International Journal of Computer Applications (0975 – 8887) Volume 56– No.17, October 2012 46 Integrating TOPSIS and AHP into GORE Decision Support System Vinay S NMAMIT, Nitte, India Shridhar Aithal TAPMI, Manipal, India Sudhakara G MIT, Manipal, India ABSTRACT Decision making in Software Engineering plays an important role at different stages of Software development life cycle. In this paper we consider the case study of selecting one among the three Content Management Systems (CMS) for a university website. We use our Goal-Oriented Requirements Engineering (GORE) method to identify the soft goals which play a vital role in deciding which CMS is chosen. Analytic Hierarchy Process (AHP) is then used to prioritize the soft goals. The output of AHP is used as input to Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) which produces a metric which decides the best alternative among the candidates. General Terms Requirements Engineering, Decision Support System Keywords GoalOriented Requirements Engineering, Analytic Hierarchy Process, Technique for Order of Preference by Similarity to Ideal Solution, Soft goals 1. INTRODUCTION It is well acknowledged in Software Engineering that while functional requirements are important, eliciting and capturing the non-functional requirements (NFR) during the requirements engineering phase becomes even more important [1]. Goal-oriented requirements engineering (GORE) approaches make a good attempt to address the essential quality characteristics which are commonly known as non- functional requirements [2, 3]. NFRs play a major role in coming up with alternative system configurations for a given functionality. Gunther Rahe in his paper [6] highlights the importance of Decision Support system (DSS) in Software Engineering. Decisions are the driving engines for all stages of software development and evolution. Decisions can be related to methods, tools, and techniques. Decisions are aimed at answering the questions ‘How’? ‘How good’? ‘When’? ‘Why’? and ‘Where’?. The objective is to have a sound methodology which provides rationale for the decision arrived at. The importance of decision making techniques is also addressed in [7, 8 and 9]. The importance of stakeholders in decision making is done in [10]. Architecture decision making is closely linked to requirements engineering and the aspects related to this are addressed in [11] and [12]. A survey of various requirements prioritization techniques is undertaken in [13]. Decision-Making in Software Engineering is extremely challenging because of a dynamically changing environment, conflicting stakeholder objectives, constraints, coupled with a high degree of uncertainty and vagueness of the available information. The Analytic Hierarchy Process (AHP) is based on the experience gained by its developer, T.L. Saaty [12], while directing research projects in the US Arms Control and Disarmament Agency. AHP is a well established process used as an aid to decision making when confronted with multiple stakeholders, competing and conflicting objectives, constraints and environments. AHP has been widely used across multiple domains in business, government, social studies, R&D, defence and other domains involving decisions in which choice, prioritization or forecasting is essential [12]. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is presented in Chen and Hwang [21], with reference to Hwang and Yoon [22]. The basic principle is that the chosen alternative should have the shortest distance from the ideal solution and the farthest distance from the negative-ideal solution. Combining our GORE method with AHP and TOPSIS in decision making provides adequate rationale for the decision arrived at. In this paper we consider the case study of selecting one among the three Content Management Systems (CMS) for a university website. We use our Goal-Oriented Requirements Engineering (GORE) method to identify the soft goals which play a vital role in deciding which CMS is chosen. Analytic Hierarchy Process (AHP) is then used to prioritize the soft goals. The output of AHP is used as input to Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) which produces a metric which decides the best alternative among the candidates. In Section 2 and 3, we discuss our proposed approach and highlight how our GORE approach is used for identifying soft goals (non-functional requirements), their contribution links to each of the alternative. Section 4 discusses how AHP is used to prioritize the soft goals. Combining the output of GORE with TOPSIS and AHP is discussed in Section 5. The effectiveness of the proposed method is discussed in Section 6. 2. PROPOSED APPROACH The major steps involved in our proposed approach are shown in Table 1: