In-Depth

Borland Ships Gauntlet Automatic Test Tool

Borland Software adds another piece to its life-cycle quality management tool offering with its shipment of Gauntlet automated build and test software.

Borland Software has announced shipment of Gauntlet automated build and test software, adding another piece to its life-cycle quality management (LQM) tools offering.

Gauntlet continuously tests code as developers check it in. It's designed to detect potential problems early by automatically pre-screening all new code against a set of quality guidelines before it enters the build process, according to Borland statements.

The package institutes quality controls within existing version control processes. These controls, called "gauntlets," enable development teams to identify and isolate problems earlier in the application life cycle—when their impact can be minimized—by automatically inspecting development "artifacts" every time a change is made or at desired intervals.

Gauntlet's "dashboards" include realtime snapshots and time series analysis of metrics, such as build performance, unit or functional test results, code coverage, and project activity.

By making it possible for you to view and measure application health earlier in the life cycle, Gauntlet aims to help development teams gain greater confidence and accountability in their estimates, technical predictions, and risk assessments, while also enabling management to identify at-risk projects early enough in the life cycle to institute changes in scope or resources.

Gauntlet is a component of Borland's LQM solution. The LQM solution combines versions of the Silk application life-cycle management products, which Borland acquired from Segue Software in April, with the Gauntlet continuous build and test product, which it acquired in March with the acquisition of Gauntlet Systems, and its Caliber requirements management tools (see Resources). Not so much a bundle as an ala carte menu of integrated products as well as services and consulting, the idea behind Borland's LQM solution, and Gauntlet, is to let development teams more closely track user requirements through the entire process including QA.

In addition, Gauntlet integrates with leading configuration management products—including Borland StarTeam, CVS, and Subversion.

It supports also a growing number of third-party and open source integrations that enable customers to test for a broad range of potential defects—from code complexity and readability to security vulnerabilities or license compliance, Borland said. Gauntlet also lets you add or create your own custom gauntlets, all of which feed metrics into centralized Gauntlet dashboards.

Among the open source integrations for Gauntlet that are currently available or under development, are Ant, CheckStyle, Emma, Findbugs, JUnit, NUnit, and PMD. Commercial tools integrations include Cenzic Hailstorm for Web application vulnerability assessment, Fortify SCA for source code security analysis, Klocwork K7 for automated software detection and prevention, Lint4J for static Java source code analysis, and Palamida IP Amplifier for software intellectual property compliance scanning and auditing.

About the Author

Stuart J. Johnston has covered technology, especially Microsoft, since February 1988 for InfoWorld, Computerworld, Information Week, and PC World, as well as for Enterprise Developer, XML & Web Services, and .NET magazines.

comments powered by Disqus

Featured

  • Hands On with New GitHub Copilot App Technical Preview: Turning a Blazor Issue into a Pull Request

    GitHub's brand-new Copilot desktop app, in technical preview, handled a small Blazor issue from planning through pull request creation, but the hands-on test also showed why developers still need to verify agent work in the running app before merging.

  • At Build 2026, Microsoft Sets Up Windows as an OS for AI Agents

    Microsoft's Build 2026 Windows developer announcements point to a broader platform strategy for agentic AI, spanning terminal workflows, local models, app-building skills, Cloud PCs and operating system-level containment.

  • Slammed by Copilot Usage-Based Billing on Day 1, Facing $180 Bill for June

    A journalist using GitHub Copilot Pro details how a broken editorial workflow on day one of usage-based billing led to runaway token consumption, a projected $180 monthly bill, and practical tactics for cutting AI credit burn.

  • AdaBoost.R2 Regression Using C#

    AdaBoost.R2 regression works by building an ensemble of decision trees, training them on reweighted data, and combining their predictions with a weighted median, while also showing how parameter choices affect accuracy and overfitting.

Subscribe on YouTube