JetBrains / android

7	5974	15420	8805	7355	11438	18588	26359	16407	19906	28879	21166	17290	6304	2245	1062	309
6	255	230	240	225	193	180	192	179	155	152	112	66	36	28	19	11
2026	2025	2024	2023	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010

	gradle bazel renovate
Standard analyses:
		Main Code: 1,870,017 LOC (36221 files) = KT (51%) + JAVA (31%) + XML (13%) + KTS (<1%) + PROTO (<1%) + CC (<1%) + BZL (<1%) + H (<1%) + PY (<1%) + TOML (<1%) + FLEX (<1%) + CPP (<1%) + DCL (<1%) + NSI (<1%) + HTML (<1%) + JS (<1%) + YAML (<1%) + NSH (<1%) + SMALI (<1%) + C (<1%) + PRO (<1%) + RS (<1%) + XSD (<1%) + CSS (<1%) + CFG (<1%) + GROOVY (<1%) Secondary code: Test: 148,440 LOC (2149); Generated: 12,478 LOC (31); Build & Deploy: 46,559 LOC (3801); Other: 2,156,631 LOC (3078);
		File Size: 7% long (>1000 LOC), 56% short (<= 200 LOC)
		Logical Component Decomposition: primary (132 components)
		15 years, 3 months old 94% of code older than 365 days 48% of code not updated in the past 365 days
		12% 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: 3% long (>100 LOC), 57% short (<= 10 LOC)
		Conditional Complexity: 1% complex (McCabe index > 50), 85% simple (McCabe index <= 5)
		Static Component Dependencies: primary (132 components)

	Features of interest: TODOs 886 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: 2026-01-12

Reference analysis date: 2026-01-18

18

commits
(30 days)

14

contributors
(30 days)

7	5974	15420	8805	7355	11438	18588	26359	16407	19906	28879	21166	17290	6304	2245	1062	309
6	255	230	240	225	193	180	192	179	155	152	112	66	36	28	19	11
2026	2025	2024	2023	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010

Activity Per File Extension

commits

	2026	2025	2024	2023	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010
	4	3816	11399	6283	5036	7530	11410	12793	6531	1425	86	182	52					kt
	1	1818	4484	3028	2793	5142	9490	17357	12128	18409	27459	19781	15919	5782	2099	978	289	java
	1	502	1271	935	743	1025	2062	2824	1291	1935	2549	2988	2683	1157	413	124	53	xml
		187	306	85	60	58	78											bzl
		103	234	145	119	9	4											cc
		73	143	94	46	256	396	498	124	121								kts
		68	110	94	76	2	12	4	8	20		2	25	14				h
		38	136	51	30	85	95	10	3									py
dcl		35	91															dcl
		32	15	1				12		6								yaml
proto		30	92	32	27	21	18	18	40									proto
		23	80	85	11	8												toml
		17	23	17	8	10	36	82	54	34	48	44	23	30	6	4	5	html
pro		17	34	32	22	28	75	169	43	124	56	67	116					pro
flex		11	60	7	16	8	11	86	8	52	30	42	17	4				flex
		11	6	15	6	3	26	10	10	22		13	52	14				cpp
nsi		3	20	7	5	6	28	38	4	4	28	80	31					nsi
cfg		3	42	21	7	1	6	8			4	7	2	1	2			cfg
		2													28			groovy
		1																css
							6		4	2			9	2				rs
nsh			3									16	18					nsh
smali										10								smali
xsd														1		6	1	xsd
								2	4									js
			3	2	3	4	12	8	4	35	12	4	12	5				c

contributors

	2026	2025	2024	2023	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010
	4	196	190	196	182	151	141	128	115	61	8	11	4					kt
	1	162	159	162	158	143	144	168	152	140	145	102	64	34	28	19	11	java
	1	109	113	116	113	90	97	102	83	79	66	53	38	21	12	7	6	xml
		31	25	18	18	12	7											bzl
		31	30	24	13	12	16	13	13	10								kts
		15	21	22	3	2												toml
dcl		13	5															dcl
proto		13	15	16	12	4	2	5	4									proto
pro		13	13	16	14	11	12	17	12	17	8	9	5					pro
		12	8	8	5	1	3	2	2	5		1	3	2				h
		12	5	1				3		2								yaml
		11	8	8	4	4	2											cc
		9	20	13	13	14	10	4	2									py
		9	7	8	2	3	4	10	9	5	9	6	2	3	1	1	2	html
		9	4	5	2	2	7	3	3	6		2	4	2				cpp
cfg		3	16	9	5	1	3	3			1	2	1	1	1			cfg
flex		2	11	4	6	2	5	8	3	5	5	5	4	1				flex
nsi		2	6	4	3	2	5	5	2	1	3	5	1					nsi
		1													4			groovy
		1																css
							3		1	1			2	1				rs
nsh			1									4	1					nsh
smali										2								smali
xsd														1		2	1	xsd
								1	1									js
			3	1	2	1	4	2	1	5	3	1	2	2				c

Visual Code Explorers

MAIN (36221)	Circles	Sunburst
TEST (2149)	Circles	Sunburst
BUILD AND DEPLOYMENT (3801)	Circles	Sunburst
GENERATED (31)	Circles	Sunburst
OTHER (3078)	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 (132)

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: graphviz | 2D graph | 2D graph (with commits) | 3D graph | 3D graph (with commits)
past 3 months: graphviz | 2D graph | 2D graph (with commits) | 3D graph | 3D graph (with commits)
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 / android
- Repository Description: Android Plugin for IntelliJ IDEA. This repository is a subset of git://git.jetbrains.org/idea/android.git cut according to GitHub file size limitations.
- 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