elastic / elasticsearch

3472	8630	7004	4978	5837	6663	6232	6333	6562	9000	8867	4901	2778	1275	1516	1665
195	295	281	281	256	326	350	317	305	298	316	319	117	54	51	7
2025	2024	2023	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010

	github actions npm gradle renovate docker
Standard analyses:
		Main Code: 1,920,392 LOC (14651 files) = JAVA (98%) + ST (<1%) + XML (<1%) + GROOVY (<1%) + YAML (<1%) + G4 (<1%) + ASCIIDOC (<1%) + TOML (<1%) + PY (<1%) + POLICY (<1%) + SQL (<1%) + C (<1%) + CPP (<1%) + CFG (<1%) + PREFS (<1%) + JS (<1%) + ASC (<1%) + H (<1%) + FTL (<1%) Secondary code: Test: 1,500,657 LOC (8546); Generated: 68,460 LOC (561); Build & Deploy: 16,900 LOC (423); Other: 171,684 LOC (1924);
		File Size: 12% long (>1000 LOC), 41% short (<= 200 LOC)
		Logical Component Decomposition: primary (15 components)
		15 years, 3 months old 87% of code older than 365 days 15% of code not updated in the past 365 days
		25% 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: 7% long (>100 LOC), 50% short (<= 10 LOC)
		Conditional Complexity: 2% complex (McCabe index > 50), 75% simple (McCabe index <= 5)
		Static Component Dependencies: primary (15 components)

	Features of interest: TODOs 1237 files

All Analysis Reports

Source Code Overview

Components

Temporal Dependencies

Duplication

File Size

File Age & Freshness

File Change Frequency

Commits

Contributors

Unit Size*

Conditional Complexity*

Features of Interest

All Metrics

Goals & Controls

Component Dependencies*

Trend

Notes & Findings

Overall Activity Per Year

Latest commit date: 2025-05-13

Reference analysis date: 2025-05-13

581

commits
(30 days)

103

contributors
(30 days)

3472	8630	7004	4978	5837	6663	6232	6333	6562	9000	8867	4901	2778	1275	1516	1665
195	295	281	281	256	326	350	317	305	298	316	319	117	54	51	7
2025	2024	2023	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010

Activity Per File Extension

commits

	2025	2024	2023	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010
	2317	6209	5688	3897	4081	4615	4486	4789	4769	7098	6478	3459	2014	1021	1339	1513	java
	1780	3542	2024	1556	782	863	607	726	753	1057	684	236	152	14	32	38	yaml
	172	1446	1271	1015	1493	1877	1690	1852	1513	1878	1629	929	238				asciidoc
	43	274	290	123	39	25	24	112	139	401	1133	527	277	235	67	119	xml
st	34	116	137		1			6			2	2					st
	43	100	40	21	11	23	18	60	23	117	6						g4
	19	99	55	93	84	126	187	354	192	408	283	4			7	32	groovy
policy	14	45	35	45	30	30	32	73	104	216	251	20					policy
	16	36	42	44	11	57											toml
	1	13															c
		12															h
		4															cpp
		3	2		1	1	2	4	12	164	177	92	10				py
cfg						1											cfg
				5	2	1				9	13						js
					6	3	16	20	20								sql
prefs					4	2	2	6	5		24	6	3				prefs
asc								3	1								asc
					2			1		10	7						ftl

contributors

	2025	2024	2023	2022	2021	2020	2019	2018	2017	2016	2015	2014	2013	2012	2011	2010
	148	220	190	170	170	187	203	160	150	127	147	127	75	44	42	6	java
	142	203	154	157	90	91	73	76	72	66	71	40	17	4	7	1	yaml
	77	174	186	181	171	229	232	238	225	226	218	229	46				asciidoc
	20	34	29	28	10	13	14	36	25	31	48	43	17	10	4	1	xml
	19	21	13	6	6	8	6	18	7	17	6						g4
st	12	21	13		1			5			2	1					st
policy	8	19	16	17	15	17	13	24	27	30	30	8					policy
	8	18	17	16	11	14	34	36	25	35	20	4			2	1	groovy
	6	16	15	12	5	10											toml
	1	7															c
		7															h
		4															cpp
		3	2		1	1	2	3	9	27	25	15	1				py
cfg						1											cfg
				3	1	1				6	3						js
					5	3	5	10	4								sql
prefs					4	2	2	5	2		12	2	1				prefs
asc								3	1								asc
					2			1		5	5						ftl

Visual Code Explorers

MAIN (14651)	Circles	Sunburst
TEST (8546)	Circles	Sunburst
BUILD AND DEPLOYMENT (423)	Circles	Sunburst
GENERATED (561)	Circles	Sunburst
OTHER (1924)	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 (15)

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: elastic / elasticsearch
- Repository Description: Free and Open Source, Distributed, RESTful Search Engine
- 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