Project Coin: Elephants, Knapsacks, and Language Features
By Darcy-Oracle on Aug 17, 2009
Paraphrasing some thoughts already sent to the Project Coin list and discussed at JavaOne this year, there continues to be traffic on the list and elsewhere about the criteria for proposal selection (and non-selection) and those criteria are worth elaborating ahead of the final proposal list being determined in the near future.
First, a reminder from some earlier blog entries describing the context for Project Coin:
"Especially with the maturity of the Java platform, the onus is on the proposer to convince that a language change should go in; the onus is not to prove the change should stay out."
Criteria for desirable small language changes, December 23, 2008
"Given the rough timeline for JDK 7 and other on-going efforts to change the language, such as modules and annotations on types, only a limited number of small changes can be considered for JDK 7."
Guidance on measuring the size of a language change, December 11, 2008
With nearly 70 proposals submitted to the mailing list and the Sun bug database having well over 100 open "requests for enhancements" (rfe's) for the language, the large majority of those proposals and rfe's will not be included in JDK 7 as part of Project Coin or any other effort.
Project Coin will be limited to around 5 proposals total. That's it.
Therefore for Project Coin, in addition to determining whether a proposal to change the language is in and of itself appropriate, a determination also has to be made as to whether the change is more compelling than all but four or so other proposals. In economic terms, there an an opportunity cost in the proposal selection; that is, because of finite resources, choosing to have a particular proposal in the platform removes the opportunity to do other proposals. There will be good, compelling proposals that would improve the language not selected for Project Coin because there are a full set of better, more compelling proposals that are more useful to include instead. Having available prototypes for proposals, running the existing tests, and writing new tests can only better inform the continuing proposal evaluation and selection.
Part of evaluating proposals is judging their utility to the Java platform as a whole. In this way, I've long thought the Java platform is like the elephant in the parable about the blind men and the elephant:
While each Duke and each of us may know and understand our own usage of Java quite well and have valid ideas about how Java could be changed to improve programming in our own areas of interest (properties! operator overloading! design by contract! your favorite feature!), putting together all that accurate local information might just result in a patchwork elephant:
Rather than just a collection of local views, a broad perspective is needed to have an accurate, unified picture of the platform so Java can keep evolving and improving as a general-purpose programming language. This approach favors features with broader applicability. For example, a usability improvement to generics, like the diamond operator which allows type parameters to be elided during constructor calls, is usable more often than, say, one of the various proposals to allow extensible or abstract
enum types, a change that would only helpful in a small minority of
Even with a broad perspective, there are complexities in feature selection because choosing a set of language proposals is a kind of knapsack problem. That is, each feature has some discrete size and complexity to implement and confers some improvement to the language. There is a bounded size and complexity budget and the goal is maximizing the value held in the knapsack, the value of the set of improvements shipped in a release. Of note is that implementing a language change has much more of a discrete size (or a small selection of possible sizes) rather than a continuous range of possible sizes. In other words, because of the coordinated set of deliverables associated with a language change, it may be reasonable to implement 0%, 50,% or 100% of a possible feature but no other fraction. And doing 50% of the feature might take on quarter of the effort of doing the whole thing or three fourths of that effort.
Even when precise costs and benefits can be quantified, because of these discrete sizes the "greedy" algorithm of putting the highest value / cost item in the knapsack first can lead to globally poor results. If nothing else, having a pre-pass to reduce the number of proposals being considered for further review greatly reduces the combinatorial possibilities of subsets of features that could be included in a release.