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1. Trade-off analysis using simple machine learning algorithms Presenter

2. Abstract In order to elicit most suitable requirements different requirement elicitation techniques are used by the engineers. The selection of suitable technique in a particular situation is a challenging task. The reason is that project attributes and their sub-situational factors have high impact on a technique selection. A technique may be suitable in one situation but may not fit in the other. This research proposed simple additive weighting method to carry out the trade-off analysis among technique selection on the basis of project attributes and their sub-situational factors.

3. Introduction Requirement engineering is the most critical and important phase of software engineering. Software life cycle is based on this phase, which untimely lead toward the success/failure of the software. This phase mainly converts ambiguous, incomplete necessities and desires of stakeholders into clear, complete and proper specifications Requirement elicitation is more challenging where stakeholders belong to different culture and technology diverse conditions [3]. Hence, it is very clear that the overall success and failure rate of a software project is dependent upon this activity. The requirement elicitation process is strongly supported by different elicitation techniques. Elicitation techniques are used by requirement engineers to gather user requirements for a particular software project. The main objective of elicitation techniques is to extract proper requirements and resolve issues exist among different stakeholders with respect to requirements.

4. Related work Edgar Serna M [6] presented analysis and selection to requirement elicitation techniques. In this study techniques are analyzed and evaluated and a matrix is presented to requirement engineer for the selection of elicitation techniques. Diana Marcela Vasquez Bravo et al. [14] presented to improve the acquisition of Knowledge management with help of different elicitation techniques. They presented the outcomes extracted from empirical results to evaluate the knowledge acquisition efficiency in the phase of externalization of nonaka’s model by using various elicitation techniques

5. SAW for elicitation technique selection The simple additive weighting (SAW) method is one of the most commonly used and well known multi-attributes decision making technique. In this method weight is assigned to each attribute (criteria) according to its importance and then weight is assigned to each alternative with respect to attribute. The weighted sum of performance ratings of each alternative is obtained regarding attributes (criteria). Let C = {C1, C2, C3, ……….Cm} be the set of criteria where Ci such that i = 1,2,3,4 …….. m and A = {A1, A2, A3 ……….. An} be the set of alternatives where Aj such that j = 1,2,3,4 ………..n

6. SAW process • Step 3- To obtain the normalized decision matrix divide the values in each row of the table 5 by the maximum value in that row according to equation 1. Table 6 represents the normalized decision matrix as given below: Table 6.Shows normalized decision matrix

7. SAW process • Step 5- The best technique is obtained on the basis of sub situational factors of project environment attributes. To obtain the final result the sum of each column in table 7 is calculated as shown in table 8. Table 8. Results obtained from the addition of each column in table 7 Figure 1 shows the graphical representation of the final result obtained by using SAW method Figure 1: Graphical representation of the result obtained by using SAW method

8. C. Trade-off analysis among elicitation techniques Figure 2: Importance of a technique with respect to each sub-situational factor

9. Discussions When multiple criteria and alternatives exist, the selection of best alternative is always a difficult task. In such situation MCDM methods are very useful to use and find the optimal solution in multiple alternatives. This research work also contains a situation which has multiple criteria that are software project environment attributes and its sub situational factors, and having multiple alternatives in the form of elicitation techniques. In this study SAW method is used to select the best elicitation technique according to the situation of sub situational factors of software project attributes. SAW is also one of the MCDM methods which can facilitate the decision making mechanism easy when an analyst needs to select the best alternative among the multiple alternatives based on some criteria. The results provided by the SAW method as given in graph 2 clearly represents that which elicitation technique is suitable to use in a particular situation and which one is inappropriate. The reason is this; priorities are assigned to elicitation techniques based on the sub situational factors of software project attributes. Hence this assignment of priorities to elicitation techniques can clearly help requirement engineers to carry out trade off analysis among elicitation techniques based on sub situational factors of software project attributes. It will further help requirements engineers to make a proper decision regarding technique selection according to the situation of software project. For example if the sub situational factor of attribute SCO is tight then according to priority list the analyst will select one technique and if SCO is average or loose then he/she will use the other technique.

10. Conclusion In this research, the SAW method is applied to find out which technique in suitable in a particular situation. The SAW is a MADM method which is beneficial in solving decision making problems. In the current study, initially weights were derived from experts for sub-situational factors of project attributes and then with respect to these sub situational factors elicitation techniques weights were derived. The results obtained by applying the SAW method shows adequacy of elicitation technique and inappropriateness in a particular situation of project. Thus the trade-off analysis among elicitation technique can be easily done. This study will help requirement engineers in decision making and changing policy according to the nature of the project regarding elicitation technique selection. The limitation of this study is that here only 14 software projects attributes, their sub situational factors and traditional elicitation techniques are considered because they are mostly reported by the industry and experts in the industry. There are other software project attributes which have their own sub situational factors which need to be considered in order to carry out trade-off analysis among elicitation techniques. In future, some more efficient and accurate elicitation technique will be tried to overcome the limitation of elicitation technique selection.

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