Many practitioners and academics believe in a delayed issue effect (DIE); i.e. the longer an issue lingers in the system, the more effort it requires to resolve. This belief is often used to justify major investments in new development processes that promise to retire more issues sooner. This paper tests for the delayed issue effect in 171 software projects conducted around the world in the period from 2006--2014. To the best of our knowledge, this is the largest study yet published on this effect. We found no evidence for the delayed issue effect; i.e. the effort to resolve issues in a later phase was not consistently or substantially greater than when issues were resolved soon after their introduction. This paper documents the above study and explores reasons for this mismatch between this common rule of thumb and empirical data. In summary, DIE is not some constant across all projects. Rather, DIE might be an historical relic that occurs intermittently only in certain kinds of projects. This is a significant result since it predicts that new development processes that promise to faster retire more issues will not have a guaranteed return on investment (depending on the context where applied), and that a long-held truth in software engineering should not be considered a global truism.
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I read some of the more questionable parts of the second edition just now, and while I think there are a lot of things to criticize in it, I suspect that it's just rose-tinted hindsight, or ignorance, that made me not object to them in the first edition; I'm pretty sure most of these problems were already there:
- All the time wasted on the dumb "construction" analogy.
- The total lack of attention to open-source software, possibly because he was misled by his own "construction" analogy. There's no such thing as a freely redistributable cabinet that's extra reliable because your house shares it with the local nuclear reactor, or a rotten floor joist you can't fix without…
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negotiating a source license. (He does discuss buying libraries, just as you can buy cabinets instead of building them.) Though this was surely also lacking in the first edition, it was a more forgivable oversight in 01994.
- Very little attention given to automated testing; we don't get to "developer testing" until chapter 22, and even that's mostly about manual testing, though there are a few offhand remarks in §4.4 and §9.4 about unit testing and test-first programming, with no explanation of what that means. Even when he tries to explain "test-first programming" in §22.2, there's no hint that we're talking about automated testing. And we finally see mentions of "test code" and "JUnit" in §22.4, and then §22.5 and §22.6 have information about actual automated testing, though without any actual test code. The advice on test-case design is still excellent.
- Also, very little about source control. I know this was a deficiency in the first edition because I remember the revelation of learning about RCS a couple of years after I read it. I think it actually got better in the second edition; there's a little "Version Control" section in §30.2 which refers you to §28.2, "Configuration Management", which talks a little bit about the problem but doesn't mention Subversion (first released October 02000), CVS (01990), RCS (01982), SCCS (01973), or even Visual SourceSafe (01994). Instead, it mostly describes implementing similar processes manually, through bureaucracy, because this is the "Managing Construction" chapter. But there is technically half a page on p. 668 singing the praises of version-control software, calling it "indispensable on team projects", which manages to not mention a single program you could use for it. An understandable oversight in 01994, unforgivable in 02004, but again, incompetence rather than snake oil.
- Although he pays lip service at the beginning of the book to the independence of project phases and project activities, he often conflates them later, often presuming a quasi-waterfall model (when he isn't outright advocating it), where a requirements-analysis phase is followed by an architecture phase, then a detailed design phase, then a "construction" phase, then a testing phase, and then finally a maintenance phase. This is obviously completely unlike the reality of projects like Microsoft Windows, Emacs, Linux, GCC, and Facebook. When did Facebook mostly move from detailed design to construction? Would it have been a better social-networking website if it had spent a year or two on architecture before beginning "construction"? He does kind of go back and forth on this a lot, though, sometimes advocating more incremental approaches and then contradicting himself a page later.
- Relatedly, he advocates a division of labor where "the architect consumes the requirements; the designer consumes the architecture; and the coder consumes the design." (Traditionally, though he doesn't say this, the QA tester then consumes the code.) This division of labor has been tried many times, and the companies that have tried it have been mostly outcompeted by companies with less dysfunctional divisions of labor; they mostly survive only in niches where they have legally enforceable monopolies, such as DoD cost-plus prime contractors. None of them have been able to produce products of quality comparable to things like Linux, GCC, and Facebook. I think this is the snake-oiliest part of the book.
- Code Complete's table of "Average Cost of Fixing Defects Based on When They're Introduced and Detected", table 3-1, is convincing, compelling, thoroughly footnoted with decades of literature, and completely made up. See https://softwareengineering.stackexchange.com/questions/1637... https://web.archive.org/web/20121101231451/http://blog.secur... https://www.lesswrong.com/posts/4ACmfJkXQxkYacdLt/diseased-d... https://gist.github.com/Morendil/258a523726f187334168f11fc83.... This made-up data is McConnell's major justification for advocating waterfall-like models. More recent research that investigates the question empirically instead of relying on made-up hearsay finds, by contrast, "We found no evidence for the delayed issue effect; i.e., the effort to resolve issues in a later phase was not consistently or substantially greater than when issues were resolved soon after their introduction." https://arxiv.org/pdf/1609.04886 https://agilemodeling.com/essays/costofchange.htm https://buttondown.com/hillelwayne/archive/i-ing-hate-scienc....
- The section about "user interface design" is cringe-inducingly bad. He thinks you can design a good user interface up front without having working software ("The user interface is often specified at requirements time. If it isn't, it should be specified in the software architecture,") rather than incrementally responding to usability feedback from people using a working system. It's a very short section, and that in itself is eyebrow-raising; usability is a central concern of most kinds of software, and one of the most challenging aspects of software. Really, almost everything in most software should be driven ultimately by user experience and grounded out in usability testing. Games, websites, browsers, and even compilers live and die on usability. But McConnell treats it as one minor detail among many.
- The section about the "architecture prerequisite" sounds like it was written by IBM mainframe programmers in 01978, then decorated with some OO and WWW jargon. Yes, clearly the architecture should "describe the major files and table designs to be used". That makes sense. Yes, "Input/output (...) is another area that deserves attention in the architecture. The architecture should specify a read-ahead, read-behind, or just-in-time reading scheme." I mean, seriously? Note that words like "client", "server", "tier", "cache", "protocol", "network", "message", "queue", and even "process" (as in a running instance of a program) are completely missing here. It's not that he uses different terms for them; he just doesn't talk about them at all, using any words.
- He tries to discuss "fault tolerance" with a totally nonsensical example "the square root of a number", necessarily making complete hash of the topic as a result. He doesn't mention any of the techniques that actually work for achieving fault-tolerance, such as statelessness, idempotence, the end-to-end principle, transactions, journaling, fail-stopness, checksums, disk mirroring, hardware trimodular redundancy, watchdog timers, ECC, anomaly detection, network timeouts, monitoring, alarms, etc. The only exception is that he sort of mentions granular restarts. I'm restricting myself to techniques that were well-known when he wrote the first edition of the book here, excluding things like Paxos, eventual consistency, and Merkle graphs.
- There are a lot of cases where he repeats something he's heard that he evidently doesn't understand. The muddled attempt to explain fault tolerance above is one example, but we could also mention, for example, his attempt in §4.1 to describe Fortran programmers writing Fortran in C++, which completely misses the actual major difficulty (it's mostly about structuring the data as arrays, not the control flow), or his remark, "Assembler is regarded as the second-generation language," devoid of the historical context to provide any meaning to it.
- One problem that I think is actually new in the second edition is its presumption that all software is object-oriented (despite paying lip service to the fact that Visual Basic [6] was the most popular language among professional programmers, many people were still programming in Ada and assembly and Cobol and C and Fortran, etc.) and that looks a bit snake-oilier from our perspective now than it did at the time. I think OO is a useful approach to software design, but if I'm writing a generic tutorial on how to design a program, I wouldn't have a step in it called "Level 3: Division into Classes" as McConnell does in §5.2, because that makes my book completely inapplicable to programming in C, Go, Fortran, Rust, Racket, VB6, or Clojure, and inapplicable to much of what people do in Python, PHP, JS, Octave, and R. The snake oil here is not object-orientation but a totalizing ideology that everything must be OO; the Chapter 6 introduction says, "In the twenty-first century, programmers think about programming in terms of classes.". The way I remember it, the first edition didn't have this problem.
- This totalizing OO outlook is somewhat exacerbated by the fact that he doesn't really understand object orientation at all, so he gives a lot of bad advice, like, "A large percentage of routines in object-oriented programs will be accessor routines, which will be very short," §7.4. His whole chapter 6 is about designing classes, but he never mentions the actual core concept of object-orientation, which is polymorphic message sends, presumably because although he knows they exist, he isn't really comfortable with them and doesn't understand how central they are to the OO worldview. Instead he treats classes as a newfangled synonym for CLU's "clusters" or Ada "packages". Much of the chapter is devoted to workarounds for shortcomings of C++. This isn't really "snake oil," just incompetence.
- Another problem that I'm pretty sure wasn't present in the first edition is the counterproductive recommendations of worthless IEEE management process standards in virtually every chapter. This is kind of snake-oily; these standards are of abominable literary quality and contain no useful information that could conceivably help anyone to improve the software they write. As a representative emetic example, check out IEEE 1028, recommended in Chapter 20 and again in Chapter 21. http://profs.etsmtl.ca/claporte/english/enseignement/cmu_sqa.... Unlike some other IEEE management process standards I've had the misfortune of reading, it at least doesn't seem to contain any misinformation, but that's because it manages to spend 47 pages saying nothing at all about software.
There's still much material in the book that's solid, and lots of references to good information, but it's mixed with a lot of serious misinformation, misleading analogies, and embarrassing incompetence. And it's a slog to get through so much verbiage. But it's certainly better than Clean Code. Still, now that The Practice of Programming, The Pragmatic Programmer, and A Philosophy of Software Design are out, I think there's no longer any reason to recommend Code Complete.
I'm a big fan of TDD, but I quit reading this article the second my eyes came across "IBM System Sciences Institute" and the chart that accompanies it.
This is by now one of the most thoroughly debunked memes in our profession. I wrote a couple chapters about it: http://leanpub.com/leprechauns . I wrote a handy little guide for people to know just how much BS was involved in any one citation: https://plus.google.com/+LaurentBossavit/posts/aNKut1QV8pT
If that wasn't enough, there is now an actual negative research result on the so-called defect cost increase: https://arxiv.org/pdf/1609.04886.pdf
It should be quite clear by now that this type of argument doesn't do TDD any favors, it taints it by association with intellectual dishonesty.
It's buried a bit, but it actually does kind of refute that.
> Here is a 2016 paper [PDF] whose authors "examined 171 software projects conducted between 2006 and 2014," all of which used a methodology called the Team Software Process. The researchers concluded that "the times to resolve issues at different times were usually not significantly different."
Link is to https://arxiv.org/pdf/1609.04886.pdf
Googling more, the same vaguely sourced "IBM System Sciences" figure seems to be passed on from one poorly researched web post to another. The trail went cold but it seems to date back to the mainframe IBM of the 1970's or 1980's. Certainly it's from a different software engineering culture than today's continuous delivery processes.
A promising looking current review of the question is here: https://link.springer.com/article/10.1007/s10664-016-9469-x
(PDF link: https://arxiv.org/pdf/1609.04886.pdf)
They conclude: "We checked for traces of this effect in 171 projects from the period 2006–2014. That
data held no trace of the delayed issue effect. To the best of our…
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knowledge, this paper is
the largest study of this effect yet performed." ... "Our results beg the question: why does the delayed issue effect persist as a truism in software engineering literature? No doubt the original evidence was compelling at the time, but
much has changed in the realm of software development in the subsequent 40 years."
Fast compilation is important when compilation occurs at runtime, such as query compilers in modern database systems and WebAssembly virtual machines in modern browsers.
The recent discovery of the Spectre and Meltdown attacks represents a watershed moment not just for the field of Computer Security, but also of Programming Languages.
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