A Study on Techniques for Measuring Requirement ... - Springer Link

A Study on Techniques for Measuring Requirement Suitability Considering Project Objectives and Constraints JungWon Byun1, SungYul Rhew1, and ManSoo Hwang2 1

Soongsil University, Korea ShinHeung College, Korea {jimi01,syrhew}@ssu.ac.kr, [email protected] 2

Abstract. The suitability of requirements that are developed and changed is a key factor to make a success of project. The key elements of requirement suitability are the objectives and constraints which are decided by scope. To ensure that requirements have suitability, our study proposes the techniques for measuring requirement suitability considering objectives, constraints and requirements. To calculate requirement suitability points, which are quantities calculated by these techniques, we develop indicators and metrics based on relationship among objectives, constraints and requirements, and propose expressions to quantify our indicators using MCDM (Multi Criteria Decision Making) techniques. An interpretation and usage of our techniques are described by statistical analysis. Keywords: Requirement Suitability, Objective and Constraints, Requirement Suitability Points.

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Introduction

The importance of requirement engineering to make a success of project is already shown by various studies [1, 2, 3]. That is, a many cause of failed project are result of performing requirement engineering (RE) improperly. For this reason, the importance of performing RE properly is focused to improve the quality of project result [4]. In many studies, some criteria of successful project are “Within Budget”, “In Time” and “Something and Quality to Satisfy Customer” on which “Objectives” and “Constraints” have effects. The objectives and constraints are identified at planning stage of project, and have effects through project life-cycle. To ensure that requirements are to achieve objectives and to conform to constraints is to ensure the results of project are to achieve and conform to them. As some study about failed project[5], in objective view, the rates of failed projects caused by some improper requirements to objectives are 72.9% and the rate of them cause by unrealistic requirements are 68.6%. In constraints view, the rates of failed caused by requirements to estimate schedule inappropriately are 71.4% and the rates of considering risks insufficiently are 75.7%. At result, the major causes of failed G. Lee et al. (Eds.): ICHIT 2012, CCIS 310, pp. 449–457, 2012. © Springer-Verlag Berlin Heidelberg 2012

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projects are requirements not considering objective and constraints. So, the validation of requirements suitability could decrease these rates of failed projects. In other views, one of important issues of requirement engineering is to change requirement. As some study [5], the rates of failed projects cause by changing requirements are 70.0% and by changing scope are 64.3%. So, validating changed requirements could reduce the failed rate of project related to change. At result of analyzing requirement errors [4], the rate of errors caused by incorrect facts is 49%, by inconsistency is 13% and by misplacement is 2%. As validating requirement suitability, the rates of failed project are reduced. However, the existing works proposed the criteria to validate requirements. These criteria might show the relationship among objectives, constraints and requirements unclearly. In views of changing requirement, some existing studies focus the changing rates and impacting rates; however, they might not validate changed requirements to project. The goal of our study is to validate requirements, which are developed newly or changed from existing requirements, considering objectives and constraints. If our goal is achieved, the rates of failed project caused by unsuitable requirements are reduced, our techniques can be used as criteria to select and triage requirements. And, our study might provide some quantitative rationales and information to support changing requirement. To achieve our goal, we establish some objective of our study. First, we study indicators and metrics to show requirement suitability considering project objectives and constraints, and propose expressions to calculate them using MCDM (MultiCriteria-Decision-Making) technique. Second, we propose the requirements suitability points that are quantities calculated by proposed expressions, and propose the techniques for interpreting them using statistic-analysis and a graph.

2

Term Definition

This section describes some major terms used frequently by our study. In generally, the definitions of terms used in our study conform to the definitions provided in IEEE 610.12 [6]. The definitions below are key terms as they are used in our study. · Objective: An objective is a high-level statements specified to achieve goals and to perform project successful. This is a key factor to decide project score, and might be identified at planning stage. Our study assumes that objectives are already identified. · Constraint: A constraint is a factor that a project might have an effect on. This consists of schedule, budget, related risks and technologies, regulation, and so on. Our study assumes that objectives are already identified. · Requirement: A requirements is a description that requirement engineers develop and specify from needs (newly and change) and expectations of various stakeholders who are related by a project. A requirement can be presented by various media, types and abstract-levels, and can be used by rationales and information for performing projects. Our techniques are applied after making requirements and use them as input artifacts.

A Study on Techniques for Measuring Requirement Suitability Considering Project

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· Requirement Suitability: To satisfy needs and expectations of various stakeholders, requirements should meet objectives and conform to constraints. In our study, these characteristic is called “Requirement Suitability.” If requirements have high suitability, then they will be included in a project, and could ensure that the results of project are correct. · Indicator and Metric: An indicator means a status to be able to show some facts. For example, the index-organism is an indicator to show water quality; whereas, a metric means a quantitative measurement to represent structural/mathematical model to show some facts. For example, the dissolved-oxygen is a metric to show water quality. · Requirement Suitability Point (RSP): A RSP is a quantity calculated by some metrics. That is, the quantity is calculated by some metric to make decision to validate whether requirements are suitable or not. In our study, The RSP is used as major information to make decision for including requirements in project.

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Proposing Indicators and Metrics for Requirement Suitability Considering Project Objectives and Constraints

The requirement presents something that customer and organization want to. To succeed project, the key factors through project life-cycle are the objectives and constraints. That is, it is necessary to ensure that requirements should meet objectives and conform to constraints. So, the way to show relationship between requirements and objectives/constraints is important. As such way, our study proposes some indicators and metrics for requirement suitability. Our study proposes 6 relationship-indicators to show relationship between requirements and objectives and between requirements and constraints, and propose 5 suitability-metrics considering these indicators. [Figure 1] shows the assumptions, scopes and procedures of our study.

Fig. 1. The assumption, scope and procedure of our study

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3.1


Proposing Indicators and Metrics for Requirement Suitability

In our study, we have developed the 6 relationship-indicators representing relationship of requirements/objectives or requirements/constraints, and 5 suitabilitymetrics to be calculated using these relationship-indicators to represent relationship requirements/objectives/constraints at the same time. The Relationship-Indicators for Relationship between Requirements and Objectives. To complete project, a number or requirements are elicited and have specific values. The requirement`s value can be acquired by comparison with objective, so it can be divided the degree of contribution to archive objective and the degree met by specific requirement. Based on the difference, we propose the following 3 relationship-indicators between requirements and objectives;

Pseudo-Value for each Req. (PV) is a relative value that is considered by relationship between objective and requirement. PV = f(Objective Contribution Rate, Objective Meet Rate, Relationship)

(1)

Objective Contribution Rate (OCR) is a relative degree how much one requirement has an influence on various objectives. This is a relative quantity to show that a requirement is contributed to objectives. OCR = f(one requirement, various objectives, Relationship)

(2)

Objective Meet Rate (OMR) is a relative degree how much various requirements has an influence on one objective. This is a relative quantity to show that an objective is met by requirements. OMR = f(various requirement, one objective, Relationship)

(3)

Where, f(x, y, Relationship) is an expression which can consider x and y given by relationship. The ‘Relationships’ are represented using matrix of relation-values as shown in [Figure 2].

Fig. 2. The relationship between requirements and objectives


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The Relationship-indicators for Relationship Between Requirements and Constraints. In our study, the constraints are acquired in planning phase, and cover many meaning such as organization's rule, regulation and legal, project's budget and schedule, assumption of following phases. The requirements will need some costs such as effort, money and time by considering constraints. Based on the difference, we propose the following 3 relationship-indicators for constraints. Pseudo-Cost for each Req. (PC) is a relative cost that is considered by relationship between constraint and requirement. PC = f(Constraints Conformance Rate, Constraints Impact Rate, Relationship)

(4)

Constraints Conformance Rate (CCR) is a relative degree how much one requirement has an influence on various constraints. This is a relative quantity to show that a requirement is conformed to constraints. CCR = f(one requirement, various constraints, Relationship)

(5)

Constraints Impact Rate (CIR) is a relative degree how much various requirements have an influence on one constraints. This is a relative quantity to show that a constraint is impact to requirements. CIR = f(various requirements, one constraint, Relationship) (6)

Where, f(x, y, Relationship) is an expression which can consider x and y given by relationship. The ‘Relationship’ is a represented matrix of relation-values as shown in [Figure 3].

Fig. 3. The relationship and requirements and constraints

The Suitability-Metrics and Requirement Suitability Point Considering Indicators. The relationship-indicators represent requirements` relationship with objectives or constraints independently. Therefore, to propose the metrics for both objectives and constraints, we have to consider relationship among the relationship-indicators; it is called “suitability-metrics”. We propose 5 suitability-metrics by considering a relative degree of relations among relationship-indicators as shown in [Figure 4]. The name of the proposed metrics and how they are calculated can be changed depending on context of the organization and project. A requirement is represented as specific quantity using such metrics; it is called “Requirement-Suitability-Point (RSP)”.

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Fig. 4. The proposed suitability-metrics considering relationship-indicators

OM-CC is a relative degree of meeting objectives when the specific requirement conforms to constraints. This is a metric to show a specific aspect of requirements, and can be used as suitability point considering views of those to measure. OM-CC = f(OMR, CCR)

(7)

OM-CI is a relative degree of impacted from constraints to meet objectives. This is a metric to show a specific aspect of requirements, and can be used as suitability point considering views of those to measure. OM-CI = f(OMR, CIR)

(8)

OC-CC is a relative degree of contributing objectives when the specific requirement conforms to constraints. This is a metric to show a specific aspect of requirements, and can be used as suitability point considering views of those to measure. OC-CC = f(OCR, CCR)

(9)

OC-CI is a relative degree of impacted from constraints to contribute objectives. This is a metric to show a specific aspect of requirements, and can be used as suitability point considering views of those to measure. OC-CI = f(OCR, CIR)

(10)

Pseudo-ROI for each Req. (ROI) is a relative degree of the specific requirement's value per a unit cost. This is a metric to show a specific aspect of requirements, and can be used as suitability point considering views of those to measure. ROI = f(PV, PC)

(11)


3.2

455

The Calculation of Requirement Suitability Points (RSP)

The assumption of proposed metrics above discussion is that the weights of requirements/objectives/constraints are same. However, the weight is different by viewpoints, dependency, etc. Therefore, the weights are determined using techniques such as AHP [7] and KANO [8], and expressions f(x, y, Relationship) are decided considering characteristics of project and organization. The expressions of indicator/metric are decided using Multi-Criteria-Decision- Making (MCDM), which is a discipline aimed for supporting decision makers faced with making numerous and sometimes conflicting evaluations [9]. Using MCDM, we make the expressions of OCR and OMR given by · fOCRRn (Reqn-th, VObj, VRn-O Rel) = Reqn-th * ∑(VObj * VRn-O Rel) · fOMROn (VReq, Objn-th, VOn-R Rel) = Objn-th * ∑(VReq * VOn-R Rel)

(12) (13)

If specific requirement is related to two or more objective, than the sum of relationship is considered, and it is shown following expression · fOMRRn = ∑(fOMROi * VOi-Rn Rel / ∑(VOi-Rj Rel) ), where (14) i = {0, ..., I}, j = {0, ..., J}, I = the number of Objectives, J = the number of Requirements

We have calculated relationship-indicators, so we can calculate the suitability-metrics. The expression of suitability-metrics might be f(x, y). · fOM-CCRn (OMRn-th, CCRn-th) = OMRn-th / CCRn-th

3.3

(15)

The Interpretation of Requirement Suitability Point (RSP)

A requirement is represented as specific quantity, which is requirement suitability point (RSP), using proposed metrics, using some expressions. Some RSPs are enough general to interpret directly. For example, if Pseudo-ROI of a requirement is 1.0, than we know that the value to be had though the requirement is same to its cost. Whereas, if Pseudo-ROI is higher than 1.0, we know that the value of requirement is bigger than its cost. However, some RSPs are too many meaning to understand directly. The RSP might be changed to understand them easily. In our study, we propose to change them using probability and reliability and to understand them. To achieve them, the RSP would be required to be normalized and presented by probability distribution, as shown in [Figure 5] First, the calculated RSP have to be normalized, because they have various ranges and Positive/Negative meanings, which is that a high quantity is a either good or bad meaning. After normalized, values lie in the interval [0, 1] and Positive meanings.

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Fig. 5. The procedure for changing suitability point

The probability for requirement to be selected is presented by probability distribution, which is used when result of population can be acquired [10]. The probability whether requirement is covered or not is represented by binomial distribution. And then, the central limit theorem [11] is generally used to change a binomial distribution to a normal distribution. We are able to calculate the probability and reliability of requirements using the calculated RSP and to draw the graph using them as shown in [Figure 6]. To select some requirements, we would decide the criteria for selecting requirements with the context of organization and project. The criteria are consisted in the probability and reliability of requirements above discussed.

Fig. 6. Decision-Information using statistical analysis

With the graph such as shown in [Figure 6], we might expect to select requirements that are selected by more over 70% probability and 45% reliability and to consider requirements that are selected by more over 30% probability and 30% reliability. Using the criteria, the requirements R5 and R6 are selected and delivered to next phase such as analysis phase, and the requirement R1, R2, R8 are considered before delivering to next phase. Whereas, the others R3, R4, R7 don't meet the criteria, they are refined additionally.


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Conclusion

To succeed project, a requirement is satisfied by objectives and is conformed to constraints, and the techniques and criteria to validate them are important. So, our study proposes the techniques for measuring requirement suitability. To measure them, we propose relationship-indicators and suitability-metrics among requirements, objectives and constraints, and the quantities calculated using them are called requirement suitability point (RSP). Moreover, we propose the techniques for interpreting RSP using statistic-analysis. Our techniques might be contributed to reducing the rates of failed project, and provide information/rationales of decision making for selecting requirements properly. So, the effort occurred due to inappropriate requirements might be decreased using our study. As future study, we should carry out various case-studies considering practical field and refine our techniques. And then, although assuming that newly developed requirement and changed requirement have same characteristics, they are not same. So, we should refine our techniques considering changing requirements. Finally, we should study decision-making technique, and implements automation-tools using our metrics. Acknowledgments. "This research was supported by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC(Information Technology Research Center) support program supervised by the NIPA(National IT Industry Promotion Agency" (NIPA-2012-(C1090-1131-0008).

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