Analytical Methodology: A Structured, Standards-Based Framework for Technology Litigation
The same framework applied across 37 years of technology leadership and 14 years of litigation expert work. Systematic. Objective. Reproducible.
The Core Framework
Bruce Weiner’s expert methodology follows the same structured analytical approach he has applied across 37 years of technology leadership: Establish clear questions → Apply experience and recognized frameworks → Gather and review extensive documentary evidence → Measure processes against articulated goals and standards → Synthesize reproducible conclusions.
This approach — described in federal MDL litigation as a structured analysis that mirrors the analysis used across large-scale technology-driven organizations — produces opinions that are systematic, objective, and reproducible. The methodology survived Daubert challenge on grounds of qualification, methodology, and relevance (N.D. Cal., January 6, 2026).
“Mr. Weiner’s expertise in product development is just right.” — Plaintiffs’ Counsel, In gig-economy MDL, N.D. Cal., December 10, 2025
Five-Step Analytical Process
Frame the Questions
01Define the scope and the product development or governance issues at issue. What standard applies? Was it followed? If not, what was the causal consequence? This framing discipline ensures every document reviewed and every opinion rendered is traceable to a specific, answerable technical question.
Establish Inclusion and Exclusion Criteria
02Apply experience-based judgment to identify relevant document types: OKRs, planning documents, sprint artifacts, testing records, post-deployment performance data, server logs, source code modules, billing records.
Gather Documentary Evidence Systematically
03Staged search process — broad then refined — pulling only document types meeting pre-established criteria. Substantial weight given to the organization’s own internal records. Programmatic analysis tools applied for large productions (Python, AWS cloud infrastructure).
Apply Recognized Frameworks and Benchmarks
04Benchmark findings against ISO/IEC 12207, ISO 31000, ISO/IEC 25010, IEEE 730, IETF RFC standards, and OWASP. Apply IFPUG Function Point Analysis (ISO/IEC 20926:2009) where labor benchmarking is required.
Synthesize and Test Conclusions
05Form opinions grounded in documented evidence, professional judgment, and standards benchmarks. Apply hypothesis-testing: formulate hypothesis → test against evidence → refine → confirm or reject. Mirrors the scientific method. Ensures opinions rest on a foundation broader than personal observation alone.
Technical Analysis Methods
Source Code Review
Direct examination of source code in disputes involving software systems. Module-level analysis of specific functions and their behavior. HTTP request composition and API interaction analysis. Authentication and session management code review. Automation and scheduling logic evaluation.
Applied in: web scraping disputes, platform API access cases, software development methodology cases.
Web Server Log & API Traffic Analysis
Analyzing system logs and network traffic captures to establish patterns. Amazon Lambda execution logs and API Gateway log review. Fiddler Everywhere and similar proxy capture analysis. Rate pattern analysis — distinguishing human from automated access.
Applied in: web scraping disputes, system performance claims, API access authorization disputes.
Large-Scale Document Production Analysis
Programmatic analysis for large document productions. Python-based document structure examination (openpyxl, pandas). AWS cloud infrastructure for PST and file analysis. Excel workbook version history and cell storage format analysis.
Applied in: consulting billing disputes, SDLC governance cases, complex commercial litigation.
Standards Applied
| STANDARD | APPLICATION |
|---|---|
| ISO 31000:2018 | Risk management — foreseeable risk governance in product development |
| ISO/IEC 12207:2017 | Software lifecycle processes — primary SDLC/PDLC benchmark |
| ISO/IEC 25010:2023 | Software quality model — suitability, performance, security |
| IEEE 730:2014 | Software quality assurance plan requirements |
| ISO/IEC 20926:2009 | Function Point Analysis — system sizing and labor benchmarking |
| ISO 20700:2017 | Management consulting guidelines — deliverable substantiation |
| ISO/IEC Guide 51:2014 | Safety aspects in standards — risk reduction requirements |
| ISO/IEC 42001 | AI management systems |
| IETF RFC 7231 | HTTP/1.1 semantics — web API standards |
| OWASP | Web application security standards |
| NIST AI RMF | AI risk management framework |
Rule 702 Alignment
This methodology produces opinions consistent with Federal Rule of Evidence 702: testable standards benchmarks, peer-reviewed consensus frameworks, known quality criteria, and general acceptance across the global software engineering community. Bruce’s 37 years of applying these frameworks in production environments — not theoretical study — is the foundation of every opinion.