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Java string concatenation optimisation is applied in this case?

Let's imagine I have a lib which contains the following simple method:
private static final String CONSTANT = "Constant";
public static String concatStringWithCondition(String condition) {
return "Some phrase" + condition + CONSTANT;
}
What if someone wants to use my method in a loop? As I understand, that string optimisation (where + gets replaced with StringBuilder or whatever is more optimal) is not working for that case? Or this is valid for strings initialised outside of the loop?
I'm using java 11 (Dropwizard).
Thanks.

No, this is fine.
The only case that string concatenation can be problematic is when you're using a loop to build one single string. Your method by itself is fine. Callers of your method can, of course, mess things up, but not in a way that's related to your method.

The code as written should be as efficient as making a StringBuilder and appending these 3 constants to it. There certainly is absolutely no difference at all between a literal ("Some phrase"), and an expression that the compiler can treat as a Compile Time Constant (which CONSTANT, here, clearly is - given that CONSTANT is static, final, not null, and of a CTCable type (All primitives and strings)).
However, is that 'efficient'? I doubt it - making a stringbuilder is not particularly cheap either. It's orders of magnitude cheaper than continually making new strings, sure, but there's always a bigger fish:
It doesn't matter
Computers are fast. Really, really fast. It is highly likely that you can write this incredibly badly (performance wise) and it still won't be measurable. You won't even notice. Less than a millisecond slower.
In general, anybody that worries about performance at this level simply lacks perspective and knowledge: If you apply that level of fretting to your java code and you have the knowledge to know what could in theory be non-perfectly-performant, you'll be sweating every 3rd character you ever type. That's no way to program. So, gain that perspective (or take it from me, "just git gud" is not exactly something you can do in a week - take it on faith for now, as you learn you can start verifying) - and don't worry about it. Unless you actually run into an actual situation where the code is slower than it feels like it could be, or slower than it needs to be, and then toss profilers and microbenchmark testing frameworks at it, and THEN, armed with all that information (and not before!), consider optimizing. The reports tell you what to optimize, because literally less than 1% of the code is responsible for 99% of the performance loss, so spending any time on code that isn't in that 1% is an utter waste of time, hence why you must get those reports first, or not start at all.
... or perhaps it does
But if it does matter, and it's really that 1% of the code that is responsible for 99% of the loss, then usually you need to go a little further than just 'optimize the method'. Optimize the entire pipeline.
What is happening with this string? Take that into consideration.
For example, let's say that it, itself, is being appended to a much bigger stringbuilder. In which case, making a tiny stringbuilder here is incredibly inefficient compared to rewriting the method to:
public static void concatStringWithCondition(StringBuilder sb, String condition) {
sb.append("Some phrase").append(condition).append(CONSTANT);
}
Or, perhaps this data is being turned into bytes using UTF_8 and then tossed onto a web socket. In that case:
private static final byte[] PREFIX = "Some phrase".getBytes(StandardCharsets.UTF_8);
private static final byte[] SUFFIX = "Some Constant".getBytes(StandardCharsets.UTF_8);
public void concatStringWithCondition(OutputStream out, String condition) {
out.write(PREFIX);
out.write(condition.getBytes(StandardCharsets.UTF_8));
out.write(SUFFIX);
}
and check if that outputstream is buffered. If not, make it buffered, that'll help a ton and would completely dwarf the cost of not using string concatenation. If the 'condition' string can get quite large, the above is no good either, you want a CharsetEncoder that encodes straight to the OutputStream, and may even want to replace all that with some ByteBuffer based approach.
Conclusion
Assume performance is never relevant until it is.
IF performance truly must be tackled, strap in, it'll take ages to do it right. Doing it 'wrong' (applying dumb rules of thumb that do not work) isn't useful. Either do it right, or don't do it.
IF you're still on bard, always start with profiler reports and use JMH to gather information.
Be prepared to rewrite the pipeline - change the method signatures, in order to optimize.
That means that micro-optimizing, which usually sacrifices nice abstracted APIs, is actively bad for performance - because changing pipelines is considerably more difficult if all code is micro-optimized, given that this usually comes at the cost of abstraction.
And now the circle is complete: Point 5 shows why the worrying about performance as you are doing in this question is in fact detrimental: It is far too likely that this worry results in you 'optimizing' some code in a way that doesn't actually run faster (because the JVM is a complex beast), and even if it did, it is irrelevant because the code path this code is on is literally only 0.01% or less of the total runtime expenditure, and in the mean time you've made your APIs worse and lack abstraction which would make any actually useful optimization much harder than it needs to be.
But I really want rules of thumb!
Allright, fine. Here are 2 easy rules of thumb to follow that will lead to better performance:
When in rome...
The JVM is an optimising marvel and will run the craziest code quite quickly anyway. However, it does this primarily by being a giant pattern matching machine: It finds recognizable code snippets and rewrites these to the fastest, most carefully tuned to juuust your combination of hardware machine code it can. However, this pattern machine isn't voodoo magic: It's got limited patterns. Which patterns do JVM makers 'ship' with their JVMs? Why, the common patterns, of course. Why include a pattern for exotic code virtually nobody ever writes? Waste of space.
So, write code the way java programmers tend to write it. Which very much means: Do not write crazy code just because you think it might be faster. It'll likely be slower. Just follow the crowd.
Trivial example:
Which one is faster:
List<String> list = new ArrayList<String>();
for (int i = 0; i < 10000; i++) list.add(someRandomName());
// option 1:
String[] arr = list.toArray(new String[list.size()]);
// option 2:
String[] arr = list.toArray(new String[0]);
You might think, obviously, option 1, right? Option 2 'wastes' a string array, making a 0-length array just to toss it in the garbage right after. But you'd be wrong: Option 2 is in fact faster (if you want an explanation: The JVM recognizes it, and does a hacky move: It makes an new string array that does not need to be initialized with all zeroes first. Normal java code cannot do this (arrays are neccessarily initialized blank, to prevent memory corruption issues), but specifically .toArray(new X[0])? Those pattern matching machines I told you about detect this and replace it with code that just blits the refs straight into a patch of memory without wasting time writing zeroes to it first.
It's a subtle difference that is highly unlikely to matter - it just highlights: Your instincts? They will mislead you every time.
Fortunately, .toArray(new X[0]) is common java code. And easier and shorter. So just write nice, convenient code that looks like how other folks write and you'd have gotten the right answer here. Without having to know such crazy esoterics as having to reason out how the JVM needs to waste time zeroing out that array and how hotspot / pattern matching might possibly eliminate this, thus making it faster. That's just one of 5 million things you'd have to know - and nobody can do that. Thus: Just write java code in simple, common styles.
Algorithmic complexity is a thing hotspot can't fix for you
Given an O(n^3) algorithm fighting an O(log(n) * n^2) algorithm, make n large enough and the second algorithm has to win, that's what big O notation means. The JVM can do a lot of magic but it can pretty much never optimize an algorithm into a faster 'class' of algorithmic complexity. You might be surprised at the size n has to be before algorithmic complexity dominates, but it is acceptable to realize that your algorithm can be fundamentally faster and do the work on rewriting it to this more efficient algorithm even without profiler reports and benchmark harnesses and the like.

What would be the best way to build a Big-O runtime complexity analyzer for pseudocode in a text file?

I am trying to create a class that takes in a string input containing pseudocode and computes its' worst case runtime complexity. I will be using regex to split each line and analyze the worst-case and add up the complexities (based on the big-O rules) for each line to give a final worst-case runtime. The pseudocode written will follow a few rules for declaration, initilization, operations on data structures. This is something I can control. How should I go about designing a class considering the rules of iterative and recursive analysis?
Any help in C++ or Java is appreciated. Thanks in advance.
class PseudocodeAnalyzer
{
public:
string inputCode;
string performIterativeAnalysis(string line);
string performRecursiveAnalysis(string line);
string analyzeTotalComplexity(string inputCode);
}
An example for iterative algorithm: Check if number in a grid is Odd:
1. Array A = Array[N][N]
2. for i in 1 to N
3. for j in 1 to N
4. if A[i][j] % 2 == 0
5. return false
6. endif
7. endloop
8. endloop
Worst-case Time-Complexity: O(n*n)

The concept: "I wish to write a program that analyses pseudocode in order to print out the algorithmic complexity of the algorithm it describes" is mathematically impossible!
Let me try to explain why that is, or how you get around the inevitability that you cannot write this.
Your pseudocode has certain capabilities. You call it pseudocode, but given that you are now trying to parse it, it's still a 'real' language where terms have real meaning. This language is capable of expressing algorithms.
So, which algorithms can it express? Presumably, 'all of them'. There is this concept called a 'turing machine': You can prove that anything a computer can do, a turing machine can also do. And turing machines are very simple things. Therefore, if you have some simplistic computer and you can use that computer to emulate a turing machine, you can therefore use it to emulate a complete computer. This is how, in fundamental informatics, you can prove that a certain CPU or system is capable of computing all the stuff some other CPU or system is capable of computing: Use it to compute a turing machine, thus proving you can run it all. Any system that can be used to emulate a turing machine is called 'turing complete'.
Then we get to something very interesting: If your pseudocode can be used to express anything a real computer can do, then your pseudocode can be used to 'write'... your very pseudocode checker!
So let's say we do just that and stick the pseudocode that describes your pseudocode checker in a function we shall call pseudocodechecker. It takes as argument a string containing some pseudocode, and returns a string such as O(n^2).
You can then write this program in pseudocode:
1. if pseudocodechecker(this-very-program) == O(n^2)
2. If True runSomeAlgorithmThatIsO(1)
3. If False runSomeAlgorithmTahtIsO(n^2)
And this is self-defeating: We have 'programmed' a paradox. It's like "This statement is a lie", or "the set of all sets that do not contain themselves". If it's false it is true and if it is true it false. [Insert GIF of exploding computer here].
Thus, we have mathematically proved that what you want is impossible, unless one of the following is true:
A. Your pseudocode-based checker is incorrect. As in, it will flat out give a wrong answer sometimes, thus solving the paradox: If you feed your program a paradox, it gives a wrong answer. But how useful is such an app? An app where you know the answer it gives may be incorrect?
B. Your pseudocode-based checker is incomplete: The official definition of your pseudocode language is so incapable, you cannot even write a turing machine in it.
That last one seems like a nice solution; but it is quite drastic. It pretty much means that your algorithm can only loop over constant ranges. It cannot loop until a condition is true, for example. Another nice solution appears to be: The program is capable of realizing that an answer cannot be given, and will then report 'no answer available', but unfortunately, with some more work, you can show that you can still use such a system to develop a paradox.

The answer by #rzwitserloot and the ones given in the link are correct. Let me just add that it is possible to compute an approximation both to the halting problem as well as to finding the time complexity of a piece of code (written in a Turing-complete language!). (Compare that to the existence of automated theorem provers for arithmetic and other second order logics, which are undecidable!) A tool that under-approximated the complexity problem would output the correct time complexity for some inputs, and "don't know" for other inputs.
Indeed, the whole wide field of code analyzers, often built into the IDEs that we use every day, more often than not under-approximate decision problems that are uncomputable, e.g. reachability, nullability or value analyses.
If you really want to write such a tool: the basic idea is to identify heuristics, i.e., common patterns for which a solution is known, such as various patterns of nested for-loops with only very basic arithmetic operations manipulating the indices, or simple recursive functions where the recurrence relation can be spotted straight-away. It would actually be not too hard (though definitely not easy!) to write a tool that could solve most of the toy problems (such as the one you posted) that are given as homework to students, and that are often posted as questions here on SO, since they follow a rather small number of patterns.
If you wish to go beyond simple heuristics, the main theoretical concept underlying more powerful code analyzers is abstract interpretation. Applied to your use case, this would mean developing a mapping between code constructs in your language to code constructs in a different language (or simpler code constructs in the same language) for which it is easier to compute the time complexity. This mapping would have to conform to some constraints, in particular, the mapped constructs have have the same or worse time complexity as the original code. Actually, mapping a piece of code to a recurrence relation would be an example of abstract interpretation. So is replacing a line of code with something like "O(1)". So, the task is just to formalize some of the things that we do in our heads anyway when we are analyzing the time complexity of code.

How can I convert something to double?

I have an object from an implemented class ReportManager. Now getReport() is a number like 0.23 with the data type report. But I want this number to be a double so I can work with it.
I cannot change the class, because it is implemented in the Java compiler (it is for writing macros for a program).
Does anybody have a suggestion how I could handle it? I checked the API and there is no function implemented that could help me.
EDIT: I do have the situation: I want to calculate the Center of Pressure of an object in my simulation. So I need the moment in that position to be 0.
Now: This is how the automated macro ask the value of the Moment:
MomentReport momentReport_0 =
((MomentReport) simulation_0.getReportManager().getReport("Moment 1"));
Now I want to take the abs of it, because I don't mind if it's positive or negative.
while(Math.abs(momentReport_0) > 0.2)
(Do iterate and change position.) At the end I want to println the the position.
simulation_0 is an object of Simulation. I could copy a part of the API if it's needed. Just don't know which class documentation would help.

You can cast the number to a double so that you can work with it, assuming it's returning you a single-precision float at the moment.
double result = (double) reportManager.getReport();
I recommend you read up on what typecasting is so that you can better understand what's going on here, as there would be some situations where it's unsafe to cast:
https://en.wikipedia.org/wiki/Type_conversion

BigDecimal precision above 1E22

for some reason I found myself coding some piece of software, that should be able to perfom some astronomic calculations.
While most of it will be about transfering the correct formula into Java, I found an annoying Problem right at the verry beginning of my "test how to calculate big numbers".
Well... Imagine the Sun (our Sun), which has a mass of (about and rounded, for more easy explaining) 10E30 kg. Ten with 30 following Zeros. All native datatypes are just unusuable for this. To mention: I KNOW that I could use 3000 to calculate things and just add trailing zeros in the output-view, but I hoped to keep it as precise as possible. So using short numbers will be my last resort only.
Comming to the Problem. Please have a look at the code:
BigDecimal combinedMass = new BigDecimal(1E22);
int massDistribution = 10;
Integer mD1 = massDistribution;
Integer mD2 = 100 - massDistribution;
BigDecimal starMass;
BigDecimal systemMass;
systemMass = combinedMass.divide(new BigDecimal("100")).multiply(new BigDecimal(mD1.toString()));
starMass = combinedMass.divide(new BigDecimal("100")).multiply(new BigDecimal(mD2.toString()));
System.out.println((systemMass).toEngineeringString());
System.out.println((starMass));
It will output 1000000000000000000000 and 9000000000000000000000, whats exactly what I did expect. But look at the combineMass Field. If I raise it to 1E23, the Output will change
I get 9999999999999999161139.20 and 89999999999999992450252.80...
So I know I could use jut BigInteger, because its more reliable in this case, but for the sake of precicion, sometimes the BigWhatEver may drop to something like 50.1258
Plus, I hope to get the 10.xE30 as output, whats only possible using bigDecimals.
I want to know: Is there no way avoidng this (that error appers above 1E23 for every value I tried), while keeping the ability to calculate Floating-Points? Should I cut the After-Decimal-Separator-Values for this Field to two digets?
And for something more to wonder about:
System.out.println(combinedMass.precision());
in relation with the code above will provide 23 for that case, but En+1 for most other values (Thats was when I grow really confused)
Thanks for advise.

You're using basic types without realizing it:
new BigDecimal(1E22);
Here, 1E22 is a primitive double, and you already lost precision by using it.
What you want is
new BigDecimal("10000000000000000000000");
or
new BigDecimal(10).pow(22);

How does WEKA normalize attributes?

Suppose I input to WEKA some dataset and set a normalization filter for the attributes so the values be between 0 and 1. Then suppose the normalization is done by dividing on the maximum value, and then the model is built. Then what happens if I deploy the model and in the new instances to be classified an instance has a feature value that is larger than the maximum in the training set. How such a situation is handled? Does it just take 1 or does it then take more than 1? Or does it throw an exception?

The documentation doesn't specify this for filters in general.So it must depend on the filter. I looked at the source code of weka.filters.unsupervised.attribute.Normalize which I assume you are using, and I don't see any bounds checking in it.
The actual scaling code is in the Normalize.convertInstance() method:
value = (vals[j] - m_MinArray[j]) / (m_MaxArray[j] - m_MinArray[j])
* m_Scale + m_Translation;
Barring any (unlikely) additional checks outside this method I'd say that it will scale to a value greater than 1 in the situation that you describe. To be 100% sure your best bet is to write a testcase, invoke the filter yourself, and find out. With libraries that haven't specified their working in the Javadoc, you never know what the next release will do. So if you greatly depend on a particular behaviour, it's not a bad idea to write an automated test that regression-tests the behaviour of the library.

I have the same questions as you said. I did as follows and may this method can help you:
I suppose you use the weka.filters.unsupervised.attribute.Normalize to normalize your data.
as Erwin Bolwidt said, weka use
value = (vals[j] - m_MinArray[j]) / (m_MaxArray[j] - m_MinArray[j])
* m_Scale + m_Translation;
to normalize your attribute.
Don't forget that the Normalize class has this two method:
public double[] getMinArray()
public double[] getMaxArray()
Which Returns the calculated minimum/maximum values for the attributes in the data.
And you can store the minimum/maximum values. And then use the formula to normalize your data by yourself.
Remember you can set the attribute in Instance class, and you can classify your result by Evaluation.evaluationForSingleInstance
I 'll give you the link later, may this help you.
Thank you