JetBrains / skia

0	1210	4258	5754	5449	6015	6791	6776	7070	6094	5750	4509	5296	4369	2948	1881	189	401	25	2
0	61	114	115	105	81	109	99	93	100	113	110	98	35	40	24	10	8	2	1
2026	2025	2024	2023	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010	2009	2008	2006

	github actions npm gradle bazel make docker
Standard analyses:
		Main Code: 757,190 LOC (4891 files) = CPP (67%) + H (19%) + GO (2%) + PY (2%) + MM (1%) + JS (1%) + GN (<1%) + BZL (<1%) + GNI (<1%) + HTM (<1%) + HTML (<1%) + JAVA (<1%) + CC (<1%) + RS (<1%) + INC (<1%) + XML (<1%) + TS (<1%) + C (<1%) + JSON5 (<1%) + NATVIS (<1%) + SQL (<1%) + TOML (<1%) + CSS (<1%) + CFG (<1%) + LEX (<1%) + VERT (<1%) + PROTO (<1%) + PS1 (<1%) + M (<1%) + FRAG (<1%) Secondary code: Test: 290,920 LOC (2388); Generated: 24,206 LOC (14); Build & Deploy: 1,812 LOC (79); Other: 346,561 LOC (594);
		File Size: 22% long (>1000 LOC), 34% short (<= 200 LOC)
		Logical Component Decomposition: primary (22 components)
		19 years, 4 months old 99% of code older than 365 days 57% of code not updated in the past 365 days
		32% of code updated more than 50 times Also see temporal dependencies for files frequently changed in same commits.
		Goals: Keep the system simple and easy to change (4)
Experimental analyses (less reliable heuristic analyses):
		Unit Size: 13% long (>100 LOC), 40% short (<= 10 LOC)
		Conditional Complexity: 10% complex (McCabe index > 50), 54% simple (McCabe index <= 5)
		Static Component Dependencies: primary (22 components)

	Features of interest: TODOs 641 files

All Analysis Reports

Source Code Overview

Components

Temporal Dependencies

File Size

File Age & Freshness

File Change Frequency

Commits

Contributors

Unit Size*

Conditional Complexity*

Features of Interest

All Metrics

Goals & Controls

Duplication

Component Dependencies*

Trend

Notes & Findings

Overall Activity Per Year

Latest commit date: 2025-08-08

Reference analysis date: 2026-01-18

0

commits
(30 days)

0

contributors
(30 days)

0	1210	4258	5754	5449	6015	6791	6776	7070	6094	5750	4509	5296	4369	2948	1881	189	401	25	2
0	61	114	115	105	81	109	99	93	100	113	110	98	35	40	24	10	8	2	1
2026	2025	2024	2023	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010	2009	2008	2006

Activity Per File Extension

commits

	2026	2025	2024	2023	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010	2009	2008	2007	2006
		544	1906	3182	3008	3824	4550	3618	4054	4109	4300	3465	3321	3036	2444	1492	168	352	19		2	cpp
		461	637	350	242	251	158	150	187	160	51	2	55									go
		369	1239	2201	2134	2532	3200	2596	2844	2745	2909	2408	2257	1681	1408	857	95	181	7		2	h
		206	967	1124	442	26	55	52	83	154	139											bzl
gni		46	289	614	586	816	679	422	496	562	130											gni
cfg		36	7		6	97	103	661	363	227	51	10	7	12	6							cfg
		35	95	116	216	183	249	387	463	646	482	189	241	209	62	13	1					py
		32	127	157	235	271	252	370	108	40	24	17	31	23	42	32	1					mm
		28	80	30																		rs
gn		28	163	257	223	207	318	306	312	282	244											gn
		8	14	18		3																toml
		6	9	39	59	102	173	105	52			2	72	31								js
		4	7	18	32	74	85	57	46			1	79	36	9	1						html
		3	4	33	25	57	29															ts
frag		2	28	116	111	294	63		2													frag
		2	1	4	6	13	17	1	19	3	12	15	1	4		6		2				xml
		1	3	4	15	65	28	3	37	5	20	13	1	9		7						java
		1	6		1		32	37	27	2	1	2				1						inc
		1	8	26	6	9	6	36	21						1	1						cc
								1				1	30	14								css
			4		7	8	21	18														json5
vert			2	6	5	25	10		2													vert
							4															sql
					1			1														ps1
natvis				3	1		5															natvis
lex			4	1	12	19	6	5	1	9												lex
						4	6	2	96	15	15	20	13	22	43							htm
						2	2	6	87	17	18	7	3	4	7	5	1		2			c
								1		2				1	1	12		1				m
proto							4		1													proto

contributors

	2026	2025	2024	2023	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010	2009	2008	2007	2006
		49	85	87	71	58	75	66	66	70	90	87	86	34	38	23	10	7	1		1	cpp
		41	73	63	68	51	62	55	54	56	80	73	78	31	36	21	10	6	1		1	h
		14	21	22	20	20	21	13	14	10	8	2	7									go
gni		14	32	35	34	31	40	29	31	33	24											gni
		10	20	27	32	28	32	33	35	32	34	25	20	17	11	3	1					py
		10	19	23	16	14	22	18	12	9	11	12	10	10	8	8	1					mm
gn		9	28	27	35	32	40	30	34	31	25											gn
		8	8	5																		rs
		7	23	32	21	11	19	12	16	17	21											bzl
cfg		2	2		3	3	2	7	9	17	9	6	2	3	1							cfg
		2	3	4		1																toml
		2	6	15	17	14	14	7	3			2	7	4								js
		2	2	16	10	8	3															ts
		1	5	8	9	9	12	7	3			1	8	6	3	1						html
frag		1	5	4	9	8	3		1													frag
		1	1	3	3	3	6	1	6	2	6	6	1	2		3		1				xml
		1	3	3	6	3	5	1	6	3	6	4	1	4		3						java
		1	3		1		7	9	9	2	1	2				1						inc
		1	1	4	2	1	2	4	3						1	1						cc
								1				1	5	5								css
			3		3	2	4	6														json5
vert			2	2	2	3	3		1													vert
							2															sql
					1			1														ps1
natvis				2	1		1															natvis
lex			1	1	4	3	3	2	1	1												lex
						3	5	2	6	3	1	2	3	1	2							htm
						2	2	5	9	5	8	7	1	3	5	3	1		1			c
								1		2				1	1	3		1				m
proto							2		1													proto

Visual Code Explorers

MAIN (4891)	Circles	Sunburst
TEST (2388)	Circles	Sunburst
BUILD AND DEPLOYMENT (79)	Circles	Sunburst
GENERATED (14)	Circles	Sunburst
OTHER (594)	Circles	Sunburst

File Visualizations

File size views:

File age views:

	files grouped by age category files grouped by folder
	files grouped by freshness category files grouped by folder

File change frequency views:

Contributors per file views:

Contributor Visualizations

Contributor dependency views:

past 30 days: graphviz | 2D graph | 2D graph (with files) | 2D graph (with shared files only) | 3D graph | 3D graph (with files) | 3D graph (with shared files only)
past 3 months: graphviz | 2D graph | 2D graph (with files) | 2D graph (with shared files only) | 3D graph | 3D graph (with files) | 3D graph (with shared files only)
past 6 months: graphviz | 2D graph | 2D graph (with files) | 2D graph (with shared files only) | 3D graph | 3D graph (with files) | 3D graph (with shared files only)
past year: graphviz | 2D graph | 2D graph (with files) | 2D graph (with shared files only) | 3D graph | 3D graph (with files) | 3D graph (with shared files only)

Components and Dependencies Visualizations

Components

Temporal Dependencies

Duplication

Commits Racing Charts

30 days

3 months

6 months

PRIMARY (22)

Bubble Chart

Tree Map

graphviz

2D

3D

graphviz

2D

3D

graphviz

2D

3D

Duplication Graph

All Time

12 Months

File Dependencies Visualizations

Temporal dependencies among files:

past 30 days: no dependencies
past 3 months: no dependencies
past 6 months: graphviz | 2D graph | 2D graph (with commits) | 3D graph | 3D graph (with commits)

Units Visualizations

Unit size and conditional complexity views:

Lists of Files Per Scope

Analysis Results

CONFIGURATION: JSON
ALL ANALYSIS RESULTS: JSON
DUPLICATES: TXT | JSON
UNITS: TXT | JSON
CONTRIBUTORS: TXT | JSON
LOGICAL DECOMPOSITIONS: JSON
CONCERNS: JSON
CONTROLS: TXT
ALL METRICS: TXT

Zipped Files

GIT HISTORY: ZIP
ALL FILES IN ALL ANALYSIS SCOPES: ZIP

Generative AI tools, like ChatGPT or Gemini, can help you explore and discuss various aspects of source code repositories using simple prompts and file uploads. Sokrates provides you with curated data that you can use to analyze your source code further.

Example Prompt 1: Repository Evolution Analyzer (based on git history)

Try on: OpenAI ChatGPT | Claude.ai Chat | Google Gemini

Files to upload: git-history.zip

Prompt:

You are an experienced software architect tasked with analyzing Git commit history.
Context:
- Repository Name: JetBrains / skia
- Repository Description: Skia is a complete 2D graphic library for drawing Text, Geometries, and Images.
- Data Provided: A plain text file containing Git commit records. Source code is not available.
- Analysis Basis: Your analysis must be based solely on inferring context from the provided file paths, file names, file extensions, commit timestamps, and author information within the commit records.

Input Format:
The commit records are provided in the following format per line:
[YYYY-MM-DD] [author email] [commit hash] [file path changed]

Requested Insights:

Please analyze the provided commit history and generate a report covering the following sections:

1. Management Summary
- Provide a concise, high-level overview suitable for non-technical stakeholders.
- Summarize the repository's likely purpose, main development phases observed, and key takeaways about the team structure/activity.

2. Functional Overview
- Based only on file/module/class names, infer and describe the primary functions and capabilities of the software in this repository.
- What services or features does the codebase seem to support?

3. Key Business/Domain Concepts
- Identify and list core business or domain concepts reflected in the file and directory names (e.g., reporting, analytics, data export, user management, sourcecode analysis, landscape, visualization).

4. Inferred Architecture & Design
- Infer potential architectural patterns (e.g., modular, layered, microservices) based on directory structures and file naming conventions.
- Highlight notable design choices evident from the structure, such as separation of concerns (e.g., common module), use of configuration files, or templating engines.

5. Inferred Technology Stack
- List the programming languages, frameworks, libraries, and tools likely used, based on file extensions (.java, .py, .js, .html, .xml, .yml, pom.xml, dockerfile), configuration files, and common directory structures (e.g., /src/main/java).
- Categorize these technologies where possible (e.g., Backend, Frontend, Build, Infrastructure).

6. Logical Components / Modules
- Identify the major logical components or modules suggested by the directory structure (e.g., codeanalyzer, reports, cli, common, web).
- Briefly describe the inferred purpose of each major component.

7. Evolution by Year
- Summarize the apparent focus of development activity for each year present in the commit history.
- Assign a thematic title to each year (e.g., "Year 1: Foundation & Core Analysis", "Year 2: Reporting & Visualization Expansion").

8. Trends Over Time
Identify and describe significant trends observed across the years, such as:
- Shifts in technology usage (e.g., introduction of Docker).
- Changes in module activity (e.g., increased focus on landscape analysis).
- Signs of project maturity, expansion into new areas, or periods of focused maintenance.
9. Team Dynamics
- Analyze contributor patterns based on author emails and commit frequency:
 - Identify core maintainer(s) vs. occasional contributors.
 - Describe observable contribution trends (e.g., stable team, high turnover, reliance on a single developer).
 - Note any appearance of automated contributors (e.g., Dependabot).
10. Risk Analysis:
- Based on the findings in all previous sections (Team Dynamics, Technology, Architecture, Evolution), identify potential key risks for the project.
- Examples: Key person dependency, technology obsolescence, maintainability challenges due to complexity, potential scalability bottlenecks, bus factor.

Input File:
You will receive the commit records in a plain text file. Please parse this file to perform your analysis.

Example Prompt 2: File name conventions

Try on: OpenAI ChatGPT | Claude.ai Chat | Google Gemini

Files to upload: files.json

Prompt:

Example Prompt 3: Technology analyzer (based of file paths)

Try on: OpenAI ChatGPT | Claude.ai Chat | Google Gemini

Files to upload: files.json

Prompt:

Analyze the provided list of file paths to identify as many technologies, frameworks, tools, programming languages, cloud services, and architectural patterns used in the project as possible.

**Input:**
Please analyze the following list of file structures (provided as a list of strings or a JSON object containing file paths and optionally extensions/metadata):

*(Example: A JSON array like the one previously provided, or a simple list like `["src/server.ts", "Dockerfile", "tests/e2e/spec.cy.js", "infra/main.tf"]`)*

**Analysis Instructions:**
When performing the analysis, please consider the following:

1. **File Extensions:** Identify languages and configuration types (e.g., `.ts`, `.js`, `.py`, `.java`, `.tf`, `.yml`, `.hcl`, `.css`, `.html`).
2. **Directory Structure & Naming:** Look for conventional directory names (`src`, `tests`, `infra`, `docs`, `cicd`) and names indicating specific components or frameworks (`packages/bff`, `features`, `controllers`, `services`, `cypress`).
3. **Specific Filenames:** Identify standard configuration or definition files (e.g., `package.json`, `pom.xml`, `docker-compose.yml`, `Dockerfile`, `Jenkinsfile`, `webpack.config.js`, `tsconfig.json`, `requirements.txt`, `terragrunt.hcl`, `lint-staged.config.js`, `commitlint.config.js`).
4. **Keywords in Paths:** Look for names of known technologies, tools, frameworks, or cloud providers within the paths (e.g., `aws`, `azure`, `lambda`, `sqs`, `react`, `nest`, `k6`, `datadog`, `pm2`).

**Output:**
Please present the findings as a list of identified technologies. If possible, group them into relevant categories such as:

* Programming Languages
* Frameworks & Runtimes
* Testing Tools
* Infrastructure as Code / Cloud Providers
* Containerization & Orchestration
* Build Tools / Bundlers
* Databases (if identifiable)
* Monitoring & Logging
* CI/CD & Dev Tools
* Architectural Patterns