Executive Summary

This report presents detailed performance data for five candidates considered for a Full-Stack Developer role. Over the course of one week, each candidate worked on tasks covering both frontend and backend responsibilities, wrote and optimized code, debugged issues, and interacted with a collaborative communication platform.

The following tables, charts, and qualitative notes detail task completion rates, code quality metrics, debugging times, productivity patterns, and communication quality. Each skill level (e.g., "Advanced") corresponds to specific quantitative criteria, such as percentage of tasks completed on the first attempt, maintainability scores, and response times to detected issues.

Readers can review the evidence to form their own conclusions about which candidate best meets their organizational needs.

At a Glance

Candidate	Overall Score	Frontend Skill Level	Backend Skill Level	Debugging Efficiency	Code Quality
Candidate 1	85%	Advanced	Intermediate	8/10	9/10
Candidate 2	80%	Intermediate	Intermediate	7/10	8/10
Candidate 3	90%	Advanced	Advanced	9/10	9/10
Candidate 4	75%	Intermediate	Basic	5/10	6/10
Candidate 5	88%	Advanced	Intermediate	8/10	9/10

Skill Level Criteria

Advanced: Over 90% of tasks completed successfully on first attempt, high test pass rates (>95%), minimal rework, and consistently low error rates.
Intermediate: 60-89% task completion on first attempt, moderate complexity handled with occasional guidance needed, some minor rework required.
Basic: Less than 60% successful first-attempt completion, frequent rework, and recurring issues that slow down progress.

Data Sources & Measurements

Task Completion: Percentage of assigned tasks completed correctly on the first attempt, based on code reviews and test reports.
Code Quality: Measured by maintainability scores (e.g., >85% for high quality), lint error counts, and adherence to established coding conventions.
Debugging Efficiency: Average time to resolve issues, complexity of bugs fixed, and number of successful fixes relative to attempts.
Productivity Metrics: Hours of focused coding per day, number and length of breaks, and peak productivity hours identified by activity logs.
Communication Quality: Responsiveness and clarity in collaboration channels, as inferred from Slack transcripts and code review comments.

Individual Candidate Performance Details

Candidate 1

Candidate 1 completed 19/20 frontend components on the first attempt, demonstrating proficiency in implementing responsive designs and reusable patterns. Backend tasks (14/20 on the first attempt) required iterative improvements, particularly in query optimizations. Debugging logs show efficient resolution of common issues within ~10-15 minutes. Code quality is reflected in a maintainability score of 85%, with lint errors at <2%.

Evidence Highlights:
- Frontend tasks (#5, #8): Reusable React components integrated, passing 95% UI tests.
- Backend commits (#14, #17): Incremental improvements to API routes after initial performance checks.
- Debug Log (Day 3): CORS issue resolved in under 10 minutes.
- Productivity: Averaged 6 hrs coding/day, 3 short breaks/day, peak productivity from 10 AM to 1 PM.

Metric	Score / Level	Quantitative Data
Frontend Tasks	Advanced	95% success first attempt, 19/20 tasks passed QA
Backend Tasks	Intermediate	70% success first attempt, optimization required in 3/10 APIs
Code Quality	9/10	Maintainability: 85%, Lint errors <2%< /td>
Debugging Efficiency	8/10	15/18 issues fixed <15 min each
Productivity	85%	~6hrs coding/day, 3 breaks/day, peak hours: 10AM-1PM

Overall: 85%

Candidate 2

Candidate 2 successfully completed 16/20 frontend tasks and 15/20 backend tasks on the first attempt. While less consistently achieving top-tier results compared to advanced candidates, this intermediate performance was stable. Debugging logs indicate a moderate resolution speed. Code quality remains solid with minimal linting errors and a maintainability score of 80%.

Evidence Highlights:
- Frontend test logs show 80% first-pass success on UI components.
- Backend integrations required adjustments after initial review (commits #12, #15).
- Typical bug fix time: ~20 minutes for medium complexity issues.
- Productivity: ~5.5 hrs coding/day, 2 breaks/day, stable performance mid-afternoon.

Metric	Score / Level	Quantitative Data
Frontend Tasks	Intermediate	80% success first attempt, 16/20 tasks
Backend Tasks	Intermediate	75% success first attempt, slight rework on queries
Code Quality	8/10	Maintainability: 80%, Lint errors <3%< /td>
Debugging Efficiency	7/10	12/16 issues <20 min each, some reliance on trial and error
Productivity	80%	~5.5hrs coding/day, 2 breaks/day, peak hours: 2PM-4PM

Overall: 80%

Candidate 3

Candidate 3 completed nearly all assigned tasks at a high standard on the first attempt. Frontend and backend work showed consistently robust implementation, including handling microservices and responsive UI without rework. Debugging times averaged under 10 minutes, even on complex issues. Code quality scores were among the highest, with a maintainability rating of 92%.

Evidence Highlights:
- All critical APIs delivered with <200ms latency (perf tests #10, #11).
- 98% UI components passed automated tests on first run.
- Complex concurrency bug resolved in ~10 minutes (commit diffs #11-#12).
- Productivity: ~6.5hrs coding/day, 3 breaks/day, consistently high output across morning and early afternoon.

Metric	Score / Level	Quantitative Data
Frontend Tasks	Advanced	98% success first attempt, responsive UI verified by tests
Backend Tasks	Advanced	All endpoints optimized on first pass, <200ms latency
Code Quality	9/10	Maintainability: 92%, negligible lint errors
Debugging Efficiency	9/10	Most issues resolved <10 min, including complex async errors
Productivity	88%	~6.5hrs coding/day, 3 breaks/day, stable output 9AM-2PM

Overall: 90%

Candidate 4

Candidate 4 completed a majority of frontend tasks but required multiple corrections before passing quality checks. Backend tasks presented more significant challenges, with only about half completed successfully on the first attempt and some recurring issues with data handling. Debugging logs show slower resolution times, often exceeding 30 minutes for moderate errors. Code quality metrics were modest, with a maintainability score of 70%.

Evidence Highlights:
- Frontend completion ~75%, some styling and responsiveness issues addressed in later commits.
- Backend complexity (authentication, DB queries) required multiple reworks (commits #8, #9, #13).
- Frequent reliance on trial-and-error debugging extended resolution times.
- Productivity: ~5hrs coding/day, 4 breaks/day, peak focus late morning but dip in late afternoon.

Metric	Score / Level	Quantitative Data
Frontend Tasks	Intermediate	75% success, multiple UI refinements needed
Backend Tasks	Basic	50% success first attempt, repeated data handling issues
Code Quality	6/10	Maintainability: 70%, occasional style deviations
Debugging Efficiency	5/10	Many issues >30 min to resolve, some recurring bugs
Productivity	75%	~5hrs coding/day, 4 breaks/day, productivity varies widely by day

Overall: 75%

Candidate 5

Candidate 5 completed most frontend tasks efficiently and achieved strong code quality in UI components. Backend tasks were generally solid, though a few endpoints required second-pass optimizations. Debugging times were respectable, averaging ~12 minutes per issue. Code quality metrics show a maintainability score of 88%. Productivity data indicates a consistent output with focused bursts in the early afternoon.

Evidence Highlights:
- Frontend: 90% first-attempt success, minor styling fixes after initial pass.
- Backend: Achieved solid API performance after minor adjustments (commit #16, #19).
- Debug logs: Typical medium-complexity issues solved <15 min.
- Productivity: ~6hrs coding/day, 2-3 breaks/day, peak hours: 1PM-3PM.

Metric	Score / Level	Quantitative Data
Frontend Tasks	Advanced	90% success, responsive and accessible designs
Backend Tasks	Intermediate	85% success, minor API refactoring needed
Code Quality	9/10	Maintainability: 88%, few lint warnings
Debugging Efficiency	8/10	Majority of issues <15 min to fix
Productivity	88%	~6hrs coding/day, 2-3 breaks/day, strong early-afternoon focus

Overall: 88%

Overall Performance Comparison

Composite scores based on task completion, code quality, debugging speed, and productivity. Each score reflects a weighted average of these core metrics.

Debugging Efficiency Over Time

Tracks the average time to resolve issues and the proportion of successful fixes per day. Lower times and higher fix rates suggest strong problem-solving capabilities.