## 2 Related Research  
There is a long list of MCDM techniques, such as SMART, FAHP, ANP, ELECTRE, TOPSIS, etc. Normally, different methods are merged to enhance the process of decision-making. This study aims to employ two multi-criteria methods, which include FMEA and FAHP integrated with grey relational analysis, to evaluate and rank the five selected MLPs. Furthermore, the study adopts the technical requirements concerning the ISO/IEC 9126 model to generate a suitable framework for the effective evaluation of the selected MLPs using a combination of the FMEA and FAHP techniques. The Fuzzy AHP (FAHP) method is an extension of AHP which was developed by [PERSON] in 1975 [9]. The FAHP combines the fuzzy set theory and also the analytical hierarchy process, which makes it a more powerful approach for remedying problems that require multi-criteria decision-making (MCDM) approaches. FAHP is generally used as a decision-making method of prioritizing values for different experts in an MDCM [10]. In their study, they employed the Fuzzy AHP method to generate weights for risk factors. Different techniques exist for obtaining the weights from fuzzy pairwise comparison matrices. FAHP leverages a range of values instead of a range of crisp values to deal with the vagueness, uncertainties, and ambiguities associated with the decision-making process for decision-makers [10]. FAHP is a decision-making method used to analyze and rank alternatives in a hierarchal structure. The overall objective was to prioritize experts considering three different alternatives as experts (D1, D2, and D3) based on three criteria: experience, education, and individual level. The majority of Fuzzy AHP applications use the simple extent analysis method proposed by [11] because fuzzy weights are difficult to compute in the form of crisp weights. Research in various literature shows that a very effective FAHP approach is the extent analysis method. This method was introduced by [PERSON] in 1992. [PERSON], in his paper, vividly illustrates the application of the FAHP extent analysis method for introducing the synthetic extent value S of a pairwise comparison by applying the principle of the comparison of fuzzy numbers and also demonstrates the decision process by an example. The extent analysis method was also used [12]. They generated fuzzy synthetic extent values and applied the method of comparison of fuzzy numbers in calculating the normalized weight vectors. These vectors were used to obtain the final score of each student for breaking a tie situation and deciding the rank among the students in the case of having the same marks in an examination. The failure modes and effects analysis (FMEA) is used to identify hazards in requirements or possible failure of software. FMEA is used to estimate the risk priorities of failure modes associated with an event or product. In the case of this study, FMEA is used to evaluate the potential failure of MLPs through the risk priority number (RPN) value. The risk priority number (RPN) is the estimated numerical value of the assessment of risk assigned to a process or steps in a process as part of its FMEA. RPN is calculated by multiplying the risk factors occurrence (O), severity (S), and detection (D) of a potential failure. [13] in his paper, he proposed the possible use and application of FMEA in the analysis stage by identifying potential hazards in a bid to develop software defenses by developing fault-tolerant or self-checking techniques to reduce the probability of their occurrence. Also, researchers in [14] used failure mode and effect analysis (FMEA) as a tool for evaluating Enterprise architecture (EA) risks. However, due to some drawbacks of the traditional FMEA, as stated by their research, instead of calculating RPN--the study prioritized EA risk factors with fuzzy VIKOR. Researchers in [10] employed the use of FMEA to compute the RPN value of Maintenance Policy Selection (MPS) of equipment using three dimensions, including Severity, Occurrence, and Detection.