Difference between pages "System Life Cycle Process Models: Iterative" and "Life Cycle Models"

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There are a large number of [[Life Cycle Models|life cycle process models]]. As discussed in the [[System Life Cycle Process Drivers and Choices]] article, these models fall into three major categories: (1) primarily pre-specified and sequential processes; (2) primarily evolutionary and concurrent processes (e.g., the rational unified process and various forms of the Vee and spiral models); and (3) primarily interpersonal and unconstrained processes (e.g., agile development, Scrum, extreme programming (XP), dynamic system development methods, and innovation-based processes).
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The life cycle model is one of the key concepts of systems engineering (SE).  A {{Term|Life Cycle (glossary)|life cycle}} for a {{Term|System (glossary)|system}} generally consists of a series of {{Term|Stage (glossary)|stages}} regulated by a set of management decisions which confirm that the system is mature enough to leave one stage and enter another.  
  
This article discusses incremental and evolutionary development models (the second and third categories listed above) beyond variants of the [[System Life Cycle Process Models: Vee|Vee model]].  While there are a number of different models describing the project environment, the spiral model and the Vee Model have become the dominant approaches to visualizing the development process. Both the Vee and the spiral are useful models that emphasize different aspects of a system life cycle.
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==Topics==
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Each part of the SEBoK is divided into knowledge areas (KAs), which are groupings of information with a related theme. The KAs in turn are divided into topics. This KA contains the following topics:
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*[[System Life Cycle Process Drivers and Choices]]
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*[[System Life Cycle Process Models: Vee]]
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*[[System Life Cycle Process Models: Iterative]]
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*[[Integration of Process and Product Models]]
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*[[Lean Engineering]]
  
General implications of using iterative models for system design and development are discussed below. For a more specific understanding of how this life cycle model impacts systems engineering activities, please see the other knowledge areas (KAs) in Part 3. This article is focused on the use of iterative life cycle process models in systems engineering; however, because iterative process models are commonly used in software development, many of the examples below come from software projects. (See [[Systems Engineering and Software Engineering]] in [[Related Disciplines|Part 6]] for more information on life cycle implications in software engineering.)
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See the article [[Matrix of Implementation Examples]] for a mapping of case studies and vignettes included in Part 7 to topics covered in Part 3.
  
==Incremental and Evolutionary Development ==
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==Type of Value Added Products/Services==
===Overview of the Incremental Approach===
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The [[Generic Life Cycle Model]] shows just the single-step approach for proceeding through the stages of a system’s life cycle.  Adding value (as a product, a service, or both), is a shared purpose among all enterprises, whether public or private, for profit or non-profit. Value is produced by providing and integrating the elements of a system into a product or service according to the system description and transitioning it into productive use. These value considerations will lead to various forms of the generic life cycle management approach in Figure 1. Some examples are as follows (Lawson 2010):
  
Incremental and iterative development (IID) methods have been in use since the 1960s (and perhaps earlier). They allow a project to provide an initial capability followed by successive deliveries to reach the desired {{Term|System-of-Interest (glossary)|system-of-interest}} (SoI).
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* A manufacturing enterprise produces nuts, bolts, and lock washer products and then sells their products as value added elements to be used by other enterprises; in turn, these enterprises integrate these products into their more encompassing value-added system, such as an aircraft or an automobile. Their requirements will generally be pre-specified by the customer or by industry standards.
  
The IID approach, shown in Figure 1, is used when
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* A wholesaling or retailing enterprise offers products to their customers. Its customers (individuals or enterprises) acquire the products and use them as elements in their systems.  The enterprise support system will likely evolve opportunistically, as new infrastructure capabilities or demand patterns emerge.
  
*rapid exploration and implementation of part of the system is desired;
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* A commercial service enterprise such as a bank sells a variety of ''products'' as services to their customers. This includes current accounts, savings accounts, loans, and investment management. These services add value and are incorporated into customer systems of individuals or enterprises. The service enterprise’s support system will also likely evolve opportunistically, as new infrastructure capabilities or demand patterns emerge.
*the requirements are unclear from the beginning;
 
*funding is constrained;
 
*the customer wishes to hold the SoI open to the possibility of inserting new technology at a later time; and/or
 
*experimentation is required to develop successive {{Term|prototype (glossary)|prototype (glossary)}} versions.
 
  
The attributes that distinguish IID from the single-pass, plan-driven approach are velocity and adaptability. 
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* A governmental service enterprise provides citizens with services that vary widely, but may include services such as health care, highways and roads, pensions, law enforcement, or defense. Where appropriate, these services become infrastructure elements utilized in larger encompassing systems of interest to individuals and/or enterprises. Major initiatives, such as a next-generation air traffic control system or a metropolitan-area crisis management system (hurricane, typhoon, earthquake, tsunami, flood, fire), will be sufficiently complex enough to follow an evolutionary development and fielding approach. At the elemental level, there will likely be pre-specified single-pass life cycles.
 
[[File:KF_IncrementalDevelopment_Multiple.png|frame|center|600px|'''Figure 1. Incremental Development with Multiple Deliveries (Forsberg, Mooz, and Cotterman 2005).''' Reprinted with permission of John Wiley & Sons Inc. All other rights are reserved by the copyright owner.]]
 
 
 
Incremental development may also be “plan-driven” in nature if the requirements are known early on in the life cycle. The development of the functionality is performed incrementally to allow for insertion of the latest technology or for potential changes in needs or requirements. IID also imposes constraints. The example shown in Figure 2 uses the increments to develop high-risk subsystems (or components) early, but the system cannot function until all increments are complete.
 
 
 
[[File:Incremental_Development_with_a_single_delivery.PNG|thumb|center|600px|'''Figure 2. Incremental Development with a Single Delivery (Forsberg, Mooz, Cotterman 2005).''' Reprinted with permission of John Wiley & Sons Inc. All other rights are reserved by the copyright owner.]]
 
 
 
===Overview of the Evolutionary Approach===
 
A specific IID methodology called evolutionary development is common in research and development (R&D) environments in both the government and commercial sector. Figure 3 illustrates this approach, which was used in the evolution of the high temperature tiles for the NASA Space Shuttle (Forsberg 1995). In the evolutionary approach, the end state of each phase of development is unknown, though the goal is for each phase to result in some sort of useful product. 
 
 
 
[[File:Evolutionary_Generic_Model.PNG|thumb|center|600px|'''Figure 3. Evolutionary Generic Model (Forsberg, Mooz, Cotterman 2005).''' Reprinted with permission of John Wiley & Sons, Inc. All other rights are reserved by the copyright owner.]]
 
 
 
The real world development environment is complex and difficult to map because many different project cycles are simultaneously underway. Figure 4 shows the applied research era for the development of the space shuttle Orbiter and illustrates multi-levels of simultaneous development, trade-studies, and ultimately, implementation.
 
 
 
[[File:KF_EvolutionComponents_Orbiter.png|thumb|center|600px|'''Figure 4. Evolution of Components and Orbiter Subsystems (including space shuttle tiles) During Creation of a Large "Single-Pass" Project (Forsberg 1995).''' Reprinted with permission of Kevin Forsberg. All other rights are reserved by the copyright owner.]]
 
 
 
==Iterative Software Development Process Models==
 
 
 
Software is a flexible and malleable medium which facilitates iterative [[System Analysis|analysis]], [[System Definition|design]], [[System Realization|construction]], [[System Verification |verification]], and [[System Validation|validation]] to a greater degree than is usually possible for the purely physical components of a system. Each repetition of an iterative development model adds material (code) to the growing software base; the expanded code base is tested, reworked as necessary, and demonstrated to satisfy the requirements for the baseline.
 
 
 
Process models for software development support iterative development on cycles of various lengths. Table 1 lists three iterative software development models which are presented in more detail below, as well as the aspects of software development that are emphasized by those models.
 
 
 
<center>
 
{|
 
|+'''Table 1. Primary Emphases of Three Iterative Software Development Models.'''
 
(SEBoK Original)
 
!Iterative Model
 
!Emphasis
 
|-
 
|'''Incremental-build'''
 
|Iterative implementation-verification-validations-demonstration cycles
 
|-
 
|'''Spiral'''
 
|Iterative risk-based analysis of alternative approaches and evaluation of outcomes
 
|-
 
|'''Agile'''
 
|Iterative evolution of requirements and code
 
|}
 
</center>
 
 
 
Please note that the information below is focused specifically on the utilization of different life cycle models for software systems. In order to better understand the interactions between software engineering (SwE) and systems engineering (SE), please see the [[Systems Engineering and Software Engineering]] KA in [[Related Disciplines|Part 6]].
 
 
 
===Overview of Iterative-Development Process Models===
 
Developing and modifying software involves creative processes that are subject to many external and changeable forces. Long experience has shown that it is impossible to “get it right” the first time, and that iterative development processes are preferable to linear, sequential development process models, such as the well-known Waterfall model. In iterative development, each cycle of the iteration subsumes the software of the previous iteration and adds new capabilities to the evolving product to create an expanded version of the software.  Iterative development processes provide the following advantages:
 
 
 
*Continuous integration, verification, and validation of the evolving product;
 
*Frequent demonstrations of progress;
 
*Early detection of defects;
 
*Early warning of process problems;
 
*Systematic incorporation of the inevitable rework that occurs in software development; and
 
*Early delivery of subset capabilities (if desired).
 
 
 
Iterative development takes many forms in SwE, including the following:
 
 
 
*An incremental-build process, which is used to produce periodic (typically weekly) builds of increasing product capabilities;
 
*Agile development, which is used to closely involve a prototypical customer in an iterative process that may repeat on a daily basis; and
 
*The spiral model, which is used to confront and mitigate risk factors encountered in developing the successive versions of a product.
 
 
 
==The Incremental-Build Model==
 
The incremental-build model is a build-test-demonstrated model of iterative cycles in which frequent demonstrations of progress, verification, and validation of work-to-date are emphasized. The model is based on stable requirements and a software architectural specification. Each build adds new capabilities to the incrementally growing product. The process ends when the final version is verified, validated, demonstrated, and accepted by the customer.
 
 
 
Table 2 lists some partitioning criteria for incremental development into incremental build units of (typically) one calendar week each. The increments and the number of developers available to work on the project determine the number of features that can be included in each incremental build. This, in turn, determines the overall schedule.
 
 
 
<center>
 
{|
 
|+'''Table 2.  Some partitioning criteria for incremental builds (Fairley 2009).''' Reprinted with permission of the IEEE Computer Society and John Wiley & Sons Inc. All other rights are reserved by the copyright owner.
 
!Kind of System
 
!Partitioning Criteria
 
|-
 
|Application package
 
|Priority of features
 
|-
 
|Safety-critical systems
 
|Safety features first; prioritized others follow
 
|-
 
|User-intensive systems
 
|User interface first; prioritized others follow
 
|-
 
|System software
 
|Kernel first; prioritized utilities follow
 
|}
 
</center>
 
 
 
Figure 5 illustrates the details of the build-verify-validate-demonstrate cycles in the incremental build process. Each build includes detailed design, coding, integration, review, and testing done by the developers. In cases where code is to be reused without modification, some or all of an incremental build may consist of review, integration, and testing of the base code augmented with the reused code.  It is important to note that development of an increment may result in reworking previous components developed for integration to fix defects.
 
 
 
[[File:KF_IncrementalBuildCycles.png|frame|center|600px|'''Figure 5. Incremental Build-Verify-Validate-Demonstrate Cycles (Fairley 2009).''' Reprinted with permission of the IEEE Computer Society and John Wiley & Sons Inc. All other rights are reserved by the copyright owner.]]
 
 
 
Incremental verification, validation, and demonstration, as illustrated in Figure 5, overcome two of the major problems of a waterfall approach by
 
*exposing problems early so they can be corrected as they occur; and
 
*incorporating minor in-scope changes to requirements that occur as a result of incremental demonstrations in subsequent builds.
 
 
 
Figure 5 also illustrates that it may be possible to overlap successive builds of the product. It may be possible, for example, to start a detailed design of the next version while the present version is being validated.
 
 
 
Three factors determine the degree of overlap that can be achieved:
 
 
 
#Availability of personnel;
 
#Adequate progress on the previous version; and
 
#The risk of significant rework on the next overlapped build because of changes to the previous in-progress build.
 
 
 
The incremental build process generally works well with small teams, but can be scaled up for larger projects.
 
  
A significant advantage of an incremental build process is that features built first are verified, validated, and demonstrated most frequently because subsequent builds incorporate the features of the earlier iterations. In building the software to control a nuclear reactor, for example, the emergency shutdown software could be built first, as it would then be verified and validated in conjunction with the features of each successive build.
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* For aircraft and automotive systems, there would likely be a pre-specified multiple-pass life cycle to capitalize on early capabilities in the first pass, but architected to add further value-adding capabilities in later passes.  
  
In summary, the incremental build model, like all iterative models, provides the advantages of continuous integration and validation of the evolving product, frequent demonstrations of progress, early warning of problems, early delivery of subset capabilities, and systematic incorporation of the inevitable rework that occurs in software development.
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* A diversified software development enterprise provides software products that meet stakeholder requirements (needs), thus providing services to product users.  It will need to be developed to have capabilities that can be tailored to be utilized in different customers’ life-cycle approaches and also with product-line capabilities that can be quickly and easily applied to similar customer system developments. Its business model may also include providing the customer with system life-cycle support and evolution capabilities.
  
===The Role of Prototyping in Software Development===
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Within these examples, there are systems that remain stable over reasonably long periods of time and those that change rapidly. The diversity represented by these examples and their processes illustrate why there is no one-size-fits-all process that can be used to define a specific systems life cycle. Management and leadership approaches must consider the type of systems involved, their longevity, and the need for rapid adaptation to unforeseen changes, whether in competition, technology, leadership, or mission priorities. In turn, the management and leadership approaches impact the type and number of life cycle models that are deployed as well as the processes that will be used within any particular life cycle.
In SwE, a {{Term|Prototype (glossary)|prototype}} is a mock-up of the desired functionality of some part of the system. This is in contrast to physical systems, where a {{Term|prototype (glossary)|prototype}} is usually the first fully functional version of a system (Fairley 2009, 74).
 
  
In the past, incorporating prototype software into production systems has created many problems.  Prototyping is a useful technique that should be employed as appropriate; however, prototyping is ''not'' a process model for software development. When building a software prototype, the knowledge gained through the development of the prototype is beneficial to the program; however, the prototype code may not be used in the deliverable version of the system. In many cases, it is more efficient and more effective to build the production code from scratch using the knowledge gained by prototyping than to re-engineer the existing code.
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There are several incremental and evolutionary approaches for sequencing the life cycle stages to deal with some of the issues raised above. The [[Life Cycle Models]] knowledge area summarizes a number of {{Term|Incremental (glossary)|incremental}} and {{Term|Evolutionary (glossary)|evolutionary}} life cycle models, including their main strengths and weaknesses and also discusses criteria for choosing the best-fit approach.
  
===Life Cycle Sustainment of Software===
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==Categories of Life Cycle Model==
Software, like all systems, requires sustainment efforts to enhance capabilities, adapt to new environments, and correct defects. The primary distinction for software is that sustainment efforts change the software; unlike physical entities, software components do not have to be replaced because of physical wear and tear. Changing the software requires {{Term|verification (glossary)|re-verification}} and {{Term|validation (glossary)|re-validation}}, which may involve extensive regression testing to determine that the change has the desired effect and has not altered other aspects of functionality or behavior.
 
  
===Retirement of Software===
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The Generic System Life Cycle Model in Figure 1 does not explicitly fit all situations. A simple, precedential, follow-on system may need only one phase in the definition stage, while a complex system may need more than two.  With build-upon systems (vs. throwaway) {{Term|Prototype (glossary)|prototypes}}, a good deal of development may occur during the definition stage.  System {{Term|Integration (glossary)|integration}}, {{Term|Verification (glossary)|verification}}, and {{Term|Validation (glossary)|validation}} may follow implementation or acquisition of the system elements.  With software, particularly test-first and daily builds, integration, verification, and validation are interwoven with element implementation.  Additionally, with the upcoming ''Third Industrial Revolution'' of three-dimensional printing and digital manufacturing (Whadcock 2012), not only initial development but also initial production may be done during the concept stage.
Useful software is rarely retired; however, software that is useful often experiences many upgrades during its lifetime. A later version may bear little resemblance to the initial release. In some cases, software that ran in a former operational environment is executed on hardware emulators that provide a virtual machine on newer hardware. In other cases, a major enhancement may replace and rename an older version of the software, but the enhanced version provides all of the capabilities of the previous software in a compatible manner. Sometimes, however, a newer version of software may fail to provide compatibility with the older version, which necessitates other changes to a system.
 
  
==Primarily Evolutionary and Concurrent Processes: The Incremental Commitment Spiral Model==
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Software is a flexible and malleable medium which facilitates iterative analysis, design, construction, verification, and validation to a greater degree than is usually possible for the purely physical components of a system. Each repetition of an iterative development model adds material (code) to the growing software base, in which the expanded code base is tested, reworked as necessary, and demonstrated to satisfy the requirements for the baseline.
===Overview of the Incremental Commitment Spiral Model===
 
  
A view of the Incremental Commitment Spiral Model (ICSM) is shown in Figure 6.
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Software can be electronically bought, sold, delivered, and upgraded anywhere in the world within reach of digital communication, making its logistics significantly different and more cost-effective than hardware.  It does not wear out and its fixes change its content and behavior, making regression testing more complex than with hardware fixes.  Its discrete nature dictates that its testing cannot count on analytic continuity as with hardware.  Adding 1 to 32767 in a 15-bit register does not produce 32768, but 0 instead, as experienced in serious situations, such as with the use of the Patriot Missile.
  
[[File:KF_IncrementalCommitmentSpiral.png|thumb|center|900px|'''Figure 6. The Incremental Commitment Spiral Model (ICSM) (Pew and Mavor 2007).''' Reprinted with permission by the National Academy of Sciences, Courtesy of National Academies Press, Washington, D.C. All other rights are reserved by the copyright owner.]]
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There are a large number of potential {{Term|Life Cycle Process (glossary)|life cycle process}} models. They fall into three major categories:
 
   
 
   
In the ICSM, each spiral addresses requirements and solutions concurrently, rather than sequentially, as well as products and processes, hardware, software, and human factors aspects, and business case analyses of alternative product configurations or product line investments. The stakeholders consider the risks and risk mitigation plans and decide on a course of action. If the risks are acceptable and covered by risk mitigation plans, the project proceeds into the next spiral.  
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# primarily pre-specified and sequential processes (e.g. the single-step waterfall model)
 
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# primarily evolutionary and concurrent processes (e.g. lean development, the rational unified process, and various forms of the vee and spiral models)  
The development spirals after the first development commitment review follow the three-team incremental development approach for achieving both agility and assurance shown and discussed in Figure 2, "Evolutionary-Concurrent Rapid Change Handling and High Assurance" of [[System Life Cycle Process Drivers and Choices]].
+
# primarily interpersonal and emergent processes (e.g. agile development, scrum, extreme programming (XP), the dynamic system development method, and innovation-based processes)  
 
 
===Other Views of the Incremental Commitment Spiral Model===
 
Figure 7 presents an updated view of the ICSM life cycle process recommended in the National Research Council ''Human-System Integration in the System Development Process'' study (Pew and Mavor 2007). It was called the Incremental Commitment Model (ICM) in the study. The ICSM builds on the strengths of current process models, such as early verification and validation concepts in the [[System Life Cycle Process Models: Vee|Vee model]], concurrency concepts in the concurrent engineering model, lighter-weight concepts in the agile and lean models, risk-driven concepts in the spiral model, the phases and anchor points in the rational unified process (RUP) (Kruchten 1999; Boehm 1996), and recent extensions of the spiral model to address systems of systems (SoS) capability acquisition (Boehm and Lane 2007).
 
 
 
[[File:KF_Phase_GenericIncremental.png|thumb|center|900px|'''Figure 7. Phased View of the Generic Incremental Commitment Spiral Model Process (Pew and Mavor 2007).''' Reprinted with permission by the National Academy of Sciences, Courtesy of National Academies Press, Washington, D.C. All other rights are reserved by the copyright owner.]]
 
 
 
The top row of activities in Figure 7 indicates that a number of system aspects are being concurrently engineered at an increasing level of understanding, definition, and development. The most significant of these aspects are shown in Figure 8, an extension of a similar ''“hump diagram”'' view of concurrently engineered software activities developed as part of the RUP (Kruchten 1999).
 
 
 
[[File:KF_ICSMActivityCategories.png|thumb|center|900px|'''Figure 8. ICSM Activity Categories and Level of Effort (Pew and Mavor 2007).''' Reprinted with permission by the National Academy of Sciences, Courtesy of National Academies Press, Washington, D.C. All other rights are reserved by the copyright owner.]]
 
 
 
As with the RUP version, the magnitude and shape of the levels of effort will be risk-driven and likely to vary from project to project. Figure 8 indicates that a great deal of concurrent activity occurs within and across the various ICSM phases, all of which need to be ''"synchronized and stabilized,"'' a best-practice phrase taken from ''Microsoft Secrets'' (Cusumano and Selby 1996) to keep the project under control. 
 
 
 
The review processes and use of independent experts are based on the highly successful AT&T Architecture Review Board procedures described in “Architecture Reviews: Practice and Experience” (Maranzano et al. 2005). Figure 9 shows the content of the feasibility evidence description. Showing feasibility of the concurrently-developed elements helps synchronize and stabilize the concurrent activities.
 
 
 
[[File:KF_FeasibilityEvidenceDescription.png|thumb|center|1100px|'''Figure 9. Feasibility Evidence Description Content (Pew and Mavor 2007).''' Reprinted with permission by the National Academy of Sciences, Courtesy of National Academies Press, Washington, D.C. All other rights are reserved by the copyright owner.]]
 
 
 
The operations commitment review (OCR) is different in that it addresses the often higher operational risks of fielding an inadequate system. In general, stakeholders will experience a two- to ten-fold increase in commitment level while going through the sequence of engineering certification review (ECR) to design certification review (DCR) {{Term|Milestone (glossary)|milestones}}, but the increase in going from DCR to OCR can be much higher. These commitment levels are based on typical cost profiles across the various stages of the acquisition life cycle.
 
 
 
===Underlying ICSM Principles===
 
ICSM has four underlying principles which must be followed:
 
#Stakeholder value-based system definition and evolution;
 
#Incremental commitment and accountability;
 
#Concurrent system and software definition and development; and
 
#Evidence and risk-based decision making.
 
 
 
===Model Experience to Date===
 
 
 
The National Research Council Human-Systems Integration study (2008) found that the ICSM processes and principles correspond well with best commercial practices, as described in the [[Next Generation Medical Infusion Pump Case Study]] in Part 7.  Further examples are found in ''Human-System Integration in the System Development Process: A New Look'' (Pew and Mavor 2007, chap. 5), ''Software Project Management'' (Royce 1998, Appendix D), and the annual series of "Top Five Quality Software Projects", published in CrossTalk (2002-2005).
 
 
 
==Agile and Lean Processes==
 
 
 
According to the INCOSE ''Systems Engineering Handbook'' 3.2.2, ''“Project execution methods can be described on a continuum from 'adaptive' to 'predictive.' Agile methods exist on the 'adaptive' side of this continuum, which is not the same as saying that agile methods are 'unplanned' or 'undisciplined,'” ''(INCOSE 2011, 179). Agile development methods can be used to support iterative life cycle models, allowing flexibility over a linear process that better aligns with the planned life cycle for a system. They primarily emphasize the development and use of tacit interpersonal knowledge as compared to explicit documented knowledge, as evidenced in the four value propositions in the '''"Agile Manifesto"''':
 
 
 
<blockquote>''We are uncovering better ways of developing software by doing it and helping others do it. Through this work we have come to value'' </blockquote>
 
<blockquote>
 
* '''''Individuals and interactions''' over processes and tools;''
 
* '''''Working software''' over comprehensive documentation;''
 
* '''''Customer collaboration''' over contract negotiation; and''
 
* '''''Responding to change''' over following a plan.''
 
</blockquote>
 
<blockquote>''That is, while there is value in the items on the right, we value the items on the left more.''  (Agile Alliance 2001)</blockquote>
 
 
 
Lean processes are often associated with agile methods, although they are more scalable and applicable to high-assurance systems.  Below, some specific agile methods are presented, and the evolution and content of lean methods is discussed. Please see "Primary References", "Additional References", and the [[Lean Engineering]] article for more detail on specific agile and lean processes.
 
 
 
===Scrum===
 
Figure 10 shows an example of Scrum as an agile process flow. As with most other agile methods, Scrum uses the evolutionary sequential process shown in Table 1 (above) and described in [[System Life Cycle Process Drivers and Choices#Fixed-Requirements and Evolutionary Development Processes|Fixed-Requirements and Evolutionary Development Processes]] section in which systems capabilities are developed in short periods, usually around 30 days. The project then re-prioritizes its backlog of desired features and determines how many features the team (usually 10 people or less) can develop in the next 30 days.
 
 
 
Figure 10 also shows that once the features to be developed for the current Scrum have been expanded (usually in the form of informal stories) and allocated to the team members, the team establishes a daily rhythm of starting with a short meeting at which each team member presents a roughly one-minute summary describing progress since the last Scrum meeting, potential obstacles, and plans for the upcoming day.
 
 
 
[[File:Tale_of_Two_Implementations_Schwaber.jpg|thumb|center|600px|'''Figure 10. Example Agile Process Flow: Scrum (Boehm and Turner 2004).''' Reprinted with permission of Ken Schwaber. All other rights are reserved by the copyright owner.]]
 
 
 
====Architected Agile Methods====
 
Over the last decade, several organizations have been able to scale up agile methods by using two layers of ten-person Scrum teams. This involves, among other things, having each Scrum team’s daily meeting followed up by a daily meeting of the Scrum team leaders discussing up-front investments in evolving system architecture (Boehm et al. 2010). Figure 11 shows an example of the Architected Agile approach.
 
 
 
[[File:Example_of_Architected_Agile_Process_Replacement_070912.png|thumb|center|650px|'''Figure 11. Example of Architected Agile Process (Boehm 2009).''' Reprinted with permission of Barry Boehm on behalf of USC-CSSE. All other rights are reserved by the copyright owner.]]
 
 
 
===Agile Practices and Principles===
 
As seen with the Scrum and architected agile methods, "generally-shared" principles are not necessarily "uniformly followed". However, there are some general practices and principles shared by most agile methods:
 
 
 
*The project team understands, respects, works, and behaves within a defined SE process;
 
*The project is executed as fast as possible with minimum down time or staff diversion during the project and the critical path is managed;
 
*All key players are physically or electronically collocated, and "notebooks" are considered team property available to all.
 
*Baseline management and change control are achieved by formal, oral agreements based on “make a promise—keep a promise” discipline. Participants hold each other accountable.
 
*Opportunity exploration and risk reduction are accomplished by expert consultation and rapid model verification coupled with close customer collaboration; software development is done in a rapid development environment while hardware is developed in a multi-disciplined model shop; and
 
*A culture of constructive confrontation pervades the project organization. The team takes ownership for success; it is never “someone else’s responsibility.”
 
 
 
Agile development principles (adapted for SE) are as follows (adapted from ''Principles behind the Agile Manifesto'' (Beedle et al. 2009)):
 
 
 
#First, satisfy the customer through early and continuous delivery of valuable software (and other system elements).
 
#Welcome changing requirements, even late in development; agile processes harness change for the customer’s competitive advantage.
 
#Deliver working software (and other system elements) frequently, from a couple of weeks to a couple of months, with a preference to the shorter timescale.
 
#Business personnel and developers must work together daily throughout the project.
 
#Build projects around motivated individuals; give them the environment, support their needs, and trust them to get the job done.
 
#The most efficient and effective method of conveying information is face-to-face conversation.
 
#Working software (and other system elements) is the primary measure of progress.
 
#Agile processes promote sustainable development; the sponsors, developers, and users should be able to maintain a constant pace indefinitely.
 
#Continuous attention to technical excellence and good design enhances agility.
 
#Simplicity—the art of maximizing the amount of work not done—is essential.
 
#The best architectures, requirements, and designs emerge from self-organizing teams.
 
 
 
A team should reflect on how to become more effective at regular intervals and then tune and adjust its behavior accordingly. This self-reflection is a critical aspect for projects that implement agile processes.
 
 
 
===Lean Systems Engineering and Development===
 
 
 
====Origins====
 
As the manufacturing of consumer products such as automobiles became more diversified, traditional pre-planned mass-production approaches had increasing problems with quality and adaptability.  Lean manufacturing systems such as the Toyota Production System (TPS) (Ohno 1988) were much better suited to accommodate diversity, to improve quality, and to support just-in-time manufacturing that could rapidly adapt to changing demand patterns without having to carry large, expensive inventories.
 
 
 
Much of this transformation was stimulated by the work of W. Edwards Deming, whose Total Quality Management (TQM) approach shifted responsibility for quality and productivity from planners and inspectors to the production workers who were closer to the real processes (Deming 1982). Deming's approach involved everyone in the manufacturing organization in seeking continuous process improvement, or "Kaizen".
 
  
Some of the TQM techniques, such as statistical process control and repeatability, were more suited to repetitive manufacturing processes than to knowledge work such as systems engineering (SE) and software engineering (SwE).  Others, such as early error elimination, waste elimination, workflow stabilization, and Kaizen, were equally applicable to knowledge workLed by Watts Humphrey, TQM became the focus for the Software Capability Maturity Model (Humphrey 1987; Paulk et al. 1994) and the CMM-Integrated or CMMI, which extended its scope to include systems engineering (Chrissis et al. 2003).  One significant change was the redefinition of Maturity Level 2 from "Repeatable" to "Managed".
+
The emergence of integrated, interactive hardware-software systems made pre-specified processes potentially harmful, as the most effective human-system interfaces tended to emerge with its use, leading to further process variations, such as soft SE (Warfield 1976, Checkland 1981) and human-system integration processes (Booher 2003, Pew and Mavor 2007).  Until recently, process standards and maturity models have tried to cover every eventuality.  They have included extensive processes for acquisition management, source selection, reviews and audits, quality assurance, configuration management, and document management, which in many instances would become overly bureaucratic and inefficientThis led to the introduction of more lean (Ohno 1988; Womack et al. 1990; Oppenheim 2011) and agile (Beck 1999; Anderson 2010) approaches to concurrent hardware-software-human factors approaches such as the concurrent vee models (Forsberg 1991; Forsberg 2005) and Incremental Commitment Spiral Model (Pew and Mavor 2007; Boehm and Lane 2007).
  
The Massachusetts Institute of Technology (MIT) conducted studies of the TPS, which produced a similar approach that was called the "Lean Production System" (Krafcik 1988; Womack et al. 1990).  Subsequent development of "lean thinking" and related work at MIT led to the Air Force-sponsored Lean Aerospace Initiative (now called the Lean Advancement Initiative), which applied lean thinking to SE (Murman 2003, Womack-Jones 2003).  Concurrently, lean ideas were used to strengthen the scalability and dependability aspects of agile methods for software (Poppendieck 2003; Larman-Vodde 2009). The Kanban flow-oriented approach has been successfully applied to software development (Anderson 2010).
+
In the next article on [[System Life Cycle Process Drivers and Choices]], these variations on the theme of life cycle models will be identified and presented.
  
====Principles====
+
==Systems Engineering Responsibility==
Each of these efforts has developed a similar but different set of Lean principles. For systems engineering, the current best source is ''Lean for Systems Engineering'', the product of several years’ work by the INCOSE Lean SE working group (Oppenheim 2011).  It is organized into six principles, each of which is elaborated into a set of lean enabler and sub-enabler patterns for satisfying the principle:
+
Regardless of the life cycle models deployed, the role of the systems engineer encompasses the entire life cycle of the system-of-interest. Systems engineers orchestrate the development and evolution of a solution, from defining requirements through operation and ultimately until system retirement. They ensure that domain experts are properly involved, all advantageous opportunities are pursued, and all significant risks are identified and, when possible, mitigated. The systems engineer works closely with the project manager in tailoring the generic life cycle, including key {{Term|Decision Gate (glossary)|decision gates}}, to meet the needs of their specific project.
  
#'''Value.''' Guide the project by determining the value propositions of the customers and other key stakeholders. Keep them involved and manage changes in their value propositions.
+
Systems engineering tasks are usually concentrated at the beginning of the life cycle; however, both commercial and government organizations recognize the need for SE throughout the system’s life cycle. Often this ongoing effort is to modify or change a system, product or service after it enters production or is placed in operation. Consequently, SE is an important part of all life cycle stages. During the production, support, and utilization (PSU) stages, for example, SE executes performance analysis, interface monitoring, failure analysis, logistics analysis, tracking, and analysis of proposed changes. All these activities are essential to ongoing support of the system.  
#'''Map the Value Stream (Plan the Program).'''  This includes thorough requirements specification, the concurrent exploration of trade spaces among the value propositions, COTS evaluation, and technology maturity assessment, resulting in a full project plan and set of requirements.
 
#'''Flow.'''  Focus on careful attention to the project’s critical path activities to avoid expensive work stoppages, including coordination with external suppliers.
 
#'''Pull.'''  Pull the next tasks to be done based on prioritized needs and dependencies.  If a need for the task can’t be found, reject it as waste.
 
#'''Perfection.'''  Apply continuous process improvement to approach perfection.  Drive defects out early to get the system Right The First #'''Time,''' vs. fixing them during inspection and test.  Find and fix root causes rather than symptoms.
 
#'''Respect for People.'''  Flow down responsibility, authority, and accountability to all personnel.  Nurture a learning environment.  Treat people as the organization’s most valued assets. (Oppenheim 2011)
 
  
These lean SE principles are highly similar to the four underlying incremental commitment spiral model principles.
+
All project managers must ensure that the business aspect (cost, schedule, and value) and the technical aspect of the project cycle remain synchronized. Often, the technical aspect drives the project. It is the systems engineers’ responsibility to ensure that the technical solutions that are being considered are consistent with the cost and schedule objectives. This can require working with the users and customers to revise objectives to fit within the business bounds. These issues also drive the need for decision gates to be appropriately spaced throughout the project cycle. Although the nature of these decision gates will vary by the major categories above, each will involve {{Term|In-Process Validation (glossary)|in-process validation}} between the developers and the end users. In-process validation asks the question: ''“Will what we are planning or creating satisfy the stakeholders’ needs?”'' In-process validation begins at the initialization of the project during user needs discovery and continues through daily activities, formal decision gate reviews, final product or solution delivery, operations, and ultimately to system closeout and disposal.
  
*'''Principle 1: Stakeholder value-based system definition and evolution''', addresses the lean SE principles of value, value stream mapping, and respect for people (developers are success-critical stakeholders in the ICSM).
+
==References==
*'''Principle 2: Incremental commitment and accountability''', partly addresses the pull principle, and also addresses respect for people (who are accountable for their commitments).
 
*'''Principle 3: Concurrent system and software definition and development''', partly addresses both value stream mapping and flow.
 
*'''Principle 4: Evidence and risk-based decision making''', uses evidence of achievability as its measure of success. Overall, the ICSM principles are somewhat light on continuous process improvement, and the lean SE principles are somewhat insensitive to requirements emergence in advocating a full pre-specified project plan and set of requirements.
 
  
See [[Lean Engineering]] for more information.
 
 
==References==
 
  
 
===Works Cited===
 
===Works Cited===
 +
Anderson, D. 2010. ''Kanban.'' Sequim, WA: Blue Hole Press.
  
Agile Alliance. 2001. “Manifesto for Agile Software Development.” http://agilemanifesto.org/.
+
Beck, K. 1999. ''Extreme Programming Explained.'' Boston, MA: Addison Wesley.
  
Anderson, D. 2010. ''Kanban'', Sequim, WA: Blue Hole Press.
+
Boehm, B. and J. Lane. 2007. “Using the Incremental Commitment Model to Integrate System Acquisition, Systems Engineering, and Software Engineering.” ''CrossTalk''. October 2007: 4-9.
 
+
Boehm, B. 1996. "Anchoring the Software Process." IEEE ''Software'' 13(4): 73-82.
+
Booher, H. (ed.) 2003. ''Handbook of Human Systems Integration''. Hoboken, NJ, USA: Wiley.  
 
 
Boehm, B. and J. Lane. 2007. “Using the Incremental Commitment Model to Integrate System Acquisition, Systems Engineering, and Software Engineering.” ''CrossTalk.'' 20(10) (October 2007): 4-9.
 
 
 
Boehm, B., J. Lane, S. Koolmanjwong, and R. Turner. 2010. “Architected Agile Solutions for Software-Reliant Systems,” in Dingsoyr, T., T. Dyba., and N. Moe (eds.), ''Agile Software Development: Current Research and Future Directions.'' New York, NY, USA: Springer.
 
 
 
Boehm, B. and R. Turner. 2004. ''Balancing Agility and Discipline.''  New York, NY, USA: Addison-Wesley.
 
 
 
Castellano, D.R. 2004. “Top Five Quality Software Projects.” ''CrossTalk.'' 17(7) (July 2004): 4-19. Available at: http://www.crosstalkonline.org/storage/issue-archives/2004/200407/200407-0-Issue.pdf
 
 
 
Chrissis, M., M. Konrad, and S. Shrum. 2003. ''CMMI: Guidelines for Process Integration and Product Improvement.'' New York, NY, USA, Addison Wesley.
 
 
 
Deming, W.E. 1982. ''Out of the Crisis.'' Cambridge, MA, USA: MIT.
 
 
 
Fairley, R. 2009. ''Managing and Leading Software Projects.'' New York, NY, USA: John Wiley & Sons.
 
 
 
Forsberg, K. 1995. "If I Could Do That, Then I Could…’ System Engineering in a Research and Development Environment." Proceedings of the Fifth International Council on Systems Engineering (INCOSE) International Symposium. 22-26 July 1995. St Louis, MO, USA.
 
 
 
Forsberg, K., H. Mooz, and H. Cotterman. 2005. ''Visualizing Project Management,'' 3rd ed. New York, NY, USA: John Wiley & Sons.
 
 
 
Humphrey, W., 1987.  “Characterizing the Software Process: A Maturity Framework.” Pittsburgh, PA, USA: CMU Software Engineering Institute. CMU/SEI-87-TR-11.
 
  
Jarzombek, J. 2003. “Top Five Quality Software Projects.” ''CrossTalk.'' 16(7) (July 2003): 4-19. Available at: http://www.crosstalkonline.org/storage/issue-archives/2003/200307/200307-0-Issue.pdf.
+
Checkland, P. 1999. ''Systems Thinking, Systems Practice,'' 2nd ed. Hoboken, NJ, USA: Wiley.
 
   
 
   
Krafcik, J. 1988. "Triumph of the lean production system". ''Sloan Management Review.'' 30(1): 41–52.
+
Cusumano, M., and D. Yoffie. 1998. ''Competing on Internet Time'', New York, NY, USA: The Free Press.
  
Kruchten, P. 1999. ''The Rational Unified Process''. New York, NY, USA: Addison Wesley.
+
Forsberg, K. and H. Mooz. 1991. "The Relationship of System Engineering to the Project Cycle," ''Proceedings of INCOSE'', October 1991.
 
Larman , C. and B. Vodde. 2009. ''Scaling Lean and Agile Development.'' New York, NY, USA: Addison Wesley.
 
  
Maranzano, J.F., S.A. Rozsypal, G.H. Zimmerman, G.W. Warnken, P.E. Wirth, D.M. Weiss. 2005. “Architecture Reviews: Practice and Experience.” IEEE ''Software.'' 22(2): 34-43.
+
Forsberg, K., H. Mooz, and H. Cotterman. 2005. ''Visualizing Project Management'', 3rd ed. Hoboken, NJ: J. Wiley & Sons.
  
Murman, E. 2003. ''Lean Systems Engineering I, II, Lecture Notes'', MIT Course 16.885J, Fall. Cambridge, MA, USA: MIT.
+
ISO/IEC/IEEE. 2015.''[[ISO/IEC/IEEE 15288|Systems and software engineering - system life cycle processes]]''.Geneva, Switzerland: International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC), Institute of Electrical and Electronics Engineers.[[ISO/IEC/IEEE 15288|ISO/IEC 15288]]:2015.
  
Oppenheim, B. 2011. ''Lean for Systems Engineering.'' Hoboken, NJ: Wiley.  
+
Lawson, H. 2010. ''A Journey Through the Systems Landscape.'' London, UK: College Publications.
  
Paulk, M., C. Weber, B. Curtis, and M. Chrissis. 1994. ''The Capability Maturity Model: Guidelines for Improving the Software Process.'' Reading, MA, USA: Addison Wesley.  
+
Ohno, T. 1988. ''Toyota Production System''. New York, NY: Productivity Press.
  
Pew, R. and A. Mavor (eds.). 2007. ''Human-System Integration in The System Development Process: A New Look''. Washington, DC, USA: The National Academies Press.
+
Oppenheim, B. 2011.  ''Lean for Systems Engineering.'' Hoboken, NJ: Wiley.
+
 
Poppendieck, M. and T. Poppendieck. 2003. ''Lean Software Development: An Agile Toolkit for Software Development Managers.'' New York, NY, USA: Addison Wesley.  
+
Pew, R. and A. Mavor (eds.). 2007. ''Human-System Integration in The System Development Process: A New Look.'' Washington, DC, USA: The National Academies Press.
  
Spruill, N. 2002. “Top Five Quality Software Projects.” ''CrossTalk.'' 15(1) (January 2002): 4-19. Available at: http://www.crosstalkonline.org/storage/issue-archives/2002/200201/200201-0-Issue.pdf.
+
Warfield, J. 1976. ''Systems Engineering''. Washington, DC, USA: US Department of Commerce (DoC).
 
   
 
   
Stauder, T. “Top Five Department of Defense Program Awards.” ''CrossTalk.'' 18(9) (September 2005): 4-13. Available at http://www.crosstalkonline.org/storage/issue-archives/2005/200509/200509-0-Issue.pdf.
+
Whadcock, I. 2012. “A third industrial revolution.” ''The Economist.'' April 21, 2012.
 
Womack, J., D. Jones, and D Roos. 1990. ''The Machine That Changed the World: The Story of Lean Production.'' New York, NY, USA: Rawson Associates.
 
  
Womack, J. and D. Jones. 2003. ''Lean Thinking''. New York, NY, USA: The Free Press.
+
Womack, J.P., D.T. Jones, and D. Roos 1990. ''The Machine That Changed the World: The Story of Lean Production.'' New York, NY, USA: Rawson Associates.
  
 
===Primary References===
 
===Primary References===
Beedle, M., et al. 2009. "[[The Agile Manifesto: Principles behind the Agile Manifesto]]". in ''The Agile Manifesto''  [database online]. Accessed 2010. Available at: www.agilemanifesto.org/principles.html
+
Blanchard, B.S., and W.J. Fabrycky. 2011. ''[[Systems Engineering and Analysis]]'', 5th ed. Prentice-Hall International series in Industrial and Systems Engineering. Englewood Cliffs, NJ, USA: Prentice-Hall.
  
Boehm, B. and R. Turner. 2004. ''[[Balancing Agility and Discipline]].'' New York, NY, USA: Addison-Wesley.
+
Forsberg, K., H. Mooz, H. Cotterman. 2005. ''[[Visualizing Project Management]]'', 3rd Ed. Hoboken, NJ: J. Wiley & Sons.
  
Fairley, R. 2009. ''[[Managing and Leading Software Projects]].'' New York, NY, USA: J. Wiley & Sons.
+
INCOSE. 2012. ''[[INCOSE Systems Engineering Handbook | Systems Engineering Handbook]]'', version 3.2.2. San Diego, CA, USA: International Council on Systems Engineering (INCOSE). INCOSE-TP-2003-002-03.2.2.
  
Forsberg, K., H. Mooz, and H. Cotterman. 2005. ''[[Visualizing Project Management]],'' 3rd ed. New York, NY, USA: J. Wiley & Sons.
+
Lawson, H. 2010. ''[[A Journey Through the Systems Landscape]].''  London, UK: College Publications.
  
INCOSE. 2012. ''[[INCOSE Systems Engineering Handbook|Systems Engineering Handbook]]: A Guide for System Life Cycle Processes and Activities''. Version 3.2.2. San Diego, CA, USA: International Council on Systems Engineering (INCOSE), INCOSE-TP-2003-002-03.2.2.
+
Pew, R. and A. Mavor (Eds.). 2007. ''[[Human-System Integration in the System Development Process|Human-System Integration in The System Development Process: A New Look]].'' Washington, DC, USA: The National Academies Press.
 
 
Lawson, H. 2010. ''[[A Journey Through the Systems Landscape]].'' Kings College, UK: College Publications.
 
 
 
Pew, R., and A. Mavor (eds.). 2007. ''[[Human-System Integration in the System Development Process]]: A New Look.'' Washington, DC, USA: The National Academies Press.
 
 
 
Royce, W.E. 1998. ''[[Software Project Management]]: A Unified Framework''. New York,  NY, USA: Addison Wesley.
 
  
 
===Additional References===
 
===Additional References===
Anderson, D. 2010. ''Kanban''. Sequim, WA, USA: Blue Hole Press.
+
Chrissis, M., M. Konrad, and S. Shrum. 2003. ''CMMI: Guidelines for Process Integration and Product Improvement.'' New York, NY, USA: Addison Wesley.
 
 
Baldwin, C. and K. Clark. 2000. ''Design Rules: The Power of Modularity.'' Cambridge, MA, USA: MIT Press.
 
 
 
Beck, K. 1999. ''Extreme Programming Explained.'' New York, NY, USA: Addison Wesley.
 
 
 
Beedle, M., et al. 2009. "The Agile Manifesto: Principles behind the Agile Manifesto" in The Agile Manifesto [database online]. Accessed 2010. Available at: www.agilemanifesto.org/principles.html
 
 
 
Biffl, S.,  A. Aurum, B. Boehm, H. Erdogmus, and P. Gruenbacher (eds.). 2005. ''Value-Based Software Engineering''. New York, NY, USA: Springer.
 
 
 
Boehm, B. 1988. “A Spiral Model of Software Development.” IEEE ''Computer.'' 21(5): 61-72.
 
 
 
Boehm, B. 2006. “Some Future Trends and Implications for Systems and Software Engineering Processes.” ''Systems Engineering.'' 9(1): 1-19.
 
 
 
Boehm, B., A. Egyed, J. Kwan, D. Port, A. Shah, and R. Madachy. 1998. “Using the WinWin Spiral Model: A Case Study.” IEEE ''Computer.'' 31(7): 33-44.
 
 
 
Boehm, B., J. Lane, S. Koolmanojwong, and R. Turner. 2013 (in press). ''Embracing the Spiral Model: Creating Successful Systems with the Incremental Commitment Spiral Model.'' New York, NY, USA: Addison Wesley.
 
 
 
Castellano, D.R. 2004. “Top Five Quality Software Projects.” ''CrossTalk.'' 17(7) (July 2004): 4-19. Available at: http://www.crosstalkonline.org/storage/issue-archives/2004/200407/200407-0-Issue.pdf
 
 
 
Checkland, P. 1981. ''Systems Thinking, Systems Practice''.  New York, NY, USA: Wiley.
 
 
 
Crosson, S. and B. Boehm. 2009. “Adjusting Software Life Cycle Anchorpoints: Lessons Learned in a System of Systems Context.” Proceedings of the Systems and Software Technology Conference, 20-23 April 2009, Salt Lake City, UT, USA.
 
 
Dingsoyr, T., T. Dyba. and N. Moe (eds.). 2010. "Agile Software Development: Current Research and Future Directions.”  Chapter in B. Boehm, J. Lane, S. Koolmanjwong, and R. Turner, ''Architected Agile Solutions for Software-Reliant Systems.'' New York, NY, USA: Springer.
 
 
 
Dorner, D. 1996. ''The Logic of Failure''.  New York, NY, USA: Basic Books.
 
 
 
Faisandier, A. 2012. ''Systems Architecture and Design''. Belberaud, France: Sinergy'Com.
 
 
 
Forsberg, K. 1995. "'If I Could Do That, Then I Could…' System Engineering in a Research and Development Environment.” Proceedings of the Fifth Annual International Council on Systems Engineering (INCOSE) International Symposium. 22-26 July 1995. St. Louis, MO, USA.
 
 
 
Forsberg, K. 2010. “Projects Don’t Begin With Requirements.” Proceedings of the IEEE Systems Conference. 5-8 April 2010. San Diego, CA, USA.
 
 
 
Gilb, T. 2005.  ''Competitive Engineering''.  Maryland Heights, MO, USA: Elsevier Butterworth Heinemann.
 
 
 
Goldratt, E. 1984. ''The Goal''.  Great Barrington, MA, USA: North River Press.
 
 
 
Hitchins, D.  2007. ''Systems Engineering: A 21st Century Systems Methodology.''  New York, NY, USA: Wiley.
 
 
 
Holland, J. 1998. ''Emergence''. New York, NY, USA: Perseus Books.
 
  
ISO/IEC. 2010. ''Systems and Software Engineering, Part 1: Guide for Life Cycle Management.'' Geneva, Switzerland: International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC), ISO/IEC 24748-1:2010.  
+
Larman, C. and B. Vodde. 2009. ''Scaling Lean and Agile Development.'' New York, NY, USA: Addison Wesley.  
  
ISO/IEC/IEEE. 2015. ''Systems and Software Engineering -- System Life Cycle Processes.'' Geneva, Switzerland: International Organisation for Standardisation / International Electrotechnical Commissions. ISO/IEC/IEEE 15288:2015.
 
  
ISO/IEC. 2003. ''Systems Engineering — A Guide for The Application of ISO/IEC 15288 System Life Cycle Processes.'' Geneva, Switzerland: International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC), ISO/IEC 19760:2003 (E).
+
The following three books are not referenced in the SEBoK text, nor are they systems engineering "texts"; however, they contain important systems engineering lessons, and readers of this SEBOK are encouraged to read them.
  
Jarzombek, J. 2003. “Top Five Quality Software Projects.” ''CrossTalk.'' 16(7) (July 2003): 4-19. Available at: http://www.crosstalkonline.org/storage/issue-archives/2003/200307/200307-0-Issue.pdf.
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<blockquote>Kinder, G. 1998. ''Ship of Gold in the Deep Blue Sea.'' New York, NY, USA: Grove Press.</blockquote>
  
Kruchten, P. 1999. ''The Rational Unified Process.'' New York, NY, USA: Addison Wesley.
+
This is an excellent book that follows an idea from inception to its ultimately successful implementation. Although systems engineering is not discussed, it is clearly illustrated in the whole process from early project definition to alternate concept development to phased exploration and “thought experiments” to addressing challenges along the way. It also shows the problem of not anticipating critical problems outside the usual project and engineering scope. It took about five years to locate and recover the 24 tons of gold bars and coins from the sunken ship in the 2,500-meter-deep ocean, but it took ten years to win the legal battle with the lawyers representing insurance companies who claimed ownership based on 130-year-old policies they issued to the gold owners in 1857.  
  
Landis, T. R. 2010. ''Lockheed Blackbird Family (A-12, YF-12, D-21/M-21 & SR-71).'' North Branch, MN, USA: Specialty Press.
+
<blockquote>McCullough, D. 1977. ''The Path Between the Seas: The Creation of the Panama Canal (1870 – 1914).'' New York, NY, USA: Simon & Schuster.</blockquote>
  
Madachy, R. 2008. ''Software Process Dynamics''. New York, NY, USA: Wiley.
+
Although “systems engineering” is not mentioned, this book highlights many systems engineering issues and illustrates the need for SE as a discipline. The book also illustrates the danger of applying a previously successful concept (the sea level canal used in Suez a decade earlier) in a similar but different situation. Ferdinand de Lesseps led both the Suez and Panama projects. It illustrates the danger of lacking a fact-based project cycle and meaningful decision gates throughout the project cycle. It also highlights the danger of providing project status without visibility. After five years into the ten-year project investors were told the project was more than 50 percent complete when in fact only 10 percent of the work was complete. The second round of development under Stevens in 1904 focused on “moving dirt” rather than digging a canal, a systems engineering concept key to the completion of the canal. The Path Between the Seas won the National Book Award for history (1978), the Francis Parkman Prize (1978), the Samuel Eliot Morison Award (1978), and the Cornelius Ryan Award (1977).
  
Maranzano, J., et al. 2005. “Architecture Reviews: Practice and Experience.” IEEE ''Software.'' 22(2): 34-43.
+
<blockquote>Shackleton, Sir E.H. 2008. (Originally published in by William Heinemann, London, 1919). ''South: The Last Antarctic Expedition of Shackleton and the Endurance.'' Guilford, CT, USA: Lyons Press.</blockquote>
  
National Research Council of the National Academies (USA). 2008. ''Pre-Milestone A and Early-Phase Systems Engineering''. Washington, DC, USA: The National Academies Press.
+
This is the amazing story of the last Antarctic expedition of Shackleton and the ''Endurance'' in 1914 to 1917. The systems engineering lesson is the continuous, daily risk assessment by the captain, expedition leader, and crew as they lay trapped in the arctic ice for 18 months. All 28 crew members survived.
 
 
Osterweil, L. 1987. “Software Processes are Software Too.” Proceedings of the SEFM 2011: 9th International Conference on Software Engineering. Monterey, CA, USA.
 
 
 
Poppendeick, M. and T. Poppendeick. 2003. ''Lean Software Development: an Agile Toolkit.''  New York, NY, USA: Addison Wesley.
 
 
 
Rechtin, E. 1991. ''System Architecting: Creating and Building Complex Systems.'' Upper Saddle River, NY, USA: Prentice-Hall.
 
 
 
Rechtin, E., and M. Maier. 1997. ''The Art of System Architecting''. Boca Raton, FL, USA: CRC Press.
 
 
 
Schwaber, K. and M. Beedle. 2002. ''Agile Software Development with Scrum''. Upper Saddle River, NY, USA: Prentice Hall.
 
 
 
Spruill, N. 2002. “Top Five Quality Software Projects.” ''CrossTalk.'' 15(1) (January 2002): 4-19. Available at: http://www.crosstalkonline.org/storage/issue-archives/2002/200201/200201-0-Issue.pdf.
 
 
 
Stauder, T. 2005. “Top Five Department of Defense Program Awards.” ''CrossTalk.'' 18(9) (September 2005): 4-13. Available at http://www.crosstalkonline.org/storage/issue-archives/2005/200509/200509-0-Issue.pdf.
 
 
 
Warfield, J. 1976. ''Societal Systems: Planning, Policy, and Complexity''. New York, NY, USA: Wiley.
 
 
 
Womack, J. and D. Jones. 1996. ''Lean Thinking.'' New York, NY, USA: Simon and Schuster.
 
 
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<center>[[System Life Cycle Process Models: Vee|< Previous Article]] | [[Life Cycle Models|Parent Article]] | [[Integration of Process and Product Models|Next Article >]]</center>
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<center>[[Life Cycle Processes and Enterprise Need|< Previous Article]] | [[Systems Engineering and Management|Parent Article]] | [[System Life Cycle Process Drivers and Choices|Next Article >]]</center>
  
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[[Category: Part 3]][[Category:Knowledge Area]]
 
<center>'''SEBoK v. 2.0, released 1 June 2019'''</center>
 
<center>'''SEBoK v. 2.0, released 1 June 2019'''</center>
 
[[Category:Part 3]][[Category:Topic]]
 
[[Category:Life Cycle Models]]
 

Revision as of 03:08, 19 October 2019

The life cycle model is one of the key concepts of systems engineering (SE). A life cyclelife cycle for a systemsystem generally consists of a series of stagesstages regulated by a set of management decisions which confirm that the system is mature enough to leave one stage and enter another.

Topics

Each part of the SEBoK is divided into knowledge areas (KAs), which are groupings of information with a related theme. The KAs in turn are divided into topics. This KA contains the following topics:

See the article Matrix of Implementation Examples for a mapping of case studies and vignettes included in Part 7 to topics covered in Part 3.

Type of Value Added Products/Services

The Generic Life Cycle Model shows just the single-step approach for proceeding through the stages of a system’s life cycle. Adding value (as a product, a service, or both), is a shared purpose among all enterprises, whether public or private, for profit or non-profit. Value is produced by providing and integrating the elements of a system into a product or service according to the system description and transitioning it into productive use. These value considerations will lead to various forms of the generic life cycle management approach in Figure 1. Some examples are as follows (Lawson 2010):

  • A manufacturing enterprise produces nuts, bolts, and lock washer products and then sells their products as value added elements to be used by other enterprises; in turn, these enterprises integrate these products into their more encompassing value-added system, such as an aircraft or an automobile. Their requirements will generally be pre-specified by the customer or by industry standards.
  • A wholesaling or retailing enterprise offers products to their customers. Its customers (individuals or enterprises) acquire the products and use them as elements in their systems. The enterprise support system will likely evolve opportunistically, as new infrastructure capabilities or demand patterns emerge.
  • A commercial service enterprise such as a bank sells a variety of products as services to their customers. This includes current accounts, savings accounts, loans, and investment management. These services add value and are incorporated into customer systems of individuals or enterprises. The service enterprise’s support system will also likely evolve opportunistically, as new infrastructure capabilities or demand patterns emerge.
  • A governmental service enterprise provides citizens with services that vary widely, but may include services such as health care, highways and roads, pensions, law enforcement, or defense. Where appropriate, these services become infrastructure elements utilized in larger encompassing systems of interest to individuals and/or enterprises. Major initiatives, such as a next-generation air traffic control system or a metropolitan-area crisis management system (hurricane, typhoon, earthquake, tsunami, flood, fire), will be sufficiently complex enough to follow an evolutionary development and fielding approach. At the elemental level, there will likely be pre-specified single-pass life cycles.
  • For aircraft and automotive systems, there would likely be a pre-specified multiple-pass life cycle to capitalize on early capabilities in the first pass, but architected to add further value-adding capabilities in later passes.
  • A diversified software development enterprise provides software products that meet stakeholder requirements (needs), thus providing services to product users. It will need to be developed to have capabilities that can be tailored to be utilized in different customers’ life-cycle approaches and also with product-line capabilities that can be quickly and easily applied to similar customer system developments. Its business model may also include providing the customer with system life-cycle support and evolution capabilities.

Within these examples, there are systems that remain stable over reasonably long periods of time and those that change rapidly. The diversity represented by these examples and their processes illustrate why there is no one-size-fits-all process that can be used to define a specific systems life cycle. Management and leadership approaches must consider the type of systems involved, their longevity, and the need for rapid adaptation to unforeseen changes, whether in competition, technology, leadership, or mission priorities. In turn, the management and leadership approaches impact the type and number of life cycle models that are deployed as well as the processes that will be used within any particular life cycle.

There are several incremental and evolutionary approaches for sequencing the life cycle stages to deal with some of the issues raised above. The Life Cycle Models knowledge area summarizes a number of incrementalincremental and evolutionaryevolutionary life cycle models, including their main strengths and weaknesses and also discusses criteria for choosing the best-fit approach.

Categories of Life Cycle Model

The Generic System Life Cycle Model in Figure 1 does not explicitly fit all situations. A simple, precedential, follow-on system may need only one phase in the definition stage, while a complex system may need more than two. With build-upon systems (vs. throwaway) prototypesprototypes, a good deal of development may occur during the definition stage. System integrationintegration, verificationverification, and validationvalidation may follow implementation or acquisition of the system elements. With software, particularly test-first and daily builds, integration, verification, and validation are interwoven with element implementation. Additionally, with the upcoming Third Industrial Revolution of three-dimensional printing and digital manufacturing (Whadcock 2012), not only initial development but also initial production may be done during the concept stage.

Software is a flexible and malleable medium which facilitates iterative analysis, design, construction, verification, and validation to a greater degree than is usually possible for the purely physical components of a system. Each repetition of an iterative development model adds material (code) to the growing software base, in which the expanded code base is tested, reworked as necessary, and demonstrated to satisfy the requirements for the baseline.

Software can be electronically bought, sold, delivered, and upgraded anywhere in the world within reach of digital communication, making its logistics significantly different and more cost-effective than hardware. It does not wear out and its fixes change its content and behavior, making regression testing more complex than with hardware fixes. Its discrete nature dictates that its testing cannot count on analytic continuity as with hardware. Adding 1 to 32767 in a 15-bit register does not produce 32768, but 0 instead, as experienced in serious situations, such as with the use of the Patriot Missile.

There are a large number of potential life cycle processlife cycle process models. They fall into three major categories:

  1. primarily pre-specified and sequential processes (e.g. the single-step waterfall model)
  2. primarily evolutionary and concurrent processes (e.g. lean development, the rational unified process, and various forms of the vee and spiral models)
  3. primarily interpersonal and emergent processes (e.g. agile development, scrum, extreme programming (XP), the dynamic system development method, and innovation-based processes)

The emergence of integrated, interactive hardware-software systems made pre-specified processes potentially harmful, as the most effective human-system interfaces tended to emerge with its use, leading to further process variations, such as soft SE (Warfield 1976, Checkland 1981) and human-system integration processes (Booher 2003, Pew and Mavor 2007). Until recently, process standards and maturity models have tried to cover every eventuality. They have included extensive processes for acquisition management, source selection, reviews and audits, quality assurance, configuration management, and document management, which in many instances would become overly bureaucratic and inefficient. This led to the introduction of more lean (Ohno 1988; Womack et al. 1990; Oppenheim 2011) and agile (Beck 1999; Anderson 2010) approaches to concurrent hardware-software-human factors approaches such as the concurrent vee models (Forsberg 1991; Forsberg 2005) and Incremental Commitment Spiral Model (Pew and Mavor 2007; Boehm and Lane 2007).

In the next article on System Life Cycle Process Drivers and Choices, these variations on the theme of life cycle models will be identified and presented.

Systems Engineering Responsibility

Regardless of the life cycle models deployed, the role of the systems engineer encompasses the entire life cycle of the system-of-interest. Systems engineers orchestrate the development and evolution of a solution, from defining requirements through operation and ultimately until system retirement. They ensure that domain experts are properly involved, all advantageous opportunities are pursued, and all significant risks are identified and, when possible, mitigated. The systems engineer works closely with the project manager in tailoring the generic life cycle, including key decision gatesdecision gates, to meet the needs of their specific project.

Systems engineering tasks are usually concentrated at the beginning of the life cycle; however, both commercial and government organizations recognize the need for SE throughout the system’s life cycle. Often this ongoing effort is to modify or change a system, product or service after it enters production or is placed in operation. Consequently, SE is an important part of all life cycle stages. During the production, support, and utilization (PSU) stages, for example, SE executes performance analysis, interface monitoring, failure analysis, logistics analysis, tracking, and analysis of proposed changes. All these activities are essential to ongoing support of the system.

All project managers must ensure that the business aspect (cost, schedule, and value) and the technical aspect of the project cycle remain synchronized. Often, the technical aspect drives the project. It is the systems engineers’ responsibility to ensure that the technical solutions that are being considered are consistent with the cost and schedule objectives. This can require working with the users and customers to revise objectives to fit within the business bounds. These issues also drive the need for decision gates to be appropriately spaced throughout the project cycle. Although the nature of these decision gates will vary by the major categories above, each will involve in-process validationin-process validation between the developers and the end users. In-process validation asks the question: “Will what we are planning or creating satisfy the stakeholders’ needs?” In-process validation begins at the initialization of the project during user needs discovery and continues through daily activities, formal decision gate reviews, final product or solution delivery, operations, and ultimately to system closeout and disposal.

References

Works Cited

Anderson, D. 2010. Kanban. Sequim, WA: Blue Hole Press.

Beck, K. 1999. Extreme Programming Explained. Boston, MA: Addison Wesley.

Boehm, B. and J. Lane. 2007. “Using the Incremental Commitment Model to Integrate System Acquisition, Systems Engineering, and Software Engineering.” CrossTalk. October 2007: 4-9.

Booher, H. (ed.) 2003. Handbook of Human Systems Integration. Hoboken, NJ, USA: Wiley.

Checkland, P. 1999. Systems Thinking, Systems Practice, 2nd ed. Hoboken, NJ, USA: Wiley.

Cusumano, M., and D. Yoffie. 1998. Competing on Internet Time, New York, NY, USA: The Free Press.

Forsberg, K. and H. Mooz. 1991. "The Relationship of System Engineering to the Project Cycle," Proceedings of INCOSE, October 1991.

Forsberg, K., H. Mooz, and H. Cotterman. 2005. Visualizing Project Management, 3rd ed. Hoboken, NJ: J. Wiley & Sons.

ISO/IEC/IEEE. 2015.Systems and software engineering - system life cycle processes.Geneva, Switzerland: International Organization for Standardization (ISO)/International Electrotechnical Commission (IEC), Institute of Electrical and Electronics Engineers.ISO/IEC 15288:2015.

Lawson, H. 2010. A Journey Through the Systems Landscape. London, UK: College Publications.

Ohno, T. 1988. Toyota Production System. New York, NY: Productivity Press.

Oppenheim, B. 2011. Lean for Systems Engineering. Hoboken, NJ: Wiley.

Pew, R. and A. Mavor (eds.). 2007. Human-System Integration in The System Development Process: A New Look. Washington, DC, USA: The National Academies Press.

Warfield, J. 1976. Systems Engineering. Washington, DC, USA: US Department of Commerce (DoC).

Whadcock, I. 2012. “A third industrial revolution.” The Economist. April 21, 2012.

Womack, J.P., D.T. Jones, and D. Roos 1990. The Machine That Changed the World: The Story of Lean Production. New York, NY, USA: Rawson Associates.

Primary References

Blanchard, B.S., and W.J. Fabrycky. 2011. Systems Engineering and Analysis, 5th ed. Prentice-Hall International series in Industrial and Systems Engineering. Englewood Cliffs, NJ, USA: Prentice-Hall.

Forsberg, K., H. Mooz, H. Cotterman. 2005. Visualizing Project Management, 3rd Ed. Hoboken, NJ: J. Wiley & Sons.

INCOSE. 2012. Systems Engineering Handbook, version 3.2.2. San Diego, CA, USA: International Council on Systems Engineering (INCOSE). INCOSE-TP-2003-002-03.2.2.

Lawson, H. 2010. A Journey Through the Systems Landscape. London, UK: College Publications.

Pew, R. and A. Mavor (Eds.). 2007. Human-System Integration in The System Development Process: A New Look. Washington, DC, USA: The National Academies Press.

Additional References

Chrissis, M., M. Konrad, and S. Shrum. 2003. CMMI: Guidelines for Process Integration and Product Improvement. New York, NY, USA: Addison Wesley.

Larman, C. and B. Vodde. 2009. Scaling Lean and Agile Development. New York, NY, USA: Addison Wesley.


The following three books are not referenced in the SEBoK text, nor are they systems engineering "texts"; however, they contain important systems engineering lessons, and readers of this SEBOK are encouraged to read them.

Kinder, G. 1998. Ship of Gold in the Deep Blue Sea. New York, NY, USA: Grove Press.

This is an excellent book that follows an idea from inception to its ultimately successful implementation. Although systems engineering is not discussed, it is clearly illustrated in the whole process from early project definition to alternate concept development to phased exploration and “thought experiments” to addressing challenges along the way. It also shows the problem of not anticipating critical problems outside the usual project and engineering scope. It took about five years to locate and recover the 24 tons of gold bars and coins from the sunken ship in the 2,500-meter-deep ocean, but it took ten years to win the legal battle with the lawyers representing insurance companies who claimed ownership based on 130-year-old policies they issued to the gold owners in 1857.

McCullough, D. 1977. The Path Between the Seas: The Creation of the Panama Canal (1870 – 1914). New York, NY, USA: Simon & Schuster.

Although “systems engineering” is not mentioned, this book highlights many systems engineering issues and illustrates the need for SE as a discipline. The book also illustrates the danger of applying a previously successful concept (the sea level canal used in Suez a decade earlier) in a similar but different situation. Ferdinand de Lesseps led both the Suez and Panama projects. It illustrates the danger of lacking a fact-based project cycle and meaningful decision gates throughout the project cycle. It also highlights the danger of providing project status without visibility. After five years into the ten-year project investors were told the project was more than 50 percent complete when in fact only 10 percent of the work was complete. The second round of development under Stevens in 1904 focused on “moving dirt” rather than digging a canal, a systems engineering concept key to the completion of the canal. The Path Between the Seas won the National Book Award for history (1978), the Francis Parkman Prize (1978), the Samuel Eliot Morison Award (1978), and the Cornelius Ryan Award (1977).

Shackleton, Sir E.H. 2008. (Originally published in by William Heinemann, London, 1919). South: The Last Antarctic Expedition of Shackleton and the Endurance. Guilford, CT, USA: Lyons Press.

This is the amazing story of the last Antarctic expedition of Shackleton and the Endurance in 1914 to 1917. The systems engineering lesson is the continuous, daily risk assessment by the captain, expedition leader, and crew as they lay trapped in the arctic ice for 18 months. All 28 crew members survived.


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SEBoK v. 2.0, released 1 June 2019