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Let's say I had over 2 billion objects with a unique int id field and decided that I needed to extend that. I replace all the relevant int tokens in the code with long and perform the conversion in my database. Intuition tells me something would go horribly horribly wrong, but I can't figure out what. What would go horribly horribly wrong?
If you take proper precautions like:
testing your code properly,
doing a trial conversion on a development server using a snapshot of the production data,
using proper configuration management on your production system,
backing up your production database before you start the real conversion,
etcetera
then the worst case is that you might need to recover from the backup if the conversion fails ... or you discover bad things soon afterwards.
In short, this is not that different to any change that modifies the database schema.
This is actually a fairly low risk change, in that anything that is going to go wrong will most likely be found at compile time. Just be careful of anything you are calling through reflection, placing into raw collections, etc.
This situation somewhat based on mistakes I've seen/made. It's also somewhat contrived, but it sounds like you're looking for imaginative answers...
Suppose you've got a JDBC wrapper in which parameters are bound to queries using a bind method that's overloaded as void bind(String name, int x), void bind(String name, long x), ... rather than separately-named setInt, setLong, ... methods.
And suppose someone got into the habit of always including a redundant cast when calling these methods (e.g. query.bind("personId", (int) person.getId()); to make the target method explicit, so that, for instance, the return type of person.getId() couldn't be changed to String without introducing a compile error (so anyone changing that aspect of the person class would be forced to come look at this query and make sure it still makes sense).
Now suppose that in your refactor to change the person ID from int to long, you forget to change one of these casts from (int) to (long), and the int cast that used to be redundant is now a narrowing operation.
Three years down the road, when the identifier sequence rolls past 2^31, suddenly that cast (which ironically was supposed to be defensive) is now truncating identifiers, quietly corrupting your database.
I cannot understand why the Java compiler does not shorten names of variables, parameters, method names, by replacing them with some unique IDs.
For instance, given the class
public class VeryVeryVeryVeryVeryLongClass {
private int veryVeryVeryVeryVeryLongInt = 3;
public void veryVeryVeryVeryVeryLongMethod(int veryVeryVeryVeryVeryLongParamName) {
this.veryVeryVeryVeryVeryLongInt = veryVeryVeryVeryVeryLongParamName;
}
}
the compiled file contains all these very long names:
Wouldn't simple unique IDs speed the parsing, and also provide a first obfuscation?
You assume that obfuscation is always desired, but it isn't:
Reflection would break, and with it JavaBeans and many frameworks reliant on it
Stack traces would become completely unreadable
If you tried to code against a compiled JAR, you'd end up with code like String name = p.a1() instead of String name = p.getName()
Obfuscation is normally the very last step taken, when you're delivering the finished app, and even then it's not used particularly often except when the target platform has severe memory constraints.
When you use a class, you refer to its methods by their name. Therefore, the compiler needs to preserve those names.
In any event, I don't see why the compiler should aim to obfuscate anything. Rather, it should aim to do exactly the opposite: be as transparent as possible.
The JVM does use numeric IDs internally.
Class files cannot be obfuscated like that because Java is dynamically linked: names of members must be publicly readable or other classes cannot use your code.
Wouldn't simple unique IDs speed the parsing?
No. It would add a mapping that would probably slow it down.
and also provide a first obfuscation
Yes, but who wants the compiler to do obfuscation buy default? Not me.
Your suggestion has no merit.
We are working in a project with multiple developers and currently the retrieval of values from a configuration file is somewhat "wild west":
Everybody uses some string to retrieve a value from the Config object
Those keys are spread across multiple classes and packages
Sometimes the are not even declared as constants
Naming of the keys is inconsistent and the config file (.properties) looks messy
I would like to sort that out and force everyone to explicitly define their configuration keys. Ideally in one place to streamline how config keys actually look.
I was thingking of using an Enum as a key and turning my retrieval method into:
getConfigValue(String key)
into something like
getConfigValue(ConfigKey)
NOTE: I am using this approach since the Preferences API seems a bit overkill to me plus I would actually like to have the configuration in a simple file.
What are the cons of this approach?
First off, FWIW, I think it's a good idea. But you did specifically ask what the "cons" are, so:
The biggest "con" is that it ties any class that needs to use configuration data to the ConfigKey class. Adding a config key used to mean adding a string to the code you were working on; now it means adding to the enum and to the code you were working on. This is (marginally) more work.
You're probably not markedly increasing inter-dependence otherwise, since I assume the class that getConfigValue is part of is the one on which you'd define the enum.
The other downside to consolidation is if you have multiple projects on different parts of the same code base. When you develop, you have to deal with delivery dependencies, which can be a PITA.
Say Project A and Project B are scheduled to get released in that order. Suddenly political forces change in the 9th hour and you have to deliver B before A. Do you repackage the config to deal with it? Can your QA cycles deal with repackaging or does it force a reset in their timeline.
Typical release issues, but just one more thing you have to manage.
From your question, it is clear that you intend to write a wrapper class for the raw Java Properties API, with the intention that your wrapper class provides a better API. I think that is a good approach, but I'd like to suggest some things that I think will improve your wrapper API.
My first suggested improvement is that an operation that retrieves a configuration value should take two parameters rather than one, and be implemented as shown in the following pseudocode:
class Configuration {
public String getString(String namespace, String localName) {
return properties.getProperty(namespace + "." + localName);
}
}
You can then encourage each developer to define a string constant value to denote the namespace for whatever class/module/component they are developing. As long as each developer (somehow) chooses a different string constant for their namespace, you will avoid accidental name clashes and promote a somewhat organised collection of property names.
My second suggested improvement is that your wrapper class should provide type-safe access to property values. For example, provide getString(), but also provide methods with names such as getInt(), getBoolean(), getDouble() and getStringList(). The int/boolean/double variants should retrieve the property value as a string, attempt to parse it into the appropriate type, and throw a descriptive error message if that fails. The getStringList() method should retrieve the property value as a string and then split it into a list of strings based on using, say, a comma as a separator. Doing this will provide a consistent way for developers to get a list value.
My third suggested improvement is that your wrapper class should provide some additional methods such as:
int getDurationMilliseconds(String namespace, String localName);
int getDurationSeconds(String namespace, String localName);
int getMemorySizeBytes(String namespace, String localName);
int getMemorySizeKB(String namespace, String localName);
int getMemorySizeMB(String namespace, String localName);
Here are some examples of their intended use:
cacheSize = cfg.getMemorySizeBytes(MY_NAMSPACE, "cache_size");
timeout = cfg.getDurationMilliseconds(MY_NAMSPACE, "cache_timeout");
The getMemorySizeBytes() method should convert string values such as "2048 bytes" or "32MB" into the appropriate number of bytes, and getMemorySizeKB() does something similar but returns the specified size in terms of KB rather than bytes. Likewise, the getDuration<units>() methods should be able to handle string values like "500 milliseconds", "2.5 minutes", "3 hours" and "infinite" (which is converted into, say, -1).
Some people may think that the above suggestions have nothing to do with the question that was asked. Actually, they do, but in a sneaky sort of way. The above suggestions will result in a configuration API that developers will find to be much easier to use than the "raw" Java Properties API. They will use it to obtain that ease-of-use benefit. But using the API will have the side effect of forcing the developers to adopt a namespace convention, which will help to solve the problem that you are interested in addressing.
Or to look at it another way, the main con of the approach described in the question is that it offers a win-lose situation: you win (by imposing a property-naming convention on developers), but developers lose because they swap the familiar Java Properties API for another API that doesn't offer them any benefits. In contrast, the improvements I have suggested are intended to provide a win-win situation.
What are some common strategies for refactoring large "state-only" objects?
I am working on a specific soft-real-time decision support system which does online modeling/simulation of the national airspace. This piece of software consumes a number of live data feeds, and produces a once-per-minute estimate of the "state" of a large number of entities in the airspace. The problem breaks down neatly until we hit what is currently the lowest-level entity.
Our mathematical model estimates/predicts upwards of 50 parameters for a timeline of several hours into the past and future for each of these entities, roughly once per minute. Currently, these records are encoded as a single Java class with a lot of fields (some get collapsed into an ArrayList). Our model is evolving, and the dependencies among the fields are not yet set in stone, so each instance wanders through a convoluted model, accumulating settings as it goes along.
Currently we have something like the following, which uses a builder pattern approach to build up the contents of the record, and enforce what the known dependencies are (as a check against programmer error as evolve the mode.) Once the estimate is done, we convert the below into an immutable form using a .build() type method.
final class OneMinuteEstimate {
enum EstimateState { INFANT, HEADER, INDEPENDENT, ... };
EstimateState state = EstimateState.INFANT;
// "header" stuff
DateTime estimatedAtTime = null;
DateTime stamp = null;
EntityId id = null;
// independent fields
int status1 = -1;
...
// dependent/complex fields...
... goes on for 40+ more fields...
void setHeaderFields(...)
{
if (!EstimateState.INFANT.equals(state)) {
throw new IllegalStateException("Must be in INFANT state to set header");
}
...
}
}
Once a very large number of these estimates are complete, they are assembled into timelines where aggregate patterns/trends are analyzed. We have looked at using an embedded database but have struggled with performance issues; we'd rather get this sorted out in terms of data modeling and then incrementally move portions of the soft-real-time code into an embedded data store.
Once the "time sensitive" pieces of this are done, the products are flushed to flat files and a database.
Problems:
It's a giant class, with way too many fields.
There is very little behavior encoded in the class; it's mostly a holder for data fields.
Maintaining the build() method is extremely cumbersome.
It feels clumsy to manually maintain a "state machine" abstraction merely for the purpose of ensuring that a large number of dependent modeling components are properly populating a data object, but it has saved us a lot of frustration as the model evolves.
There is a lot of duplication, particularly when the records described above are aggregated into very similar "rollups" which amount to rolling sums/averages or other statistical products of the above structure in time series.
While some of the fields could be clumped together, they are all logically "peers" of one another, and any breakdown we've tried has resulted in having behavior/logic artificially split and needing to reach two levels deep in indirection.
Out of the box ideas entertained, but this is something we need to evolve incrementally. Before anyone else says it, I'll note that one could suggest that our mathematical model is insufficiently crisp if the data representation for that model is this hard to get ahold of. Fair point, and we're working that, but I think that's a side-effect of an R&D environment with a lot of contributors, and a lot of concurrent hypotheses in play.
(Not that it matters, but this is implemented in Java. We use HSQLDB or Postgres for output products. We don't use any persistence framework, partly out of a lack of familiarity, partly because we have enough performance trouble with just the database alone and hand-coded storage routines... we're skeptical of moving towards additional abstraction.)
I had much of the same problem you did.
At least I think I did, sounds like I did. Representation was different, but at 10,000 feet, sounds pretty much the same. Crapload of discrete, "arbitrary" variables and a bunch of ad hoc relationships among them (essentially business driven), subject to change at a moment's notice.
You also have another issue, which you sorta mentioned, and that was the performance requirement. Sounds like faster is better, and likely a slow perfect solution would be tossed out for the fast lousy one, simply because the slower one can't meet a baseline performance requirement, no matter how good it is.
To put it simply, what I did was I designed a simple domain specific rule language for my system.
The entire point of the DSL was to implicitly express relationships and package them up in to modules.
Very crude, contrived example:
D = 7
C = A + B
B = A / 5
A = 10
RULE 1: IF (C < 10) ALERT "C is less than 10"
RULE 2: IF (C > 5) ALERT "C is greater than 5"
RULE 3: IF (D > 10) ALERT "D is greater than 10"
MODULE 1: RULE 1
MODULE 2: RULE 3
MODULE 3: RULE 1, RULE 2
First, this is not representative of my syntax.
But you can see from the Modules, that it is 3, simple rules.
The key though, is that it's obvious from this that Rule 1 depends on C, which depends on A and B, and B depends on A. Those relationships are implied.
So, for that module, all of those dependencies "come with it". You can see if I generated code for Module 1 it might look something like:
public void module_1() {
int a = 10;
int b = a / 5;
int c = a + b;
if (c < 10) {
alert("C is less than 10");
}
}
Whereas if I created Module 2, all I would get is:
public void module_2() {
int d = 7;
if (d > 10) {
alert("D is greater than 10.");
}
}
In Module 3 you see the "free" reuse:
public void module_3() {
int a = 10;
int b = a / 5;
int c = a + b;
if (c < 10) {
alert("C is less than 10");
}
if (c > 5) {
alert("C is greater than 5");
}
}
So, even though I have one "soup" of rules, the Modules root the base of the dependencies, and thus filter out the stuff it doesn't care about. Grab a module, shake the tree and keep what's left hanging.
My system used the DSL to generate source code, but you can easily have it create a mini runtime interpreter as well.
Simple topological sorting handled the dependency graph for me.
So, the nice thing about this is that while there was inevitable duplication in the final, generated logic, at least across modules, there wasn't any duplication in the rule base. What you as a developer/knowledge worker maintain is the rule base.
What is also nice is that you can change an equation, and not worry so much about the side effects. For example, if I change do C = A / 2, then, suddenly, B drops out completely. But the rule for IF (C < 10) doesn't change at all.
With a few simple tools, you can show the entire dependency graph, you can find orphaned variables (like B), etc.
By generating source code, it's going to run as fast as you want.
In my case, it was interesting to see a rule drop a single variable and see 500 lines of source code vanish from the resulting module. That's 500 lines I didn't have to crawl through by hand and remove during maintenance and development. All I had to do was change a single rule in my rule base and let "magic" happen.
I was even able to do some simple peephole optimization and eliminate variables.
It's not that hard to do. Your rule language can be XML, or a simple expression parser. No reason to go full boat Yacc or ANTLR on it if you don't want to. I'll put a plug in for S-Expressions, no grammar needed, brain dead parsing.
Spreadsheets also make a great input tool, actually. Just be strict on the formatting. Kind of sucks for merging in SVN (so, Don't Do That), but end users love it.
You may well be able to get away with an actual rule based system. My system wasn't dynamic at runtime, and didn't really need sophisticated goal seeking and inference, so I didn't need the overhead of such a system. But if one works for you out of the box, then happy day.
Oh, and for an implementation note, for those who don't believe you can hit the 64K code limit in a Java method, well I can assure you it can be done :).
Splitting a Large Data Object is very similar to Normalizing a Large Relational Table (first and second normal form). Follow the rules to reach at least second normal form and you may have a good decomposition of the original class.
From experience working also with R&D stuff with soft real-time performance constrains (and sometimes monster fat classes), I would suggest NOT to use OR mappers. In such situations, you'll be better off dealing "touching the metal" and working directly with JDBC result sets. This is my suggestion for apps with soft real-time constrains and massive amounts of data items per package. More importantly, if the number of distinct classes (not class instances, but class definitions) that need to persisted is large, and you also have memory constrains in your specs, you will also want to avoid ORMs like Hibernate.
Going back to your original question:
What you seem to have is a typical problem of 1) mapping multiple data items into a OO model and 2) such multiple data items do not exhibit a good way of grouping or segregation (and any attempt to grouping tends simply not to feel right.) Sometimes the domain model does not lend itself for such aggregation, and coming up with an artificial way of doing so typically ends up in compromises that don't satisfy all design requirements and desires.
To make matters worse, a OO model typically requires/expects you to have all the items present in a class as class' fields. Such a class is typically without behavior, so it is just a struct-like construct, aka data envelope or data shuttle.
But such situations beg the following questions:
Does your application need to read/write all 40, 50+ data items at once, always?
*Must all data items be always present?*
I do not know the specifics of your problem domain, but in general I've found that we rarely ever need to deal with all data items at once. This is where a relational model shines because you don't have to query all rows from a table at once. You only pulls those you need as projections of the table/view in question.
In a situation where we have a potentially large number of data items, but on average the number of data items being passed down the wire is less than the maximum, you'd be better off using a Properties pattern.
Instead of defining a monster envelope class holding all items :
// java pseudocode
class envelope
{
field1, field2, field3... field_n;
...
setFields(m1,m2,m3,...m_n){field1=m1; .... };
...
}
Define a dictionary (based on a map for example):
// java pseudocode
public enum EnvelopeField {field1, field2, field3,... field_n);
interface Envelope //package visible
{
// typical map-based read fields.
Object get(EnvelopeField field);
boolean isEmpty();
// new methods similar to existing ones in java.lang.Map, but
// more semantically aligned with envelopes and fields.
Iterator<EnvelopeField> fields();
boolean hasField(EnvelopeField field);
}
// a "marker" interface
// code that only needs to read envelopes must operate on
// these interfaces.
public interface ReadOnlyEnvelope extends Envelope {}
// the read-write version of envelope, notice that
// it inherits from Envelope, but not from ReadOnlyEnvelope.
// this is done to make it difficult (but not impossible
// unfortunately) to "cast-up" a read only envelope into a
// mutable one.
public interface MutableEnvelope extends Envelope
{
Object put(EnvelopeField field);
// to "cast-down" or "narrow" into a read only version type that
// cannot directly be "cast-up" back into a mutable.
ReadOnlyEnvelope readOnly();
}
// the standard interface for map-based envelopes.
public interface MapBasedEnvelope extends
Map<EnvelopeField,java.lang.Object>
MutableEnvelope
{
}
// package visible, not public
class EnvelopeImpl extends HashMap<EnvelopeField,java.lang.Object>
implements MapBasedEnvelope, ReadOnlyEnvelope
{
// get, put, isEmpty are automatically inherited from HashMap
...
public Iterator<EnvelopeField> fields(){ return this.keySet().iterator(); }
public boolean hasField(EnvelopeField field){ return this.containsKey(field); }
// the typecast is redundant, but it makes the intention obvious in code.
public ReadOnlyEnvelope readOnly(){ return (ReadOnlyEnvelope)this; }
}
public class final EnvelopeFactory
{
static public MapBasedEnvelope new(){ return new EnvelopeImpl(); }
}
No need to set up read-only internal flags. All you need to do is downcast your envelope instances as Envelope instances (that only provide getters).
Code that expects to read should operate on read-only envelopes and code that expects to change fields should operate on mutable envelopes. Creation of the actual instances would be compartmentalized in factories.
That is, you use the compiler to enforce things to be read-only (or allow things to be mutable) by establishing some code conventions, rules governing what interfaces to use where and how.
You can layer your code into sections that need to write separate from code that only needs to read. Once that's done, simple code reviews (or even grep) can identify code that is using the wrong interface.)
Problems:
Non-public Parent Interface:
Envelope is not declared as a public interface to prevent erroneous/malicious code from casting a read-only envelope down to a base envelope and then back to a mutable envelope. The intended flow is from mutable to read-only only - it is not intended to be bi-directional.
The problem here is that extension of Envelope is restricted to the package that contains it. Whether that is a problem will depend on the particular domain and intended usage.
Factories:
The problem is that factories can (and most likely will) be very complex. Again, the nature of the beast.
Validation:
Another problem introduced with this approach is that now you have to worry about code that expects field X to be present. Having the original monster envelope class partially frees you from that worry because, at least syntactically, all fields are there...
... whether the fields are set or not, that was another matter that still remains with this new model I'm proposing.
So if you have client code that expects to see field X, the client code has to throw some type of exception if the field is not present (or to computer or read a sensible default somehow.) In such cases, you will have to
Identify patterns of field presence. Clients that expect field X to be present might be grouped separately (layered apart) from clients that expect some other field to be present.
Associate custom validators (proxies to read-only envelope interfaces) that either throw exceptions or compute default values for missing fields according to some rules (rules provided programmatically, with an interpreter, or with a rules engine.)
Lack of Typing:
This might be debatable, but people used to work with static typing might feel uneasy with losing the benefits of static typing by going to a loosely typied map-based approach. The counter-argument of this is that most of the web works on a loose typing approach, even on the Java side (JSTL, EL.)
Problems aside, the larger the maximum number of possible fields and the lower the average number of fields present at any given time, the most effective wrt performance this approach will be. It adds additional code complexity, but that's the nature of the beast.
That complexity doesn't go away, and either will be present in your class model or in your validation code. Serialization and transferring down the wire is much more efficient, though, specially if you expect massive numbers of individual data transfers.
Hope it helps.
Actually this looks like a frequent problem that game developers face, bloated classes holding numerous variables and methods because of a deep inheritance tree etc.
There's this blog post about how and why to select composition over inheritance, maybe it would help.
One way you may be able to intelligently break up a large data class is to look at patterns of access by client classes. For example, if a set of classes only accesses fields 1-20 and another set of classes only accesses fields 25-30, maybe those groups of fields belong in separate classes.
It is possible to add and remove elements from an enum in Java at runtime?
For example, could I read in the labels and constructor arguments of an enum from a file?
#saua, it's just a question of whether it can be done out of interest really. I was hoping there'd be some neat way of altering the running bytecode, maybe using BCEL or something. I've also followed up with this question because I realised I wasn't totally sure when an enum should be used.
I'm pretty convinced that the right answer would be to use a collection that ensured uniqueness instead of an enum if I want to be able to alter the contents safely at runtime.
No, enums are supposed to be a complete static enumeration.
At compile time, you might want to generate your enum .java file from another source file of some sort. You could even create a .class file like this.
In some cases you might want a set of standard values but allow extension. The usual way to do this is have an interface for the interface and an enum that implements that interface for the standard values. Of course, you lose the ability to switch when you only have a reference to the interface.
Behind the curtain, enums are POJOs with a private constructor and a bunch of public static final values of the enum's type (see here for an example). In fact, up until Java5, it was considered best-practice to build your own enumeration this way, and Java5 introduced the enum keyword as a shorthand. See the source for Enum<T> to learn more.
So it should be no problem to write your own 'TypeSafeEnum' with a public static final array of constants, that are read by the constructor or passed to it.
Also, do yourself a favor and override equals, hashCode and toString, and if possible create a values method
The question is how to use such a dynamic enumeration... you can't read the value "PI=3.14" from a file to create enum MathConstants and then go ahead and use MathConstants.PI wherever you want...
I needed to do something like this (for unit testing purposes), and I came across this - the EnumBuster:
http://www.javaspecialists.eu/archive/Issue161.html
It allows enum values to be added, removed and restored.
Edit: I've only just started using this, and found that there's some slight changes needed for java 1.5, which I'm currently stuck with:
Add array copyOf static helper methods (e.g. take these 1.6 versions: http://www.docjar.com/html/api/java/util/Arrays.java.html)
Change EnumBuster.undoStack to a Stack<Memento>
In undo(), change undoStack.poll() to undoStack.isEmpty() ? null : undoStack.pop();
The string VALUES_FIELD needs to be "ENUM$VALUES" for the java 1.5 enums I've tried so far
I faced this problem on the formative project of my young career.
The approach I took was to save the values and the names of the enumeration externally, and the end goal was to be able to write code that looked as close to a language enum as possible.
I wanted my solution to look like this:
enum HatType
{
BASEBALL,
BRIMLESS,
INDIANA_JONES
}
HatType mine = HatType.BASEBALL;
// prints "BASEBALL"
System.out.println(mine.toString());
// prints true
System.out.println(mine.equals(HatType.BASEBALL));
And I ended up with something like this:
// in a file somewhere:
// 1 --> BASEBALL
// 2 --> BRIMLESS
// 3 --> INDIANA_JONES
HatDynamicEnum hats = HatEnumRepository.retrieve();
HatEnumValue mine = hats.valueOf("BASEBALL");
// prints "BASEBALL"
System.out.println(mine.toString());
// prints true
System.out.println(mine.equals(hats.valueOf("BASEBALL"));
Since my requirements were that it had to be possible to add members to the enum at run-time, I also implemented that functionality:
hats.addEnum("BATTING_PRACTICE");
HatEnumRepository.storeEnum(hats);
hats = HatEnumRepository.retrieve();
HatEnumValue justArrived = hats.valueOf("BATTING_PRACTICE");
// file now reads:
// 1 --> BASEBALL
// 2 --> BRIMLESS
// 3 --> INDIANA_JONES
// 4 --> BATTING_PRACTICE
I dubbed it the Dynamic Enumeration "pattern", and you read about the original design and its revised edition.
The difference between the two is that the revised edition was designed after I really started to grok OO and DDD. The first one I designed when I was still writing nominally procedural DDD, under time pressure no less.
You can load a Java class from source at runtime. (Using JCI, BeanShell or JavaCompiler)
This would allow you to change the Enum values as you wish.
Note: this wouldn't change any classes which referred to these enums so this might not be very useful in reality.
A working example in widespread use is in modded Minecraft. See EnumHelper.addEnum() methods on Github
However, note that in rare situations practical experience has shown that adding Enum members can lead to some issues with the JVM optimiser. The exact issues may vary with different JVMs. But broadly it seems the optimiser may assume that some internal fields of an Enum, specifically the size of the Enum's .values() array, will not change. See issue discussion. The recommended solution there is not to make .values() a hotspot for the optimiser. So if adding to an Enum's members at runtime, it should be done once and once only when the application is initialised, and then the result of .values() should be cached to avoid making it a hotspot.
The way the optimiser works and the way it detects hotspots is obscure and may vary between different JVMs and different builds of the JVM. If you don't want to take the risk of this type of issue in production code, then don't change Enums at runtime.
You could try to assign properties to the ENUM you're trying to create and statically contruct it by using a loaded properties file. Big hack, but it works :)