DVERA CT verification tools

io.github.SuresoftTechnologies由 GitHub 帳號 SuresoftTechnologies 發布v0.1.4更新於 Oct 24, 2026

DVERA drives CT verification of mission-critical C/C++: setup, analysis, tests, coverage.

已驗證STDIO僅桌面開發者工具安全與監控

概覽

AI 產生的概覽

讓編碼助理驅動 C/C++ 專案的 CT 驗證:專案建置、分析、測試產生與執行、覆蓋率與報告。

可以做什麼
DVERA 會把工具呼叫轉送到本機安裝的 CT(Controller Tester),讓助理可以建立 CT 驗證專案、擷取編譯器巨集與建置設定、執行分析、產生並執行單元或整合測試、重跑回歸測試與 GoogleTest 資產,並讀回覆蓋率與報告。它也提供 dvera_check_environment 工具,在找不到 CT 時說明缺少什麼。此伺服器在呼叫之間不保留自己的行程,也不取代 CT 的驗證結果。
適用情境
當你使用已部署的 CT 環境驗證關鍵任務 C/C++ 軟體,並希望助理在對話中準備與協調這些工作時適用。未安裝 CT 時沒有用處,也不能當作 CT 安裝的獨立替代品。
執行需求
由 MCP 用戶端啟動的本機行程;README 建議把用戶端指向 CT 內附的 Python 解譯器(Python 3.8 或更新版本也可),並從要驗證的專案目錄執行用戶端。需要 CT 2026.06 或更新版本、有效的 CT 授權、受支援的 C/C++ 建置與目標環境,以及已部署 CT 環境中的 DVERA 整合。若 CT 安裝在預設位置之外,請設定 CT_HOME。未宣告任何憑證。
安裝前請注意
產品相關操作需要已部署且已授權的 CT 環境;沒有該環境時,技能會停在安裝檢查處,且不得聲稱已進行分析、執行、覆蓋率量測或報告。產生的測試應先審查其測試意圖、資料與預期結果再採信。此伺服器在本機執行,依 README 不向第三方傳送任何內容,但 CT 本身記錄的工作區、分析輸出與報告受 CT 的資料處理方式約束。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 DVERA CT verification tools,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

README

DVERA — CT Verification Skills for C/C++ Coding Agents

한국어: README.ko.md

DVERA (Dynamic Verification Agent) brings CT C/C++ verification work into coding agents such as Claude Code, Codex CLI, Cursor, and GitHub Copilot. It uses the working context of source code, requirements, build information, source changes, and existing test assets to prepare and request CT verification work.

CT (Controller Tester) is a test automation solution for unit, integration, and code-based testing of mission-critical C/C++ software. It brings together test-environment setup, test design and generation, execution, code-coverage analysis, reporting, and traceability management.

DVERA does not replace CT's verification results. The coding agent helps prepare and coordinate verification work; CT performs the analysis, build, test execution, and result aggregation. Generated tests must be reviewed for test intent, data, and expected results, then confirmed with actual execution results and measured coverage.

What the CT and DVERA workflow adds

Verification needCT and DVERA workflow
Complex C/C++ environmentsCapture compiler, macro, include-path, toolchain, build, and target conditions before analysis.
Unit and integration verificationDesign and execute tests at function, module, and interface levels, including existing GoogleTest assets where applicable.
Reviewable evidenceConnect test intent, execution results, statement/branch/MC/DC coverage, reports, and requirement links for review.
Repeated change verificationRe-run affected tests after code changes and review new failures and coverage deltas for regression follow-up.
AI-assisted test workUse code, requirements, and change context to prepare test work, then improve it with CT analysis and measured results.

Workflow at a glance

  1. Prepare the compiler, macro, include-path, toolchain, and target context for a CT project.
  2. Analyze the project and resolve environment or configuration issues through a controlled feedback loop.
  3. Generate, execute, and improve unit or integration tests using build, execution, and coverage feedback.
  4. Review coverage and results, produce reports, and re-run affected verification after source changes.

The Skills in this repository document that product-connected workflow. They are not standalone replacements for a CT installation.

Install

In Claude Code:

text
/plugin marketplace add SuresoftTechnologies/dvera-plugin/plugin install dvera@suresofttech

Or from a terminal:

text
claude plugin marketplace add SuresoftTechnologies/dvera-pluginclaude plugin install dvera@suresofttech

Skills then load as /dvera:ct-init-project, /dvera:ct-test-loop, and so on. The plugin adds about 620 tokens to every session; each Skill body is read only when that Skill runs.

Product-backed actions need a deployed CT environment. Without one, a Skill stops at its installation check and shows how to reach product support.

Example requests

Trigger examples from the CT user guide. Responses can vary with the AI model and conversation context; if the result differs from what you expect, rephrase the request with more detail and retry.

RequestSkill
Create a CT project and start verification.ct-init-project
Run tests in CT.ct-init-project
Generate tests for the calculate_checksum function.ct-test-loop
Find functions without tests and generate tests for them.ct-test-loop
Run regression tests.ct-regression
Open CT.ct-open

Skills

All Skills require a deployed CT environment for their product-backed actions and stop with an installation notice when none is found.

SkillCT workflow stage
ct-init-projectStart or prepare a CT verification project.
ct-extract-macroCapture target compiler macros and build-environment facts.
ct-make-confPrepare the analysis configuration for the selected toolchain.
ct-setup-projectCreate the CT project and apply build inputs.
ct-analysis-loopAnalyze the project and resolve configuration or toolchain issues.
ct-test-loopGenerate, run, and improve tests.
ct-kb-updateRecord verified workflow observations after a completed CT run.
ct-regressionRe-run existing tests after a code change and review deltas.
ct-self-healingRun regression evidence collection and identify CT Self-Healing review candidates.
ct-run-gtestRe-run GoogleTest assets registered in CT and review results and coverage.
ct-req-to-testGenerate and execute a CT AI test from approved requirements.
ct-reportExport execution and coverage evidence.
ct-openOpen the CT project for visual inspection.
ct-orchestratorResume the appropriate stage of an in-progress verification workflow.

Product-backed workflow

DVERA works with a deployed CT and DVERA environment. This repository documents the verification workflow and ships an MCP server that forwards tool calls to a local CT installation, but does not include the CT runtime or product installation.

Without the deployed environment, users can inspect this repository's documented workflow, but a Skill that needs CT actions stops at its installation check. It must not claim that CT analysis, execution, coverage measurement, or reporting has occurred.

MCP tools

Give the agent CT's verification tools directly. With the MCP server (scripts/dvera-mcp.py) connected, it can create the project, run analysis, generate and execute tests, and read coverage back without leaving the conversation - the same tools CT exposes to its own agent. Calls go to CT's ct_tool.py entry point, and the server keeps no process of its own between them.

Connect it in one of two ways.

Point an MCP client at the interpreter CT already ships - no extra install:

json
{  "mcpServers": {    "dvera": {      "command": "C:/Program Files/Suresoft/CT 2026/python/python.exe",      "args": ["/path/to/dvera-plugin/scripts/dvera-mcp.py"]    }  }}

On Linux the interpreter is at <CT install>/python/python3. Any Python 3.8 or later works if you would rather use your own. Replace the script path with wherever this repository sits: clone it, or use the copy the plugin manager installed (claude plugin list shows where plugins live). The server takes the source directory from the client's working directory, so run the client from the project you want to verify.

Or install the bundle from this repository's releases: download dvera-mcp.mcpb and open it with a client that installs MCP bundles. It resolves its own Python, so nothing has to be installed first.

Set CT_HOME if CT is installed outside the default location. The server is safe to leave configured on any machine: it starts either way, and without CT it offers a single tool, dvera_check_environment, which reports what is missing and what to do about it. That tool is also there when CT is - run it first whenever the verification tools do not appear.

Requirements for product-backed verification

  • CT 2026.06 or later
  • A valid CT license
  • A supported C/C++ build and target environment
  • DVERA integration supplied as part of the deployed CT environment

For a product demo, purchase, or deployment consultation, contact [email protected].

Privacy Policy

The MCP server in this repository runs entirely on your machine.

  • It sends nothing to Suresoft Technologies or to any third party. There is no telemetry, no analytics, and no network call of its own.
  • Tool arguments are passed to the CT installation on the same machine, and CT's response is returned to your MCP client. Nothing is written outside CT's own workspace.
  • It stores no credentials and reads no files beyond the CT installation directory and the paths a tool call names.
  • Anything CT itself records - workspaces, analysis output, reports - is governed by CT's own handling of that data, not by this repository.

The Skills are documentation: they carry no code that runs on your machine.

The full policy is in PRIVACY.md. Questions about data handling in the CT product itself go to [email protected].

License and trademarks

This repository is licensed under the MIT License. The license covers everything in this repository - the documentation, the Skill files, and the MCP server source. It does not cover CT itself: CT and DVERA are Suresoft Technologies products, and no product functionality or product licence is granted by this repository.

GoogleTest is a trademark of Google LLC. This repository is not affiliated with, sponsored by, or endorsed by Google. Other product names may be trademarks of their respective owners.

來源:README.md,提交 92e1256

工具

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SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

4
  1. v0.1.4最新Sep 22, 2026
  2. v0.1.2Sep 21, 2026
  3. v0.1.1Sep 18, 2026
  4. v0.1.0Sep 16, 2026

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