diff --git a/.idea/.gitignore b/.idea/.gitignore
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+# Default ignored files
+/shelf/
+/workspace.xml
+# Ignored default folder with query files
+/queries/
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml
+# Editor-based HTTP Client requests
+/httpRequests/
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diff --git a/Answers.md b/Answers.md
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+## Question 1
+An atomic variable in Computer Science refers to a basic data or input variable that is used to build performance variables. These variables are not summaries or ratios, but rather fundamental building blocks in operational systems.
+
+Atomic variables allow multiple threads to safely read and update a shared value without using explicit locks, guaranteeing that operations like increment-and-update happen as a single, uninterruptible step. Ordinary variables don't provide this guarantee—if multiple threads modify them concurrently, updates can be lost due to race conditions.
+
+## Question 2
+`AtomicInteger`
+
+`AtomicLong`
+
+`AtomicBoolean`
+
+`AtomicReference` for any type of object.
+
+## Question 3
+| | Locks (`synchronized`/`ReentrantLock`) | Atomic Variables |
+|---|---|---|
+| Mechanism | Blocking (mutual exclusion) | Lock-free |
+| Scope | Can protect multiple statements/variables | Single variable only |
+| Performance | Slower under contention | Generally faster |
+| Deadlock risk | Possible | None |
+| Best for | Complex critical sections | Simple counters, flags, single values |
+
+## Question 4
+A program can be completely free of race conditions yet still perform poorly, because the very mechanisms used to guarantee correctness — such as locks or CAS — introduce overhead. When many threads compete for the same shared resource, they end up **blocking or repeatedly retrying**, which sharply reduces throughput even though correctness is fully preserved.
+
+Some concurrency-related factors that may limit scalability even when correctness iss guaranteed:
+
+1. Lock contention
+2. Context switching overhead
+3. Cache coherence traffic
+
+## Question 5
+Despite the three factors given in the previous question there is a vital factor which is **limited CPU cores**.
+
+once threads exceed available cores, they compete for the same processing units, adding scheduling overhead instead of true parallelism.
+
+Context-switching overhead – the OS spends more time switching between threads than executing actual work.
+
+Cache coherence traffic – shared/false-shared memory locations cause costly cross-core cache invalidation.
+
+## Question 6
+A precise timing where two or more threads each acquire one lock and then attempt to acquire the other's lock simultaneously.
+
+1. Stress testing with high concurrency – run many more threads than in normal testing.
+2. Deliberate interleaving control / thread scheduling tools – use tools or techniques that artificially manipulate thread timing to force specific interleavings, such as:
+ Inserting `Thread.sleep()` or `yield()` calls strategically between lock acquisitions.
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