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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.11 No.1 pp.70-81

Design Requirements in Software and Engineering Systems

A. M. Eleiche*, 1I. Ahmad, 2M. O. Elish
*Dept. of Mechanical Engineering, King Fahd University of Petroleum and Minerals
1Dept. of Information and Computer Sciences, King Fahd University of Petroleum and Minerals,

2Dept. of Information and Computer Sciences, King Fahd University of Petroleum and Minerals
Received: November 13, 2011 / Revised: January 10, 2012 / Accepted: January 13, 2012


The subject of “Design Requirements” (DR) is central to the design of software and engineering systems. The main reason for this is that quality aspects are usually closely tied to requirements, among other things. In this review paper, we consider how the subject of requirements is being managed in these two seemingly different design disciplines. Two important aspects are covered, namely: (a) requirements development, describing various activities leading to requirements documentation, and (b) requirements change management, describing various activities needed for the proper treatment of the inevitable changes in requirements. Similarities and differences on how these two aspects are handled in software and engineering systems are highlighted. It is concluded from this literature survey that the man-agement of software requirements is quite coherent and well established as a science. On the other hand, management of engineering systems requirements suffer from being unstructured, in particular when requirements changes are involved. Important gaps and future important research areas are identified.



In a previous paper (Eleiche, 2010), it was con­cluded that in order to support innovative energy re­search projects funded by the CCWCE (2008), innova­tors should be provided with a software program that can help manage the effects of possible changes in de­sign requirements (DR) and hence facilitate the design of successful quality systems on schedule and within planned budgets. It was also stated that guidance would be sought from similar research being carried out in the software engineering arena.

In the present paper, we address in detail the sub­ject of DR, which is central to the design of software and engineering systems. The main reason for this is that quality aspects are usually closely tied to requirements, among other things. In this review paper, we consider how the subject of requirements is being managed in these two seemingly different disciplines. Two impor­tant aspects are covered, namely: (a) requirements deve­lopment, describing various activities leading to re-qui­rements documentation, and (b) requirements change ma­nagement, describing various activities needed for the proper treatment of the inevitable changes in requi-re­ments. Similarities and differences on how these two aspects are handled in software and engineering systems are highlighted. Important gaps and future important re­search areas are also identified.

The next section introduces the topics related to DR. in a generic way. This is followed in Section 3 by an overview of how DR development is treated in soft­ware and engineering systems, while Section 4 presents how DR management is being applied in these same two disciplines. Important conclusions are given finally in Section 5. 


IEEE (1990) defines “Requirement” as a condition or capability that: (a) is needed by a user to solve a problem or achieve an objective, (b) must be met or pos­sessed by a system or system component to satisfy a contract, standard, specification, or other formally im­posed document. The set of all requirements forms the basis for subsequent development of the system or sys­tem component.

Requirements Engineering (RE) is a crucial aspect for a successful development of software and engineer­ing systems. The RE process is the primary work of the “Requirements” phase of the project. Figure 1 shows the sub disciplines of RE (Wiegers, 2000) consisting of two major types of activities. In RE development, “User Needs” are translated into “Requirements Specification” through five activities that form a sub-process, while the activities in RE management, namely traceability and change, do not flow into each other but are separate. 

Figure 1.Sub Disciplines of RE, Adapted from Wiegers (2000).


Requirements can be classified into: (a) Functional requirements that capture the intended behavior in terms of services, tasks or functions the system is required to perform; (b) Non-functional requirements (or system qualities) that capture required properties or qualities of the system; (c) Constraints (organizational, operational, economical, legislative, and ethical). All requirements must be carefully derived through analysis of user needs and documented. They should specify what is to be done, not how it is to be done.

A good requirement should be (Tavassoli, 2009): clear; complete; correct; consistent; verifiable; traceable; feasible; modular; adaptable; and design-independent.

Nowhere more than in the requirements process do the interests of all the stakeholders in a software or en­gineering system project intersect. These include: (a) external stakeholders (end users, customers acquiring the product, suppliers, distributors, subcontractors, legis­lators, policy makers); and (b) internal stakeholders (re­quirements analysts, project managers, developers, de­signers, manufacturing staff, testers, regulators and audi­tors, sales and marketing, purchasing and finance, and field support or help desk staff). Handled well, this in­tersection can lead to exciting products, delighted cus­tomers, and fulfilled developers. Handled poorly, it is the source of misunderstanding, frustration, and friction that undermine the product’s quality and business value. 

3.1 RD in Software

Many software problems arise from shortcomings in the ways that people acquire, document, agree on, and modify the product’s requirements. Typical problem areas include informal information gathering, implied functionality, inadequately defined requirements, and a casual change process (SERENA, 2011). The widely quoted CHAOS report (Standish Group, 1995) relates the consequences of casual approaches to requirements engineering. Year after year, lack of user input, incom­plete requirements, and changing requirements are the major reasons why so many software and information technology projects fail to deliver all of their planned functionality on schedule and within budget.

In software engineering, RE has already been ac­cepted as an independent discipline and is done system­atically. As will be seen in the following, many concepts and methods for handling of requirements have already been elaborated. Hence, a common terminology of proc­ess phases in RD has emerged, involving elicitation, negotiation, analysis, specification and validation. This is depicted in Fig. 2, as proposed by Kotonya and Som­merville (1998). 

Figure 2.Software RD Phases (Kotonya and Sommerville, 1998).

During the requirements elicitation phase, differ­ent complementary techniques are applied to understand the application domain, and the problems and needs of all stakeholders. The most common software requirements elicitation techniques are interviewing, brainstorming, storyboarding, workshops, surveys/questionnaire, and ethnography (Braude, 2010; Lamsweerde, 2009; Press­man, 2005; Sommerville, 2007; Wiegers, 2003). The full integration of users is a decisive factor for the suc­cess of this RD phase (Kujala et al., 2005).

 During requirements negotiation, the elicited re­quirements are discussed with the stakeholders. Re­quirements are then prioritized, unnecessary ones are removed, and conflicting and incomplete ones are re­solved. Requirements scope/baseline is also defined and agreed upon (Kotonya and Sommerville, 1998). Priori­tizing requirements “assists project managers with re­solving conflicts, plan for staged deliveries, and make necessary trade-off decision” (Aurum and Wohlin, 2005).

 During analysis, models are created from differ­ent perspectives to develop an understanding of the sys­tem, as well as checking for necessity, completeness, consistency and feasibility. A system model abstracts the system leaving out the unnecessary details. Models enable to filter out the complexities of the real world not relevant for the time being, so that directed effort can be put towards the most important parts of the system un­der development (Giaglis, 2001; Kotonya and Sommer­ville, 1998; Sommerville, 2007). Moreover, visualizing requirements as models helps the customer better under­stand the requirements (Tavassoli, 2009).

Requirements specification refers to the production of a requirement document which can be systematically reviewed, evaluated, and approved (Bourque and Du­puis, 2004). Once the requirements are agreed upon be­tween the stakeholders and the development team, they are specified in a document, popularly known as Soft­ware Requirements Specification (SRS) document. This is an official statement of what is required of the system developers. Its purpose is to be an authoritative state­ment of ‘what' the software is to do. As far as possible, the document shall not address the design and imple­mentations issues, and should be detailed enough to allow the design of the software without user involve­ment. In general, the size and content of the SRS docu­ment should reflect the size and complexity of the soft­ware product.

The many sections in the SRS document should de­tail various aspects of the software system to be devel­oped, mainly: functional requirements, non-functional requirements, design constraints and interface specifica­tions (Kotonya and Sommerville, 1998; Sommerville, 2007). IEEE (1998) has defined a standard known as “IEEE Std 830-1998” which provides guidelines for documenting software requirements specification.

The requirements document along with the models can be and should be managed using requirements man­agement tools such as Telelogic DOORS or IBM Ra­tional RequisitePro.

The requirements validation process ensures that the software engineer has understood the requirements. It is also important to verify that a requirements docu­ment conforms to company standards, and that it is un­derstandable, consistent, and complete (Bourque and Dupuis, 2004). The process attempts to identify the er­rors in the SRS document before it is used as a basis for further system development. In other words, require­ment validation is concerned with demonstrating that the requirements define the system that the customer really wants. Prototyping, reviews, inspections, and test case generation are the most commonly used requirements validation techniques.

3.2 RD in Engineering Systems

By engineering systems, we mean consumer or ca­pital products and systems ranging from simple to quite complex ones. Especially in modern energy applications, these may also incorporate many kinds of software, thus forming “hybrid systems” that contain material and im­material parts. The following discussion will be limited to systems consisting of hardware only.

In engineering systems design, RD is usually taken into account, as stated in most engineering design textbooks. For instance, Cross (1989) suggests the use of a goal tree to vaguely collect the initial requirements. The requirements are further refined as the problem un­derstanding of the customer and engineers increases. Pahl and Bietz (1996) suggest a sequential process model in which the engineer has to extract the requirements from the customer’s wishes. They also recognize that cu­stomers are often not able to express their requirements appropriately; however, methods for eliciting these re­quirements are not suggested. Ulrich and Eppinger (2008) collect the requirements in hierarchical weighted lists. They also state that it is important to reveal im­plicit customer needs, and that a common product un­derstanding between customer and engineer is necessary. 

In their comprehensive review, Jiao and Chen (2006) state that RD usually encompasses only the three activi­ties of elicitation, analysis and specification. During Eli­citation, approaches used can be classified into:  

· Psychology-based approaches: where techniques such as Kansei engineering; Kawakita Jiro method, affinity diagrams, and laddering can be employed.

· Methods and tools from the field of knowledge acqui­sition: where techniques employed can be: 
     (a) “Contrived” (not-heavily dependent on natural language dialogue, but good at reducing system­atic bias, eliciting implicit knowledge, represent­ing declarative and procedural knowledge): e.g. sorting, laddering, repertory grids.
     (b) “Non-contrived” (traditional) techniques: e.g. sur­veys, observations, ethnography, self-reports, in­terviews.

· AI-based approaches: where fuzzy systems, regres­sion analysis, and expert systems have been devel­oped for eliciting customer requirements more accu­rately and objectively. Also, integrated approaches by combining picture sorts and laddering, fuzzy evalua­tion and neural network techniques.

·  Knowledge recovery: from historical data.

Case studies of elicitation in practice are available in the literature. This is described by Mathelin et al. (2005) for the automotive domain, and by Ward et al. (2003) and Agouridas et al. (2006) for medical devices.

Activities in the Analysis phase consist of:

·  Understanding market and customer needs.

·  Customer preference.

·  Prioritization: By assigning different importance wei­ghts for customer requirements. This affects the target values to be set for the engineering characteristics. Existing techniques are:
    (a) AHP (Analytic hierarchy process)
    (b) Fuzzy AHP
    (c) Using supervised learning with a radial basis func­tion (RBF) neural network
    (d) Applying conjoint analysis to prioritize customer requirements through pairwise comparisons

·   Classification: This helps guiding the designer in com­piling, organizing, and analyzing product design is­sues. Existing techniques are:
    (a) Affinity diagrams
    (b) Ontology for representing requirements that sup­ports a generic requirement process. Ontology de­fines parts, features, requirements and constraints
    (c) Taxonomic approach (developing a set of taxono­mies to assist in gathering, storing, using and re­using requirements)

Specification is concerned with the creation of a structurally concrete and precise specification of product requirements based on functional knowledge that has been elicited from key stakeholders. Common techni­ques are:
· Requirement transformation: e.g. Customer optimization route and evaluation (CORE) model; methodology of organizing specifications in engineering (MOOSE)
· QFD. To translate customer requirements to technical design requirements
· Fuzzy QFD: To enhance handling of ambiguous requirement information and evaluating inputs. Subjective crisp variables are expressed as fuzzy numbers
· Prioritization of design requirements. Importance rating among engineering characteristics in the QFD; a linear programming model for the prioritization of design requirements in the QFD planning process; employing a fuzzy outranking approach to prioritize the design requirements in the QFD
· Targets of design requirements: (usually defined by design teams subjectively and empirically) Using a fuzzy set theoretic approach to determine optimum
target values for the engineering characteristics in QFD with consideration of the relevant constraints; using fuzzy regression and fuzzy optimization.

Therefore, as the RD phases proceed, the informally expressed needs of stakeholders are explored, developed and expanded into a more complete and formal docu­ment, variously known as the product description, tech­nical specification, or Product Design Specification (PDS), that is understood and agreed upon by all stakeholders, and from which a design solution can be proposed. 

3.3 Discussion on RD

RD in software engineering is highly elaborated and many methods and process models are known. Soft­ware engineering sees RD as a continuous activity that is performed throughout the entire development process, while product/systems engineering considers RD as a phase at the beginning of the project.

The specification of requirements in software engi­neering results from not only the transformation of cus­tomer requirements from those end-users, but also con­siderations of many engineering concerns. This is con­sistent with the principle of viewpoint-oriented software requirement engineering, where multiple viewpoints encapsulate different types of requirement models natu­ral to different stakeholders. 


RM involves two main tasks, namely: (a) require­ments traceability, performed once the specifications have been documented, in order to determine the links between various requirements; and (b) change impact analysis, conducted at any stage of the design process, once a change of any kind has been proposed, in order to determine the feasibility, implications, cost, etc, of such a change, and finally deciding on its approval, as illustrated in Figure 3. 

Figure 3.Generic Engineering Change Process (Jarratt et al., 2004).

Changes in requirements are always expected. In­deed, they are the norm and not the exception, since most complex projects involve interdisciplinary system scenarios. In these cases, the stakeholders needs are usually not fully identified, and hence the requirements and the specifications are loosely-defined. Therefore, those initial requirements can be expected to change for a variety of reasons, e.g. altered market needs, safety concerns, problem corrections, new constraints, intro­duction of new technologies, uncertainty of resources, cost considerations, legislation changes, etc. On the other hand, in such systems, components are usually highly interconnected; a change to one requirement in one component can propagate through the system and cause other changes in other components and parts. The change can also spread to other products (e.g. other family mem­bers) due to common platforms, other processes (e.g. manufacturing), and other businesses (e.g. suppliers, part­ners, etc.) (Jarratt et al., 2011). Hence, the need of full-scale traceability between all system players. 

In complex systems, it is important to identify and stabilize the requirements as early as possible in the process. Otherwise, inevitable changes will cause dis­ruption of the product development schedule, increase of costs, and failure to meet the expected system quality. Table 1 shows the relative costs of fixing requirements defects in different phases of a project. Whatever it may cost to do things right in the requirements phase, it may be 3 to 1000 times more costly to fix later. 

Table 1.Relative Costs of Fixing Requirement errors (Gause and Weinberg, 1989).

Similarly, Table 2 shows that return on investment (ROI) from practicing good requirements management is substantial, in terms of its results and benefits. 

Table 2.ROI from practicing good RM (SERENA, 2011).

Finally, a European study by Blackburn et al. (1996) showed that teams that developed products more quickly were found to have devoted more of their schedule and effort to requirements than did slower teams (Table 3). 

Table 3.Investing in Requirements Accelerate Development (Blackburn et al., 1996).

4.1 RM in Software

With respect to managing requirements change in software development, the requirements can be broadly categorized into volatile (requirements that are likely to change), and non-volatile requirements (stable ones) (Sommerville, 2007; De Lucia et al., 2008). As a proac­tive way to manage changing requirements, the volatile requirements are sometime further categorized. Catego­rizing requirements helps in change management as the reason and justification for change is better understood and proper attention can be given to different categories of non-volatile requirements (Sommerville, 2007; Harker et al., 1993). Additionally, if a change can be catego­rized, we can understand its impact and how much con­trol we have on this change (McGee and Greer, 2009). One of the popular categories of changing requirements is that proposed by Harker et al. (1993). Sometimes the changes are categorized from the developer’s perspec­tive too (Nurmuliani et al., 2004). During categorization of requirements, it is also helpful to assess the probabil­ity of the change to that requirement (De Lucia et al., 2008). A simplified view of the change management process is shown in Figure 4. 

Figure 4.Requirements Change Management Process.

 A requirements change normally begins as a request, either formal or informal. Informal change requests need to be checked and controlled as far as possible as it leads to many problems due to inadequate allocation of sche­dule and manpower to manage those changes. A formal change request needs to be documented from the begin­ning. A change request has many attributes apart from the requested change itself. Among the important attrib­utes for a change request are type of change <add, de­lete and modify> (Strens and Sugden, 1996; McGee and Greer, 2009), the importance of change (O’Neal and Carver, 2001), the reasons and justification and the source of change (Nurmuliani et al., 2004; McGee and Greer, 2009). It may not be possible to collect and document all the attributes for a given change request but the more the information available on these attributes, the easier it is to handle them.

Once the change request is received, the next im­portant activity is to assess the impact of implementing this change. This is popularly known as impact analysis. Conducting impact analysis helps answer many ques­tions related to the impact of implementing this change. Among the important aspects are, when in development cycle the change needs to be implemented (Ramzan and Ikram, 2006; Imtiaz et al., 2008; Strens and Sugden, 1996), what artifacts are impacted by this change (Ramzan and Ikram, 2006; De Lucia et al., 2008; O’Neal and Carver, 2001; Imtiaz et al., 2008), the degree of change (De Lu­cia et al., 2008; O’Neal and Carver, 2001; Strens and Sugden, 1996) and who among the stakeholders are im­pacted by the change (Ramzan and Ikram, 2005; O’Neal and Carver, 2001). Figure 5 shows the impact of change affecting different phases and artifacts. 

Figure 5.Ripple Effect on Artifacts and Phases Due to Change (Leffingwell and Widrig 2003).

One of the main techniques to do the impact analy­sis is the use of traceability matrix. A traceability ma­trix represents the dependency relationships between different requirements and also across different artifacts. This dependency relationship can be of different types like ‘dependent,’ ‘related.’ There are different types of traceability matrix depending on the level of details it works on, the type of information it stores, etc. (Ibrahim et al., 2005; O’Neal and Carver, 2001). An example of a simple traceability matrix is shown in Figure 6. A com­mon categorization of traceability matrix is vertical ver­sus horizontal traceability matrix. A vertical traceability matrix includes dependency relationship between arti­facts and entities from different phase of development whereas a horizontal traceability matrix includes rela­tionship between artifacts and entities within a devel­opment phase.

Figure 6.A Sample Traceability Matrix (Leffingwell and Widrig, 2003).

To come up with the traceability matrix for a pro­ject is a major task. The core of this issue is to build the dependency relationship between different entities and artifacts. For relatively small projects it may be feasible to build these relationships manually, but for large com­plex systems, we need some level of automation (Ibra­him et al., 2005). There are various techniques employed for automation ranging from heuristics, information retrieval, data mining, domain knowledge and this is a hot area in research (Imtiaz et al., 2008). Moreover, the relationship between artifacts and entities can be direct, where an artifact or an entity is directly affected by the change, or indirect, where an artifact or an entity may be affected indirectly due to its relationship to other arti­facts and entities that are affected directly by the pro­posed change (Strens and Sugden, 1996). This phenome­non is sometimes termed as “ripple effect”, and the chain of this ripple effect may not be limited to only one level but to a number of levels with different degree of effect (Bohner, 2002, De Lucia et al., 2008, Ramzan and Ikram, 2005). 

Once the impact analysis is conducted using the traceability matrix, a candidate impact set is obtained which includes all the artifacts and entities affected di­rectly or indirectly by the proposed change. It shall be kept in mind that this impact set is not always accurate in the sense that it may not be able to include all the possible artifacts and entities, and accordingly some of them might be left out (termed as false negatives). Addi­tionally, the impact set may include some artifacts and entities which may in reality not be affected by this change (termed as false positives) (Bohner, 2002). The effectiveness of a given technique for impact analysis and traceability matrix is mostly judged considering these false positives and false negatives. Figure 7 shows the process of impact analysis. The impact itself may be measured in terms of degree and probability of impact.

Figure 7.Impact analysis process (De Lucia et al. 2008).

It is also recommended that there be a clear process and change control body who takes care of the entire change management process instead of change creeping in from anywhere with no proper control on them. This may adversely affect the schedule, cost, and the final quality of the software product. The concept of having an independent change control board is very effective and popular in this respect and is practiced widespread (Leffingwell and Widrig, 2003). There are many re­quirements change management process proposed in literature and a good comparison on many of them is available in (Ramzan and Ikram, 2005). The process of change management involving change control board is shown in Figure 8. The change control board acts like a firewall by controlling the incoming change and pre­venting the change creeping in through informal change requests.

Figure 8.Change management through change control board (Leffingwell and Widrig, 2003).

4.2 RM in Engineering Systems

General engineering changes during a system’s life-cycle have been studied intensively in the last decade. A comprehensive review has been reported recently by

Jarratt et al. (2011). The subject is still under continuous development, hence no complete books have been de­voted to the topic. Results have been published mainly in journal or conference papers and a few book chapters. The change process follows the plan given previously in Figure 3, with many iterations and break/stage-gate points.

As seen in Figure 9, the sources of changes throu­ghout the design process are numerous, and can be emergent (i.e. arising from the properties of the system itself), or initiated (for improvements, enhancements, or adaptations of the system). The initiation source can be internal (operational experience, manufacture/assembly, production, build), or external (customer, supplier, con­tractual), with changes in customer requirements playing a substantial role (Table 4).

Figure 9.Sources of Change Throughout the Design Process (Eckert et al., 2004).

Table 4.Initiation of changes. From Ahmed and Kanike (2007).

Eckert et al. (2004) have identified two types of change propagation: (a) Ending ones, consisting of small ripples of change, which are brought to a conclu­sion within an expected time frame, and (b) Unending ones, consisting of avalanches of change, typical of “a snowball effect,” which occur when a major change initiates several other major changes, and all of these cannot be brought to a satisfactory conclusion. With innovative systems, changes are much more likely to occur since everything is fuzzy, particularly requirements, at the front end. This is particularly so in hybrid systems governed by both technology push and market pull, as in many emergent energy systems. In theses cases, the best strategy is to isolate the innovation process within R&D laboratories, where “organized chaos” could be controlled and maintained, until new systems (ideas, materials, processes, etc.) are fully developed and successfully tested. 

As noted by Jarratt et al. (2011), changes during the design process result in "information deficiencies" for other development teams, whose decisions are then made about the system without up-to-date data (Fricke et al., 2000; Rouibah and Caskey, 2003). In order to re­medy this situation, and provide help in decision-mak­ing, and the overall engineering change process, engi­neers need well-designed tools for their support. Such tools should help perform many important tasks, namely: track requirements status; communicate with stakehol­ders; store requirements attributes; manage versions and changes; facilitate impact analysis; control access; reuse requirements. Some of the academic support tools re­ported in the literature have been discussed in detail by Jarratt et al. (2011). A few of these will be highlighted here.

Keller et al. (2005, 2007, 2008) developed the Change Prediction Method (CPM) tool, which is a software pro­gram for predicting change propagation, by analyzing indirect changes and calculating the combined risk that a change to one component will affect others. The CPM tool makes use of Design Structure Matrices (DSMs) to provide a simple, compact, and visual representation of the probability that a change will propagate from one component to others. The tool can be used in all life-sta­ges of a system, such as in the conceptual design, detail design, and operational life-stages.

In parallel, Koh and Clarkson (2009) presented a modeling method that aims to manage the effects of change propagation, and applied the method to the de­sign of a jet engine fan. The method uses a matrix-based approach to model the dependencies between the solu­tion alternatives, the potential change propagation brou­ght about by the solutions, the affected product attrib­utes, and the resources needed to carry out the change work. The method allows engineers to trace critical change propagation paths and manage them, and hence appears to be suitable for assessing solution alternatives during preliminary design and exploring the design space in the right direction.

Lemmens et al. (2007) analyzed the impact of change from different points of view e.g. requirements, physical or functional product architecture, design processes or activities, organization, with the aim of facilitating deci­sion-making by improving the visibility and shared un­derstanding of the interdependencies that exist within and between such viewpoints. Change Propagation Analysis (CPA) algorithms were proposed and implemented in a prototype software environment to allow the modeling and visualization of multiple dependencies across multiple information domains, including lifecycle considerations.

Tracking changes can always give an engineer valuable experience in designing future products. How­ever, this approach is “reactive” and only addresses the problem of changing requirements after they have oc­curred and it is too late to adjust the current design. De­signing systems should be “proactive.” Designing with “changing requirements in mind” can be especially ef­fective when a customer has only loosely identified re­quirements or when requirements are not fully known. A few approaches have been proposed in that direction.

Qureshi et al. (2006) defined “product flexibility” as the adaptability of a system in response to changing factors. Since flexible products were realized with ad hoc methods that rely on the experience and intuition of the designer, they presented a set of formal principles for guiding the design of flexible products. These prin­ciples were derived from the results of an empirical study of the United States patent repository. They also validated the effectiveness of these principles using a Change Modes and Effects Analysis (CMEA) tool.

The Design For Variety (DFV) method uses prod­uct platform architecture to provide a structured ap­proach to reduce the amount of redesign effort for future generations of a product. For large projects, system ar­chitecture can be used to break down the design into smaller subsystems at each level of the design hierarchy (Hintersteiner, 2000). The DFV has the advantage of being a simple and inexpensive technique to determine potential design changes. The methodology makes use of standardization and modularization techniques to reduce future design costs and efforts (Martin and Ishii, 2002). The design for variety method develops two indi­ces to measure a product’s architecture. The first, called the Generational Variety Index (GVI), is an indicator of the amount of redesign effort required for future itera­tions of a product. The other is called the Coupling In­dex (CI), and it is used to gauge the extent of coupling among the different components in a product. DFV can be used to help reduce the impact of variety on the life-cycle costs (Martin and Ishii, 2002).

Peterson et al. (2007) identified six product devel­opment strategies to cope with changing requirements and specifications. These strategies were tested while developing working product prototypes for their project. These six recommendations are: 

· Establish and foster open communication between designers and customers.
· Develop and explicitly write down a complete list of design requirements..
· Analyze the list of requirements to identify which requirements are likely to change and which are stable.
· Predict future market/customer needs and requirement changes.
· Use an iterative approach. Quick turnover of designs and prototypes provides a method for testing requirements and discovering unanticipated ones.
· Build flexibility into the design by selecting product architectures that tolerate changing requirements. This can be achieved by over-designing components that are likely to change to meet future needs. 

Freezing requirements is one way designers try to deal with changing requirements. One goal of a freeze is to reduce the likelihood of design changes. The major benefits from using design freezes are the ability to struc­ture the design process and to control design changes (Eger et al., 2005). A design freeze marks the end of a development stage where requirements become fixed before the design can continue (Eger et al., 2005). Early design freezes have the benefit of pushing any design changes to future product generations. This can be con­structive in an iterative design process. Early design freezes can also force a design before it is beneficial to do so. When the exact requirements are uncertain, it may be advantageous to postpone a design freeze. Some changes due to safety concerns, problem corrections, or altered customer requests will still have to be carried out regardless of whether a component is frozen. Changes after a freeze are likely to be more costly, and the cost will continue to increase the later the change is imple­mented (Eger et al., 2005). Many designers feel it is best to keep parts flexible where changes are anticipated.

Information about design freezes is especially im­portant when working in a team. Recognizing the de­pendencies between parts and acknowledging which parts may be frozen can avoid inadvertent changes to the overall design. 

4.3 Discussion on RM

Some of the methods developed for software engi­neering to assess the impact of a design change can be applied to engineering systems with some adaptation. As noted by Peterson et al. (2007), the difficulty lies in that software design is only concerned with the trans­mission of information, while engineering systems de­sign must also deal with material and energy transfer.

A couple of models used in software engineering consider changes in evolutionary software development (Schach and Tomer, 2000; Rajlich, 2000). However these models are not appropriate for engineering systems de­sign where component interfaces are not as explicit and involve more than just information transmission. Gener­ally, these programs only identify the immediate impli­cations of change within the immediate sub system and are not capable of exploring the consequences of change propagation through complex systems with different mechanical interactions (Keller et al., 2005).

An important concept that should be carried over from software to engineering systems is the adoption of a socio-technical approach which contends that commu­nication problems can be reduced if all stakeholders are involved in all phases of the design process.

The idea of guessing future changes in software (Future Analysis) can also be applied to engineering sys­tems design. A robust design is one that can cope with alternative futures (Land, 1982). In order to build robust systems the designer must attempt to consider all possi­ble alternative futures. The outcome of the analysis of the system for future changes is a list of system features which are likely to be affected. Building flexibility into a system can be beneficial but is often expensive so it is important to determine where best to build flexibility into the system (Land, 1982). The target lifespan will determine how much flexibility the system should have to meet that target.

For both software and engineering systems, com­mercial software tools are available to handle RM. Some of these tools are compared in Table 5 and Table 6. 

Table 5.RM Commercial Tools (Uspenskiy 2004)*.

Table 6.RM Commercial Tools (McLellan et al. 2010)*.


Since requirements development and management are among the most important activities in any software or engineering system project, efforts towards improv­ing these two tasks can always increase and accelerate the ROI. According to the “garbage in, garbage out” rule: If the requirements are not “good” and “properly man­aged,” all subsequent efforts will only help design, make, and market the wrong unneeded product faster.

The analysis of the mentioned literature revealed that RE in product engineering is mostly restricted to the early phases of the development process. During the late phase, RE does not seem to play a substantial role. Most of these approaches state that the customer plays a cen­tral role during the entire development process. The type and degree of customer integration into the development process varies. The integration of the customer into the process of requirements elicitation is emphasized, but not in later phases.

RE is a well-established discipline in software de­velopment. This is clear from the many textbooks that have appeared on the subject and the many courses in curricula of various software engineering programs. In contrast, there are no books dedicated to this subject for designing engineering systems. A special journal issue of Research in Engineering Design on “Engineering Change” is forthcoming in 2011 (Eckert et al., 2010). 

Following is Table 7 compares the degree of achi­evement of various RD and RM tasks in software and in engineering systems.

Table 7.Comparing the Degree of Achievement of Various RD and RM Tasks in Software and Engineering Systems.

Both software and engineering systems lack the coverage of RD and RN in complex innovative and/or hybrid applications.

As seen also in the Table, RD and RM are applied in a structured way in software systems, whereas a few areas are still under-developed for engineering systems; further research in that direction is needed. 


Thanks are extended to the King Fahd University of Petroleum and Minerals for funding the research re­ported in this paper through the KFUPM Center of Ex­cellence for Scientific Research Collaboration with Massachusetts Institute of Technology (MIT) (Project # MIT 09023). 


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