Structured feedback for: Data Structures — Lab Report on SLL vs DLL Performance
Strengths
- Executable, functioning code for both Singly Linked List (SLL) and Doubly Linked List (DLL).
- Clear, readable charts; axes and legends improve interpretability.
- The report maintains focus on operation-level performance comparison.
Gaps
- Time complexity analysis is incomplete by operation and list type; theoretical baselines are not fully articulated.
- Boundary and exceptional cases are missing from the discussion (e.g., empty list, single-node lists, deletion at head/tail, non-existent key).
- Some aspects of experimental control and reporting are unclear (e.g., number of trials, input distributions, hardware/compiler settings).
Scores and rationale
1) Problem Definition (20%) — 17/20
- Positives: The core objective—to compare SLL and DLL operation performance—is clear and relevant to the course outcomes.
- Shortfalls: The problem statement does not fully specify comparison metrics (e.g., runtime vs. memory overhead), the operation set under test, or the workload model (random vs. structured sequences).
2) Methods & Implementation (40%) — 34/40
- Positives: Both data structures are implemented and demonstrated; the program runs end-to-end; operations appear correctly implemented for empirical comparison.
- Shortfalls: It is not clear whether the implementation isolates per-operation timing (avoiding confounds like I/O) or whether memory overhead was instrumented. Boundary-aware test hooks (e.g., forced head/tail deletions) are not evident.
3) Experimental Design (20%) — 16/20
- Positives: Visualization is strong; figures support comparative interpretation.
- Shortfalls: The design description lacks detail on input sizes (scaling plan), repetition count, warm-up/discard policy, and controls (hardware, compiler flags, build type). Workload characteristics (read/write mix, operation distribution) are not fully reported.
4) Results Analysis (20%) — 12/20
- Positives: Empirical results are presented and discussed at a high level.
- Shortfalls: Big-O analysis is incomplete and not mapped operation-by-operation. The discussion omits boundary and exceptional behaviors that materially affect performance and correctness. The empirical trends are not consistently cross-validated against theoretical expectations.
- Expected theoretical baselines to include in analysis:
- Search: O(n) for SLL and DLL.
- Insert at head: O(1) for SLL and DLL.
- Insert at tail: O(1) for DLL (with tail pointer); SLL is O(1) only if a maintained tail pointer exists, otherwise O(n).
- Delete by key: O(n) for both; delete-given-node is O(1) for DLL and O(1) for SLL only if the predecessor is known.
- Reverse traversal: supported in DLL (O(n)), not directly in SLL.
- Space per node: DLL incurs one extra pointer over SLL.
Improvement checklist (≤5 items)
1) Complete the complexity matrix by operation and structure, and reconcile empirical curves with the expected Big-O behaviors (including notes on constant-factor differences).
2) Add and report boundary/exception tests: empty list, single-node list, head/tail insertions and deletions, deleting non-existent keys, duplicate keys.
3) Strengthen experimental controls and reporting: input sizes, number of trials, random seed/workload mix, warm-up strategy, hardware/OS, compiler and optimization flags; report mean and variance.
4) Isolate measurement effects: remove I/O from timed regions, preallocate where appropriate, and use high-resolution timers; repeat enough times to reduce noise.
5) Include memory overhead in the comparison: per-node space cost and, if feasible, peak memory usage during test runs.
Terminology used consistently: SLL (Singly Linked List), DLL (Doubly Linked List), operation (insert, delete, search, traverse), boundary case, exceptional case, workload, Big-O time complexity.
