## 2 Study Background
(2019) presented a multi-criteria decision making model based on Fuzzy logic for cloud adoption. The criteria and sub criteria of software testing that were used in making the multi-criteria model were identified by performing a systematic literature review and empirical study. The proposed model was used by the decision makers to suggest cloud adoption for software testing. [PERSON] et al. (2019) proposed a framework based on AHP and TOPSIS that evaluates the security of IOT devices. The proposed framework consists of two phases; First, weights of the factors are calculated by using AHP. Second, the alternatives are assessed with respect to criteria by using the TOPSIS technique. The proposed framework suggests the most secure and reliable option among the available alternatives. [PERSON] et al. (2019) proposed a decision support system based on ANP for the selection of requirements elicitation techniques. A total of 14 factors were identified through the literature; namely key stakeholders, computer literacy, schedule constraints, stakeholders' diversity, organization culture, prospective system's nature, number of people in a session, expressiveness of users, reusable requirements, financial constraints, stakeholders' relationship, domain knowledge, existing system maintenance, relationship of clients and analysts. The model is based on these requirements elicitation's attributes that suggests one of the suitable techniques from the six alternatives. [PERSON] (2018) proposed a novel technique to asses the usability and security of healthcare software by using the combination of three tools, Fuzzy logic, ANP and TOPSIS. It is the most effective technique that assesses the usable security of applications regarding healthcare. The results produced by the proposed model can be used in the management of security with no impact on users usability. [PERSON] et al. (2018) conducted a systematic literature review and then performed industrial survey to validate the results. They identified a total of 30 best practices regarding cloud based global software development. These practices were categorized into eight groups, including resource management, integration, communication, stakeholders, procurement, time, scope and quality. The best practices of cloud were prioritized by using Fuzzy AHP technique. [PERSON] et al. (2018) performed an empirical study that identified a data set that comprised of 19 attributes, namely supplier size, team size, domain, project size, following international standards, code complexity, following standard in documentation, quality of document, maintenance type required, code structure, time zone, client's experience, language barrier, Service Level Agreement (SLA), method adopted and age of the system. A machine learning technique was proposed based on the identified attributes for service providers to assess the client proposal in offshore software maintenance outsourcing scenarios. [PERSON] et al. [30] explored the development and operational challenges by using Systematic Literature Review (SLR), which was followed by an online survey to validate the identified list of factors. The research study resulted in a list of critical success factors that are faced by companies while using the development and operations (DevOps). The identified critical challenges were prioritized using the Fuzzy AHP technique. [PERSON] et al. [31] discussed that, due to software failures, when the stakeholders are unable to meet the SLA, this leads to the dissatisfaction of the client and impacts the vendor performance as well. They examined the factors that cause the software failures and adopted the AHP technique to prioritize these factors. [PERSON] et al. [32] used these attributes, such as access control, authentication, non-repudiation, confidentiality of data, communication flow, integrity of data, availability and privacy. On the basis of these attributes, they presented a Fuzzy logic model that helps the software engineers to select software components. [PERSON] et al.