How Lifecycle Modeling Language (LML) Supports Application Lifecycle Management (ALM)

What is Lifecycle Modeling Language (LML)?

The Lifecycle Modeling Language (LML) is a simple, extensible, open-source modeling language designed to support the systems engineering development lifecycle of complex systems. In particular, LML supports activities including requirements, architecture, design, implementation, testing, deployment, and maintenance. As part of its inspiration, LML was developed to communicate cost, schedule, performance, and design information more effectively to technical and non-technical stakeholders.

Under the surface, the basis for LML is an entity, relationship, and attribute (ERA) meta-meta model, which allows for attributes on relationships that more closely align with the English-language structure. The English-language elements involved in the model are the adverb, noun (entity), relationship (verb), and attribute (adjective) elements. To maintain versatility, LML is also translatable to other object-oriented languages, such as SysML. In these cases, the LML structure can be neatly mapped to their ontology: classes (entity), relations (relationship), and properties (attribute).

Recently, LML has been receiving new attention as a systems engineering language. One of the reasons for this is that LML is ideally suited to combat the increasing complexity of other systems engineering languages that often incorporate complicated elements and structures. Having too much complexity in systems engineering languages can hinder the process of communicating ideas, especially for non-technical stakeholders, which impacts the ability to develop complex systems efficiently.

Principal Entities and Relationships for Design LML Traceability

Keep Learning About LML:

• Extending LML to Enable Decision Patterns and Traceability
• LML Essential eBook
• Standards Available for Modeling Systems

What is Application Lifecycle Management (ALM)?

According to Microsoft, Applied Lifecycle Management (ALM) “is the lifecycle management of [software] applications, which includes governance, development, and maintenance.” ALM ensures that software applications are efficiently planned, developed, tested, deployed, and maintained throughout their lifecycle.

As software applications are considered one example of many different types of systems, the development lifecycle naturally contains a lot of broad overlap with systems engineering processes and practices. This can be seen in how ALM involves development phases:

ALM Development Phases

1. Requirements Gathering: Defining the objectives and functionality.

2. Application Development: Designing and coding the application.

3. Testing: Ensuring the application meets performance and security standards.

4. Deployment: Releasing the application into production.

5. Maintenance: Updating and refining the application over time.

How Lifecycle Modeling Language Supports Application Lifecycle Management

Thanks to the overlapping processes and practices between software development and systems engineering, LML can support and enhance the ALM development lifecycle. LML as a language offers an extensible, structured, and standardized way to model and manage development phases while maintaining clarity and consistency throughout the application lifecycle. Before understanding the benefits, we must further explore how LML works as a language.

How Lifecycle Modeling Language Works

At its core, LML relies on several classes of entities that can be interrelated with each other, enabling traceability for all engineering models and decisions.

Artifact entities capture documentation (e.g., reports, literature review, standards, regulations, etc.), which can then be connected to other entities to show how they are the source of or referenced in different phases, such as requirements analysis. 

Statements and requirements capture user needs, objectives, goals, and functional and non-functional requirements. These requirements form the basis of requirements development, which defines what the system must achieve.

Action entities capture functional activities and processes that the system must perform, including capturing the flow of data and information to enable the system’s desired capabilities.

Input and Output entities represent the data and information that must be internally and externally exchanged within actions and processes.

Asset entities capture physical elements and structures that represent the system and its parts. In particular, Asset entities can be used to draw physical architecture diagrams and models, which can help determine and represent system boundaries and guide how a system fits into the bigger picture.

Connection entities are used between Asset entities to represent the physical “pipelines” through which data and information are transferred. These can include anything from literal pipelines for transporting oil to software interfaces and protocols that process and move data in cyberspace.

Characteristic and Measure entities capture metrics that help determine how well a system achieves its intended capabilities and objectives. These metrics can be either programmatic or technical, encompassing essential values such as key performance parameters (KPPs), measures of performance (MOPs), key system attributes (KSAs), and more. Metrics must be met to determine how suitable a system is for its intended purpose, and it is crucial for gaining stakeholder buy-in to validate the final product.

Using this ontological framework, LML is commonly used to execute the systems engineering Vee model used in systems engineering projects, which helps to ensure quality and efficiency when developing complex systems.

Mapping ALM to the Systems Engineering V-Model With LML

The phases used to develop systems commonly include defining Current Operations and Maintenance, Architecture Development, Systems Design, Hardware/Software Acquisition, Integration and Test, Operational Test & Evaluation and Transition, continuing Future Operations and Maintenance, and ultimately Demolition and Disposal.

On the other hand, ALM focuses on creating software applications that are maintained until they reach their end of life. There are five stages of ALM:

• Application Requirements Gathering
• Application Development
• Application Testing
• Application Deployment
• Application Maintenance

Because these ALM phases essentially touch and overlap with many of the same activities in systems engineering, LML can support and enhance ALM activities. Visually, we can map these ALM stages to the phases of the systems engineering Vee model, highlighting where LML can be used effectively:

Read More: Optimizing Systems Engineering Through the V-Model

By using LML for ALM, organizations can leverage the power of systems engineering in the following ways:

1. Standardizing ALM Processes

LML provides a common language and framework for describing the lifecycle of applications, which can help standardize ALM processes across projects and teams. Defined processes can be referenced for teams or simulated to obtain useful system information, especially when using discrete or Monte Carlo simulators.

2. Capturing and Managing Requirements

LML allows for the capture and management of requirements, ensuring that all stakeholders clearly understand what the application being developed must achieve. Engineers can then link these requirements back to the system for traceability. In addition, these requirements can then provide context for engineering decisions made during the ALM development lifecycle.

3. Modeling Design and Architecture

LML can be used to model the design and architecture of software applications, including their components, interfaces, and interactions. Because LML is extensible, users can also create additional classes and attributes as needed to best describe their domain and industry.

4. Enhancing Development and Testing

LML can help track the progress of ALM development and testing activities, ensuring they align with the design requirements. Engineering decisions that require changes can also be recorded, providing context and accountability as the system undergoes development.

5. Supporting Deployment and Maintenance

LML can also be used to manage the deployment and maintenance of software applications, tracking changes and updates over time. Operational, maintenance, and retirement plans and processes can be captured and preserved, providing critical reference materials for teams and organizations as the system reaches end-of-life.

Explore ALM Solutions with SPEC Innovations

At SPEC Innovations, we empower engineers with the tools to build effective and scalable solutions. Our flagship tool, Innoslate, is an all-in-one, cloud-based lifecycle management solution powered by LML, trusted by academic and commercial organizations worldwide.

Ready to transform your ALM strategy with Lifecycle Modeling Language (LML)? Try Innoslate today and streamline your entire application lifecycle, from requirements to retirement.