase in dependencies creates the need to perform more checks. Also, larger programs are likely to contain more special cases, which are likely to involve checking both general and specific values (i.e., more clauses in conditionals); ok, this second sentence is a bit more arm-wavy than the first. The prediction here is that the percentage of global variables appearing in conditions increases with SLOC.

• I no longer visit libraries, which are becoming coffee shops+wifi hot-spots where people who have librarian in their job title, hot desk; books, they are around here somewhere. I used to regularly visit libraries, particularly while working on my C book. No libraries have so far needed to be visited, for the writing of my evidence-based software engineering book,

• many old manuals, reports, books and magazines became freely available for download, via sites like the Internet Archive, Bitsavers and the Defense Technical Information Center; for second hand books there is AbeBooks. gas station car wash Site like Research Gate, Semantic Scholar and Google Scholar are fantastic sources for more recent work; for new books there is Amazon,

• No major new languages. These require major new hardware ecosystems; in the smartphone market Android used Java and iOS made use of existing languages. There were the usual selection of fashion/vanity driven wannabes, e.g., Julia, Rust, and Go. gas zone The R language started to get noticed, but it has been around since 1995, and Python looks set to eventually kill it off,

The early computers were essentially sold as bare metal, with the customer having to write all the software. Having to write all the software was expensive, time-consuming, and created a barrier to more companies using computers (i.e., it was limiting sales). r gasquet The amount of software that came bundled with a new computer grew over time; the following plot ( code+data) shows the amount of code (thousands of instructions) bundled with various IBM computers up to 1968 (an anti-trust case eventually prevented IBM bundling software with its computers):

A platform is an ecosystem which is primarily controlled by one vendor; Microsoft Windows is the poster child for software ecosystems. Over the years Microsoft has added more and more functionality to Windows, and I don’t know enough to suggest the date when substantial Windows programs substantially depended on third-party code; certainly small apps may be mostly Windows code. The Windows GUI certainly ties developers very closely to a Windows way of doing things (I have had many people tell me that porting to a non-Windows GUI was a lot of work, but then this statement seems to be generally true of porting between different GUIs).

The rise of open source has made it viable for substantial language ecosystems to flower, or rather substantial package ecosystems, with each based around a particular language. For practical purposes, language choice is now about the quality and quantity of their ecosystem. electricity and magnetism study guide 5th grade The dedicated followers of fashion like to tell everybody about the wonders of Go or Rust (in fashion when I wrote this post), but without a substantial package ecosystem, no language stands a chance of being widely used over the long term.

Will a major new software ecosystem come into being in the future? Major software ecosystems tend to be hardware driven; is hardware development now basically done, or should we expect something major to come along? A major hardware change requires a major new market to conquer. The smartphone has conquered a large percentage of the world’s population; there is no larger market left to conquer. Now, it’s about filling in the gaps, i.e., lots of niche markets that are still waiting to be exploited.

In practice commercial data does not seem to be that hard to get hold of. At least for academics in business schools, and I have not experienced problems gaining access to commercial data (but it is very hard finding a company willing to allow me to make an anonymised version of its data public). There are many evidence-based papers published using confidential data (i.e., data that cannot be made public).

In the academic world the software side of computing often has a strong association is mathematics departments (I know that in some universities it is in engineering). I have had several researchers tell me that it would raise eyebrows, if they started doing more people oriented research, because this kind of research is viewed as being the purview of other departments.

Baffled looks are common, when I talk to software engineering academics. electricity in the 1920s They are baffled by the idea that it is possible to run experiments in software engineering, and they are baffled by the idea of evidence-based theories. I am still struggling to understand the mindset that produces the arguments they make against the possibility of experiments and evidence being useful.