Detecting Memory Leaks CTAL-TTA Practice Questions (Page 4)

Questions 16–20

1. 16foundation · easy

   In a garbage-collected language, which coding practice helps prevent memory leaks caused by event listeners or callbacks?

   • AIncreasing the heap size to accommodate the extra memory used by listeners.
   • BDeclaring all event handlers as static methods to avoid instance references.
   • CUsing only anonymous functions for event handlers to avoid naming conflicts.
   • DUnregistering event listeners or callbacks when they are no longer needed.
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2. 17expert · hard · select all that apply

   A test analyst is investigating a suspected memory leak in a Java application. Which dynamic analysis techniques are appropriate to confirm the leak? (Select all that apply.)

   • AUsing a code coverage tool to measure test coverage
   • BMonitoring garbage collection logs for increasing heap usage
   • CHeap profiling with a tool like Eclipse MAT
   • DRunning a static code analysis tool like SpotBugs
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4. 18expert · hard

   A team is developing a microservices application in Java. One service experiences memory leaks due to improper use of a shared cache. The team wants to prevent leaks without affecting performance. Which approach is most effective?

   • AUse a static cache without any eviction
   • BIncrease the heap size to accommodate the cache
   • CClear the entire cache after each request
   • DUse a bounded cache with eviction policy (e.g., LRU)
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5. 19expert · hard

   A static analysis tool reports a potential memory leak in a C++ codebase, but the developers believe it is a false positive. The code uses a custom smart pointer class. What is the best way to verify whether the report is a true leak?

   • AAdd more comments to the code to clarify ownership
   • BIgnore the report because static analysis often produces false positives
   • CRun a dynamic analysis tool like Valgrind on the specific code path
   • DReview the code manually to see if the smart pointer is used correctly
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6. 20expert · hard

   A .NET application's memory usage grows steadily in production, but the test team cannot reproduce the leak in a test environment. They suspect the leak is related to specific user actions. Which dynamic analysis approach is most appropriate to identify the leak in production?

   • AAttach a production profiler to capture heap snapshots during user activity
   • BRun static analysis on the production code
   • CIncrease the production heap size to prevent the leak
   • DAdd extensive logging to the production code
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