Conventional Software Management

Conventional Software Management

Project Management - 1

Project

A project is a series of tasks that must be carried out in order to reach a desired outcome. It involves non-routine tasks and requires planning. Specific objectives are to be met or a specific product is to be created. The project has a predetermined time span. Work is carried out for someone other than yourself. People are formed into a temporary work group to carry out the task. Work is carried out in several phases. The project is large or complex.

Software Project Management

Software project management involves the complete procedure of software development from requirement gathering to testing and maintenance, carried out according to the execution methodologies, in a specified period of time to achieve the desired software product.

Management

Management involves planning, organizing, staffing, directing, monitoring, controlling, innovating, and representing. It is important because money is at risk and projects are not always successful. Projects are late and exceed the budget.

Approaches

There are two approaches to software management: the Old Way (Conventional Software Management) and the New Way (Evolution of Software Economics).

Old Way is good in theory but does not sound practical. Examples are the waterfall model etc. Software development is highly unpredictable. Management discipline is more of a discriminator in success or failure than our technology advances. The level of software scrap and rework is indicative of an immature process.

Waterfall Model

The Waterfall Model is a traditional, linear approach to the software development process. It involves breaking down the development process into distinct stages, with each stage having defined objectives, inputs, and outputs. The key feature of the waterfall model is that each stage must be completed before the next phase can begin.

The Waterfall model is the earliest SDLC approach that was used for software development. The waterfall Model illustrates the software development process in a linear sequential flow. This means that any phase in the development process begins only if the previous phase is complete. In this waterfall model, the phases do not overlap.

There are two essential steps common to the development of computer programs: analysis and coding. In order to manage and control all of the intellectual freedom associated with software development, one must introduce several other “overhead” steps, including system requirements definition, software requirements definition, program design, and testing. These steps supplement the analysis and coding steps.

The development process follows a sequence of stages: requirements gathering and analysis; system design; implementation; testing; operation/deployment; and maintenance.

Waterfall Model | Different Phases With Advantages & Disadvantages (2022)

Drawbacks of the Waterfall Model

  • Protracted integration and late design breakage.

  • Late risk resolution.

  • Requirements-driven functional decomposition.

  • Adversarial (conflict or opposition) stakeholder relationships.

  • Focus on documents and review meetings.

Improvements to the Waterfall Model

However, five necessary improvements can be made to the Waterfall Model to make it more effective:

  1. Complete program design before analysis and coding begins.

  2. Maintain current and complete documentation.

  3. Do the job twice if possible.

  4. Plan, control, and monitor testing.

  5. Involve the customer.

Barry Boehm’s "Industrial Software Metrics Top 10 List"

Barry Boehm’s "Industrial Software Metrics Top 10 List” is a good, objective characterization of the state of software development. It provides insight into the challenges and opportunities that software developers face in today’s fast-paced environment.

The Top 10 List

  1. Finding and fixing a software problem after delivery costs 100 times more than finding and fixing the problem in the early design phases.

  2. You can compress software development schedules to 25% of nominal, but no more.

  3. For every $1 you spend on development, you will spend $2 on maintenance.

  4. Software development and maintenance costs are primarily a function of the number of source lines of code.

  5. Variations among people account for the biggest differences in software productivity.

  6. The overall ratio of software to hardware costs is still growing. (In 1955 it was 15:85; in 1985, 85:15)

  7. Only about 15% of software development effort is devoted to programming.

  8. Software systems and products typically cost 3 times as much per SLOC as individual software programs. Software-system products (i.e., systems of systems) cost 9 times as much.

  9. Walkthroughs catch 60% of the errors.

  10. 80% of the contribution comes from 20% of the contributors.

Software Economics

Software Economics is a mature research area in software engineering that deals with the most difficult and challenging problems and issues of valuing software and determining or estimating costs usually involved in its production. In this article, we will discuss the evolution of software economics and how it can be applied to improve software design, development, and evolution.

Evolution of Software Economics

Most software cost models can be abstracted into a function of five basic parameters: size, process, personnel, environment, and required quality.

  1. Size: The size of the end product (in human-generated components), which is typically quantified in terms of the number of source instructions or the number of function points required to develop the required functionality.

  2. Process: The process used to produce the end product, in particular the ability of the process to avoid non-value-adding activities (rework, bureaucratic delays, communications overhead).

  3. Personnel: The capabilities of software engineering personnel, and particularly their experience with the computer science issues and the applications domain issues of the project.

  4. Environment: The environment, which is made up of the tools and techniques available to support efficient software development and to automate the process.

  5. Required Quality: The required quality of the product, including its features, performance, reliability, and adaptability.

Relationship Between Parameters

Effort = (Personnel) (Environment) (Quality) (Size ^ process)

Generations of Software Development

  1. Conventional: This generation of software development occurred in the 1960s and 1970s and was characterized by craftsmanship. Organizations used custom tools, custom processes, and virtually all custom components built in primitive languages. Project performance was highly predictable in that cost, schedule, and quality objectives were almost always underachieved.

  2. Transition: This generation of software development occurred in the 1980s and 1990s and was characterized by software engineering. Organizations used more-repeatable processes and off-the-shelf tools, and mostly (>70%) custom components built in higher-level languages. Some of the components (<30%) were available as commercial products, including the operating system, database management system, networking, and graphical user interface.

  3. Modern Practices: This generation of software development occurred in 2000 and later and was characterized by software production. This philosophy is rooted in the use of managed and measured processes, integrated automation environments, and mostly (70%) off-the-shelf components. Perhaps as few as 30% of the components need to be custom-built.

Cost estimation

Cost estimation is an important process in project management that involves forecasting the cost and other resources needed to complete a project within a defined scope. In this article, we will discuss the important points of cost estimation, cost estimation models, attributes of good cost estimation, and the need for good cost estimation.

Important Points of Cost Estimation

Three important topics are here:

  1. Which cost estimation model to use?

  2. Whether to measure software size in source lines of code or function points.

  3. What constitutes a good estimate?

Cost Estimation Models

There are several cost estimation models available for software development projects. Some of the most popular models include COCOMO, CHECKPOINT, ESTIMACS, KnowledgePlan, Price-S, ProQMS, SEER, SLIM, SOFTCOST, SPQR/20 etc.

Predominant Cost Estimation Process

Attributes Of Good Cost Estimation

  1. It is conceived and supported by the project manager, architecture team, development team, and test team accountable for performing the work.

  2. It is accepted by all stakeholders as ambitious but realizable.

  3. It is based on a well-defined software cost model with a credible basis.

  4. It is based on a database of relevant project experience that includes similar processes, similar technologies, similar environments, similar quality requirements, and similar people.

  5. It is defined in enough detail so that its key risk areas are understood and the probability of success is objectively assessed.

Need For Good Cost Estimation

  1. Enable you to weigh benefits against the cost to see whether the project makes sense.

  2. Allow you to see whether the necessary funds are available to support the project.

  3. Serves as guidelines to help ensure that you have sufficient funds to complete the project.

Benefits Of Good Cost Estimation

  1. A valuable tool for decision-making.

  2. Provides a starting point from which to begin evaluation of a project.

  3. Allows comparison between investments required for the project.

  4. Becomes easy to exclude bad projects from consideration.

Estimation Techniques

  1. Algorithmic or Parametric Models: This technique involves using mathematical algorithms to estimate the cost and other resources needed for a project. These models are based on historical data and can be used to estimate the cost of similar projects.

  2. Expert Judgment: This technique involves using the knowledge and experience of experts to estimate the cost and other resources needed for a project. Experts can provide valuable insights into the project’s requirements and can help identify potential risks.

  3. Top-Down Approach: This technique involves estimating the cost and other resources needed for a project at a high level and then breaking it down into smaller components. This approach is useful when there is limited information available about the project.

  4. Bottom-Up Approach: This technique involves estimating the cost and other resources needed for each component of a project and then aggregating them to determine the total cost. This approach is useful when there is detailed information available about the project.

  5. Estimation By Analog: This technique involves using historical data from similar projects to estimate the cost and other resources needed for a new project.

  6. Pricing to Win Estimation: This technique involves estimating the cost and other resources needed for a project based on what it would take to win the contract.

Improving software economics

Improving software economics is an important part of software development that involves reducing the cost and other resources needed to complete a project within a defined scope. In this article, we will discuss the five basic parameters of the software cost model that can help improve software economics.

Five Basic Parameters of the Software Cost Model

  1. Reducing the size or complexity of what needs to be developed: This parameter involves simplifying the project’s requirements and reducing its complexity. By doing so, developers can reduce the amount of time and resources needed to complete the project.

  2. Improving the development process: This parameter involves improving the development process by using best practices, such as agile development, continuous integration, and automated testing. By doing so, developers can reduce the amount of time and resources needed to complete the project.

  3. Using more-skilled personnel and better teams: This parameter involves using more-skilled personnel and better teams to complete the project. By doing so, developers can reduce the amount of time and resources needed to complete the project.

  4. Using better environments (tools to automate the process): This parameter involves using better environments and tools to automate the development process. By doing so, developers can reduce the amount of time and resources needed to complete the project.

  5. Trading off or backing off on quality thresholds: This parameter involves trading off or backing off on quality thresholds to reduce the amount of time and resources needed to complete the project.

  • Size

  • Abstraction and component-based development technologies

COST MODEL PARAMETERSTRENDS
Size: Abstraction and component-based development technologiesHigher-order languages (C++, Ada 95, Java, Visual Basic, etc.)
Object-oriented (analysis, design, programming)
Reuse
Commercial components
Process: Method and techniquesIterative development
Process maturity models
Architecture-first development
Acquisition reform
Personnel: People factorsTraining and personnel skill development
Teamwork
Win-win cultures
Environment: Automation technologies and toolsIntegrated tools (visual modelling, compiler, editor, debugger, change management etc.)
Open systems
Hardware platform performance
Automation of coding, documents, testing, analyses
Quality: Performance, reliability, accuracyHardware platform performance
Demonstration-based assessment
Statistical quality control

Reducing software product size

Reducing software product size is an important part of software development that involves producing a product that achieves the design goals with the minimum amount of human-generated source material. In this article, we will discuss two methods for reducing software product size: language and object-oriented methods.

Reducing Software Product Size: Language

Universal function points (UFPs) are useful estimators for language-independent, early life-cycle estimates. SLOC metrics are useful estimators for software after a candidate solution is formulated and an implementation language is known. The table below shows the SLOC per UFP for some of today’s popular languages:

LanguageSLOC per UFP
Assembly320
C128
FORTRAN77105
COBOL8591
Ada8371
C++56
Ada9555
Java55
Visual Basic35

Reducing Software Product Size: Object-Oriented Method

An object-oriented model of the problem and its solution encourages a common vocabulary between the end-users of a system and its developers, thus creating a shared understanding of the problem being solved. The use of continuous integration creates opportunities to recognize risk early and make incremental corrections without destabilizing the entire development effort. An object-oriented architecture provides a clear separation of concerns among disparate elements of a system, creating firewalls that prevent a change in one part of the system from rending the fabric of the entire architecture.

Booch also summarized five characteristics of a successful object-oriented project:

  1. A ruthless focus on the development of a system that provides a well-understood collection of essential minimal characteristics.

  2. The existence of a culture that is centered on results, encourages communication, and yet is not afraid to fail.

  3. The effective use of object-oriented modelling.

  4. The existence of a strong architectural vision.

  5. The application of a well-managed iterative and incremental development life cycle.

Reducing Software Product Size: Reuse

Reuse is another method for reducing software product size. Common architecture, development environment, operating system, DBMS, networking products, and office applications are some examples of reusable components.

Reducing Software Product Size: Commercial Components

A common approach being pursued today in many domains is to maximize the integration of commercial components and off-the-shelf products. The use of commercial components is certainly desirable as a means of reducing custom development. However, there are advantages and disadvantages to using commercial components.

ApproachAdvantagesDisadvantages
Commercial ComponentsPredictable license costsFrequent upgrades
Broadly used, mature technologyUp-front licence fees
Available nowRecurring maintenance fees
Dedicated support organizationDependency on vendor
Hardware/software independenceRun-time efficiency sacrifices
Rich in functionalityFunctionality constraints
Integration not always trivial
No control over upgrades and maintenance
Unnecessary features that consume extra resources
Often inadequate reliability and stability
Multiple-vendor incompatibilities
Custom developmentComplete change freedomExpensive, unpredictable development
Smaller, often simpler implementationsUnpredictable availability date
Often better performanceUndefined maintenance model
Control of development and enhancementOften immature and fragile
Single-platform dependency
Drain on expert resources

Improving software economics

Improving software economics is an important part of software development that involves reducing the cost and other resources needed to complete a project within a defined scope. In this article, we will discuss two methods for improving software economics: improving software processes and improving team effectiveness.

Improving Software Process

There are three distinct process perspectives:

  1. Metaprocess: an organization’s policies, procedures, and practices for pursuing a software-intensive line of business. The focus of this process is on organizational economics, long-term strategies, and software ROI.

  2. Macroprocess: a project’s policies, procedures, and practices for producing a complete software product within certain cost, schedule, and quality constraints. The focus of the macro process is on creating an adequate instance of the Meta process for a specific set of constraints.

  3. Microprocess: a project team’s policies, procedures, and practices for achieving an artefact of the software process. The focus of the micro process is on achieving an intermediate product baseline with adequate quality and adequate functionality as economically and rapidly as practical.

Although these three levels of process overlap somewhat, they have different objectives, audiences, metrics, concerns, and time scales.

Improving Team Effectiveness

Teamwork is much more important than the sum of the individuals. Some maxims of team management include the following:

  1. A well-managed project can succeed with a nominal engineering team.

  2. A mismanaged project will rarely succeed, even with an expert team of engineers.

  3. A well-architected system can be built by a nominal team of software builders.

  4. A poorly architected system will flounder even with an expert team of builders.

Boehm Five Staffing Principles

Boehm's five staffing principles are:

  1. The principle of top talent: Use better and fewer people.

  2. The principle of job matching: Fit the tasks to the skills and motivation of the people available.

  3. The principle of career progression: An organization does best in the long run by helping its people to self-actualize.

  4. The principle of team balance: Select people who will complement and harmonize with one another.

  5. The principle of phase-out: Keeping a misfit on the team doesn’t benefit anyone.

Leadership Qualities

Software project managers need many leadership qualities in order to enhance team effectiveness. The following are some crucial attributes of successful software project managers that deserve much more attention:

  1. Hiring skills: Placing the right person in the right job seems obvious but is surprisingly hard to achieve.

  2. Customer-interface skill: Avoiding adversarial relationships among stakeholders is a prerequisite for success.

  3. Decision-making skill: The jillion books written about management have failed to provide a clear definition of this attribute. We all know a good leader when we run into one, and decision-making skill seems obvious despite its intangible definition.

  4. Team-building skill: Teamwork requires that a manager establish trust, motivate progress, exploit eccentric prima donnas, transition average people into top performers, eliminate misfits, and consolidate diverse opinions into a team direction.

  5. Selling skill: Successful project managers must sell all stakeholders (including themselves) on decisions and priorities, sell candidates on job positions, sell changes to the status quo in the face of resistance, and sell achievements against objectives. In practice, selling requires continuous negotiation, compromise, and empathy.

Improving automation through Software Environment

Improving automation through Software Environment is an important part of software development that involves creating an environment that can automate the design process and provide payback in quality, the ability to estimate costs and schedules, and overall productivity using a smaller team. In this article, we will discuss forward engineering, reverse engineering, requirements analysis and evolution activities, software design activities, coding and unit testing activities, test activities, configuration control and change management activities, documentation activities, project management, business administration, and progress assessment.

Forward Engineering

Forward engineering is the automation of one engineering artefact from another, more abstract representation. For example, compilers and linkers have provided automated transition of source code into executable code.

Reverse Engineering

Reverse engineering is the generation or modification of a more abstract representation of an existing artefact. For example, creating a visual design model from a source code representation.

Requirements analysis and evolution activities consume 40% of life-cycle costs.

Software design activities have an impact on more than 50% of the resources.

Coding and unit testing activities consume about 50% of software development effort and schedule.

Test activities can consume as much as 50% of a project’s resources.

Configuration control and change management are critical activities that can consume as much as 25% of resources on a large-scale project.

Documentation activities can consume more than 30% of project engineering resources.

Project management, business administration, and progress assessment can consume as much as 30% of project budgets.

Achieving required quality

Achieving required quality is an important part of software development that involves creating an environment that can support early and continuous configuration control, change management, rigorous design methods, document automation, and regression test automation. In this article, we will discuss key practices that improve overall software quality, using metrics and indicators to measure the progress and quality of architecture as it evolves from a high-level prototype into a fully compliant product, visual modelling and higher-level languages that support architectural control, abstraction, reliable programming, reuse, and self-documentation, and early and continuous insight into performance issues through demonstration-based evaluations.

Key Practices

Key practices that improve overall software quality include the following:

  • Focusing on driving requirements and critical use cases early in the life cycle

  • Focusing on requirements completeness and traceability late in the life cycle

  • Focusing throughout the life cycle on a balance between requirements evolution, design evolution, and plan evolution

Metrics and Indicators

Using metrics and indicators to measure the progress and quality of an architecture as it evolves from a high-level prototype into a fully compliant product is an important part of achieving the required quality. This can help developers better understand how their architecture is evolving over time and identify areas where improvements can be made.

Visual Modeling and Higher-Level Languages

Using visual modelling and higher-level languages that support architectural control, abstraction, reliable programming, reuse, and self-documentation is another important part of achieving the required quality. This can help developers better understand their architecture and identify areas where improvements can be made.

Early and Continuous Insight into Performance Issues

Early and continuous insight into performance issues through demonstration-based evaluations is also important for achieving the required quality. This can help developers identify performance issues early on in the development process and make changes before they become more difficult to address.

The Typical Chronology of Events in Performance Assessment

The typical chronology of events in performance assessment was as follows:

  • Project inception: The proposed design was asserted to be low risk with adequate performance margin.

  • Initial design review: Optimistic assessments of adequate design margin were based mostly on paper analysis or rough simulation of the critical threads. In most cases, the actual application algorithms and database sizes were fairly well understood.

  • Mid-life-cycle design review: The assessments started whittling away at the margin, as early benchmarks and initial tests began exposing the optimism inherent in earlier estimates.

  • Integration and test: Serious performance problems were uncovered, necessitating fundamental changes in the architecture. The underlying infrastructure was usually the scapegoat, but the real culprit was the immature use of the infrastructure, immature architectural solutions, or poorly understood early design trade-offs.

General quality improvements with a modern process

QUALITY DRIVERCONVENTIONAL PROCESSMODERN ITERATIVE PROCESS
Requirements misunderstandingDiscovered lateResolved early
Development riskUnknown until lateUnderstood and Resolved early
Commercial componentsMostly unavailableStill a quality driver, but trade-offs must be resolved early in the life cycle
Change managementLate in the life cycle, chaotic and malignantEarly in the life cycle, straightforward and benign
Design errorsDiscovered LateResolved Early
AutomationMostly error-prone manual proceduresMostly automated, error-free evolution of artifacts
Resource adequacyUnpredictablePredictable
SchedulesOverconstrainedTunable to quality, performance, and technology
Target PerformancePaper-based analysis or separate simulationExecuting prototypes, early performance feedback, quantitative understanding
Software Process rigorDocument-basedManaged, measured, and tool-supported

Principles of Conventional Software Management

As technology continues to evolve, the importance of software management in creating high-quality software has become increasingly apparent. Conventional software management provides a set of principles to guide the development process and ensure that the final product meets customer needs.

  1. Make quality a priority and establish mechanisms to ensure it is achieved.

  2. Prove that high-quality software is achievable by using techniques such as involving customers, prototyping, simplifying design, conducting inspections, and hiring skilled professionals.

  3. Give products to customers early to obtain real feedback on their needs.

  4. Explore alternatives and determine the problem before writing requirements.

  5. Evaluate design alternatives after the requirements have been agreed upon.

  6. Use an appropriate process model that makes the most sense for the project.

  7. Use different languages for different phases of the project.

  8. Minimize intellectual distance by aligning software structure with the real-world structure.

  9. Prioritize techniques over tools to ensure disciplined engineering practices.

  10. Get it right before making it faster, don't optimize prematurely.

  11. Inspect code to find errors more effectively than testing alone.

  12. Good management is essential to motivate people to do their best.

  13. People are the key to success, hire skilled professionals with appropriate experience and training.

  14. Follow with care, don't adopt something just because others are doing it.

  15. Take responsibility for the quality of the software being developed.

  16. Understand the customer's priorities to meet their needs effectively.

  17. The more they see, the more they need, therefore, to balance functionality and performance with customer expectations.

  18. Plan to throw one away for entirely new applications, architectures, interfaces, or algorithms.

  19. Design for change by using architectures, components, and specifications that accommodate change.

  20. Design without documentation is not design, ensure proper documentation is created.

  21. Use software tools to increase efficiency, but be realistic about their capabilities.

  22. Avoid tricky code that can cause issues later on.

  23. Encapsulate information for easier testing and maintenance.

  24. Use coupling and cohesion to measure software maintainability and adaptability.

  25. Use the McCabe complexity measure to report software complexity.

  26. Developers should not be the primary testers of their own software.

  27. Analyze the causes of errors to prevent them in the future.

  28. Realize that software entropy increases over time, and continuous change will lead to complexity.

  29. People and time are not interchangeable, measure projects by their outcomes, not solely by person-months.

  30. Expect excellence, and employees will perform better when expectations are high.

Principle Of Modern Software Management

Here are the top 10 principles of modern software management:

  1. Base the process on an architecture-first approach: This means achieving a balance among driving requirements, architecturally significant design decisions, and lifecycle plans before committing resources for full-scale development.

  2. Establish an iterative life-cycle process that confronts risk early: With sophisticated software systems, it's not possible to define the entire problem, design the entire solution, build the software, then test the end product in sequence. An iterative process that refines the problem understanding, an effective solution, and an effective plan over several iterations encourages a balanced treatment of all stakeholder objectives. Major risks must be addressed early to increase predictability and avoid expensive downstream scrap and rework.

  3. Transition design methods to emphasize component-based development: Moving from a line-of-code mentality to a component-based mentality is necessary to reduce the amount of human-generated source code and custom development.

  4. Establish a change management environment: The dynamics of iterative development necessitates objectively controlled baselines.

  5. Enhance change freedom through tools that support round-trip engineering: Round-trip engineering is the environment support necessary to automate and synchronize engineering information in different formats (such as requirements specifications, design models, source code, executable code, test cases cycle).

  6. Capture design artifacts in rigorous, model-based notation: A model-based approach (such as UML) supports the evolution of semantically rich graphical and textual design notations.

  7. Instrument the process for objective quality control and progress assessment: Life-cycle assessment of the progress and the quality of all intermediate products must be integrated into the process.

  8. Use a demonstration-based approach to assess intermediate artifacts: It's essential that the software management process drive toward early and continuous demonstrations within the operational context of the system, namely its use cases.

  9. Plan intermediate releases in groups of usage scenarios with evolving levels of detail: Intermediate releases should be planned in groups of usage scenarios with evolving levels of detail. This ensures that the software management process is geared towards early and continuous demonstrations.

  10. Establish a configurable process that is economically scalable: No single process is suitable for all software developments. Therefore, it's important to establish a configurable process that is economically scalable and can be adapted to meet the needs of different projects.

Modern Process Approach Solving Conventional Problems

Conventional Process: Top 10 RisksImpactModern Process: Inherent Risk Resolution Features
Late breakage and excessive scrap/reworkQuality, cost, scheduleArchitecture-first approach
Iterative development
Automated change management
Risk-confronting process
Attrition of key personnelQuality, cost, scheduleSuccessful, early iterations
Trustworthy management and planning
Inadequate development resourcesCost, scheduleEnvironments as first-class artifacts of the process
Industrial-strength, integrated environments
Model-based engineering artifacts
Round-trip engineering
Adversarial stakeholdersCost, scheduleDemonstration-based review
Use-case-oriented requirements/testing
Necessary technology insertionCost, scheduleArchitecture-first approach
Component-based development
Requirements creepCost, scheduleIterative development
Use case modelling
Demonstration-based review
Analysis paralysisScheduleDemonstration-based review
Use-case-oriented requirements/testing
Inadequate performanceQualityDemonstration-based performance assessment
Early architecture performance feedback
Overemphasis on artifactsScheduleDemonstration-based assessment
Objective quality control
Inadequate functionQualityIterative development
Early prototypes, incremental releases

Transition to an Iterative Process

Modern software development processes have moved away from the conventional waterfall model towards iterative processes.

  1. Application Precedentedness: Domain experience is crucial in understanding how to plan and execute a software development project. In unprecedented systems, one of the key goals is to confront risks and establish early precedents, even if they are incomplete or experimental. This is one of the primary reasons why the software industry has moved to an iterative life-cycle process. Early iterations establish precedents from which the product, the process, and the plans can be elaborated in evolving levels of detail.

  2. Process Flexibility: Modern software development is characterized by a broad solution space and numerous interrelated concerns, necessitating continuous incorporation of changes. Project artifacts must be supported by efficient change management commensurate with project needs. A configurable process that allows a common framework to be adapted across a range of projects is necessary to achieve a software return on investment.

  3. Architecture Risk Resolution: Architecture-first development is a crucial theme underlying a successful iterative development process. A project team develops and stabilizes architecture before developing all the components that make up the entire suite of application components. An architecture-first and component-based development approach forces the infrastructure, common mechanisms, and control mechanisms to be elaborated early in the life cycle and drives all component make/buy decisions into the architecture process.

  4. Team Cohesion: Successful teams are cohesive, and cohesive teams are successful. Advances in technology (such as programming languages, UML, and visual modelling) have enabled more rigorous and understandable notations for communicating software engineering information, particularly in the requirements and design artifacts that previously were ad hoc and based completely on paper exchange. These model-based formats have also enabled the round-trip engineering support needed to establish change freedom sufficient for evolving design representations.

  5. Software Process Maturity: The Software Engineering Institute's Capability Maturity Model (CMM) is a well-accepted benchmark for software process assessment. One of the key themes is that truly mature processes are enabled through an integrated environment that provides the appropriate level of automation to instrument the process for objective quality control.

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