Java Mock Interview: 20 Questions in 50 Minutes

Intermediate operations like filter, map, sorted and distinct return a new stream and are lazy; nothing runs until a terminal operation is called. Terminal operations like collect, forEach, reduce, count and findFirst trigger processing and produce a result. Laziness lets streams fuse steps into a single pass and short-circuit, so findFirst on filtered data stops early.

var, added in Java 10, lets the compiler infer the type of a local variable from its initializer, for example var list = new ArrayList<String>(). Java stays statically typed. var cannot be used for fields, method parameters or return types, and it needs an initializer that is not null. Use it when the type is obvious to keep code readable.

PreparedStatement sends the SQL with placeholders separately from the parameter values, so user input is never treated as SQL, which prevents SQL injection. The database can also cache and reuse the execution plan, and it handles types like dates correctly. Statement with string concatenation is unsafe and slower for repeated queries, so it should not be used with user input.

Checked exceptions extend Exception (but not RuntimeException) and must be caught or declared with throws, for example IOException and SQLException. Unchecked exceptions extend RuntimeException, such as NullPointerException and IllegalArgumentException, and need no declaration. Use checked exceptions for recoverable conditions callers must handle and unchecked ones for programming errors. Errors like OutOfMemoryError should not be caught.

A deadlock happens when two or more threads each hold a lock and wait for a lock held by the other, so none can continue. It needs mutual exclusion, hold and wait, no preemption and circular wait. Prevent it by always acquiring locks in the same global order, using tryLock with a timeout, holding locks briefly and avoiding calls to unknown code while holding a lock.

Transient: a new object not yet linked to a persistence context. Managed (persistent): attached to the context, so changes are tracked and flushed automatically through dirty checking. Detached: was managed but the context closed or it was evicted; changes are not tracked until merge(). Removed: scheduled for deletion on flush. persist, merge, detach and remove move entities between these states.

An abstract class can have state (instance fields), constructors and any access modifier, and a class can extend only one. An interface has no instance state but, since Java 8, can have default and static methods, and since Java 9 private methods; a class can implement many. Use an interface for a capability contract and an abstract class to share code and state among closely related classes.

Lazy loading fetches an association only when it is first accessed, using a proxy; eager loading fetches it immediately with the parent. In JPA, @ManyToOne and @OneToOne default to EAGER, while @OneToMany and @ManyToMany default to LAZY. Best practice is to make all associations lazy and fetch what each use case needs with JOIN FETCH or entity graphs, which avoids loading huge object graphs.

Optional is a container that may or may not hold a value, used mainly as a method return type to show that a result can be absent, for example findById. Use map, filter, orElse, orElseGet and orElseThrow instead of calling get() blindly. Do not use Optional for fields, parameters or collections, and prefer orElseGet when the default is costly to create.

Each += creates a new String and copies all previous characters, so building n rows is O(n squared) in time and creates huge garbage. Use a single StringBuilder with append() inside the loop, ideally with an initial capacity, or write rows directly to a BufferedWriter for very large output. This turns minutes of work into milliseconds.

Streams, readers or connections are opened but not closed on all paths, especially when an exception is thrown before close(). Check with lsof or jcmd which files are open. Fix by wrapping every resource in try-with-resources so it always closes, and make sure Files.lines() and Files.list() streams are closed too, since they hold file handles.

This breaks encapsulation. Return an unmodifiable view with Collections.unmodifiableList(list) or a copy with List.copyOf(list), so callers cannot change internal state. Also copy the list passed into the constructor or setter. If the class should be fully immutable, store List.copyOf in a final field. Expose specific methods like addItem() when controlled changes are needed.

The pool is exhausted. Check for connection leaks, where code holds connections without closing, by setting leakDetectionThreshold. Look for long transactions doing remote calls inside @Transactional, slow queries holding connections and a pool size too small for the thread count. Fix leaks, move external calls outside transactions, optimise slow queries and then size the pool from load tests.

count++ is not atomic; two threads can read the same value and both write the same result, so updates are lost. Use AtomicInteger.incrementAndGet(), which uses CAS, or LongAdder for very high contention, as it spreads updates over cells. A synchronized method also works but is slower. volatile alone does not fix it because it gives visibility, not atomicity.

Situation: I mentored two interns who struggled with OOP. Task: help them design classes for a library app. Action: I used real objects they knew, like Book and Member, showed encapsulation with private fields, then wrote one interface with two implementations to show polymorphism, and reviewed their code daily. Result: within two weeks they designed modules on their own and their pull requests needed fewer review comments.

Situation: a report job matching 2 lakh transactions to customers took 40 minutes. Task: bring it under the 5 minute window. Action: profiling showed list.contains() inside a loop, which was O(n squared). I loaded customer ids into a HashSet and grouped transactions with a HashMap. Result: runtime dropped to 50 seconds and I shared the pattern in our team wiki.

Situation: our reporting module had nested loops 200 lines long that new joiners feared. Task: make it maintainable without changing output. Action: I added snapshot tests on real report files, then refactored into small methods using streams, groupingBy and records for intermediate data, and reviewed each step with a teammate. Result: the module shrank by 40 percent and later changes took a day instead of a week.

Situation: a bulk upload feature had to go live in four days for a client launch. Task: build it safely in time. Action: I split it into must-have and later items, used an ExecutorService to process rows in parallel, wrote focused tests for validation and kept the product owner updated daily. Result: we shipped on time, it handled 50,000 rows in under two minutes and we added the extras next sprint.