∫Calc Practice

Derivative of \( \displaystyle x \ln{\left(x \right)}^{2} - 2 x \ln{\left(x \right)} + 2 x \)

Problem 2.1505 · hard Beautiful

Differentiate \( \displaystyle f(x) = x \ln{\left(x \right)}^{2} - 2 x \ln{\left(x \right)} + 2 x \).
  1. \[ \frac{d}{d x} \left(x \ln{\left(x \right)}^{2} - 2 x \ln{\left(x \right)} + 2 x\right) \]
    Start with the derivative of the function.✓ Proved
  2. \[ = \frac{d}{d x} 2 x - \frac{d}{d x} 2 x \ln{\left(x \right)} + \frac{d}{d x} x \ln{\left(x \right)}^{2} \]
    sumApply the sum rule.✓ Proved
  3. \[ = \frac{d}{d x} 2 x - 2 \frac{d}{d x} x \ln{\left(x \right)} + \frac{d}{d x} x \ln{\left(x \right)}^{2} \]
    constant-multipleFactor out the constant 2.✓ Proved
  4. \[ = - 2 \frac{d}{d x} x \ln{\left(x \right)} + \frac{d}{d x} x \ln{\left(x \right)}^{2} + 2 \]
    constantThe derivative of 2*x is 2.✓ Proved
  5. \[ = - 2 x \frac{d}{d x} \ln{\left(x \right)} + x \frac{d}{d x} \ln{\left(x \right)}^{2} + \ln{\left(x \right)}^{2} \frac{d}{d x} x - 2 \ln{\left(x \right)} \frac{d}{d x} x + 2 \]
    productApply the product rule to each term.✓ Proved
  6. \[ = - 2 x \frac{d}{d x} \ln{\left(x \right)} + x \frac{d}{d x} \ln{\left(x \right)}^{2} + \ln{\left(x \right)}^{2} - 2 \ln{\left(x \right)} + 2 \]
    constant algebra algebraThe derivative of x is 1. Simplify the expression. Distribute the -2.✓ Proved
  7. \[ = 2 x \ln{\left(x \right)} \frac{d}{d x} \ln{\left(x \right)} - 2 x \frac{d}{d x} \ln{\left(x \right)} + \ln{\left(x \right)}^{2} - 2 \ln{\left(x \right)} + 2 \]
    chainApply the chain rule to log(x)**2.✓ Proved
  8. \[ = \ln{\left(x \right)}^{2} \]
    logarithmic algebra algebra algebra algebra simplifyThe derivative of log(x) is 1/x. Rewrite the fraction. Simplify x/x. Combine the log(x) terms. Simplify 2*x*(1/x). Final simplification.✓ Proved
Answer \( \ln{\left(x \right)}^{2} \)

Every line of this solution was proved by the computer algebra system SymPy. The answer was also checked a second way, without looking at the solution. The reviewers disagree about how one step is explained; every verdict is in the receipt.

The full receipt
LineStatusChecked byDetail
1✓ Provedsympy 1.14.0line 1 is the problem as stated
2✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
3✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
4✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
5✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
6✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
7✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
8✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
9✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
10✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
11✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
12✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
13✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
14✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
15✓ Provedsympy 1.14.0simplify(a - b) reduced to 0
log is undefined for non-positive arguments
answer✓ Provedsympy 1.14.0final line against the stated answer: simplify(a - b) reduced to 0
log is undefined for non-positive arguments
answer, a second way✓ Provedsympy 1.14.0SymPy differentiated f directly and got the stated answer

Reviewers

  • gpt-oss:20b: fail (error) — Step 5 applies the product rule to two separate terms in a single line, violating the rule that each step must change only one thing. The label "product" is appropriate for each application, but combining them in one step is an error.
  • qwen3.6:27b-mlx: pass — The solution correctly applies differentiation rules step-by-step, adhering to the one-change-per-step constraint. All labels are appropriate for the transformations performed.
Every verdict on record (4)
  • qwen3.6:27b-mlx: pass 2026-10-04 — The solution correctly applies differentiation rules step-by-step, adhering to the one-change-per-step constraint. All labels are appropriate for the transformations performed.
  • gpt-oss:20b: fail (error) 2026-10-04 — Step 5 applies the product rule to two separate terms in a single line, violating the rule that each step must change only one thing. The label "product" is appropriate for each application, but combining them in one step is an error.
  • qwen3.6:27b-mlx: pass 2026-10-04
  • gpt-oss:20b: pass 2026-10-04

Proved: SymPy reduced the difference between the two sides to zero. Checked independently: a separate method, named above, confirmed it. Checked numerically: the two sides agree at every sampled point, which is evidence, not proof. Reviewed: a model or a person read it; that is all a sentence can have. Solution by gemma4:26b, checked 2026-10-04 with SymPy 1.14.0.