# On the Use of Quality Models to Address Distinct Quality Views
## 2 Related Works  
[PERSON] et al. in [5] carried out a comprehensive systematic literature review as per [16], and developed a scoring scheme for measuring the relevance of software product quality model families for the industrial and scientific communities. In addition, an execution tracing quality study of software product quality models was reported in [3]. Other studies on software product quality models have been carried out by [PERSON] in [17] (up to 2011) and by [PERSON] et al. in [18] (up to 2014), respectively. However, these two studies are not systematic as per [16], do not measure the quality model families' relevance for the industrial and scientific communities, and include partial quality models that deal with a specific part of software product quality. Software product quality models defined, tailored or referenced since 2000 are elicited in [5], which was complemented with an analysis of the developments and trends that emerged during this period of time. Criteria regarding whether a publication establishes a new software product quality model family or solely adjusts a quality model already in use while keeping the existing quality model's concepts are also introduced in detail in [5]. In addition, the relevance of the quality model families for the industrial and scientific communities was measured (1) on the extracted, structured and synthesised qualitative information from the software product quality model definitions, and (2) on the following quantitative indicators: (i) relevance score; (ii) quality score average; (iii) time range; and (iv) 12-month average Google Relative Search Index. The identified 23 software product quality model families reveal huge differences in terms of application and research. To make the present study self-contained, a summary of the main contributions of the study [5] are given below:  
1. Search queries were developed and recorded for automatic document search;
2. Searches were carried out in six computer science digital libraries, including IEEE and ACM;
3. The automatic document search was complemented with manual and reference searches;
4. All the documents returned by the searches were pre-analysed, the duplicates were removed, the non-primary sources were removed, the complete software product quality models were included in the investigation, but process quality models and partial quality models were excluded with the reason for exclusion recorded;
5. Documents were assigned to the software product quality models they define, tailor or reference, which lead to the creation of related document clusters, i.e., to _software product quality model families_. Publications and model definitions stem from the academic and industrial domain, including EMISQ [19], SQUALE [20], FURPS [10, 11], SQUE and ISO9126 combination [21], Quality Model of Kim and Lee [15] from companies such as Air France, Siemens, Qualxio, IBM, MITRE, and Samsung;(6) Each document was analysed in-depth to extract the terminology and concepts of each software product quality model;
* (7) Each document was assigned a score value for clarity of the publication and a score value for the actuality of the publication based on defined scoring criteria; the clarity score discriminates whether a quality model was published in a detailed mature state in one publication or in several publications by means of smaller increments;
* (8) The quality score of a document is defined as the product of its clarity score and actuality score;
* (9) For each cluster of documents, the following indicators are defined: 1. The relevance score as the sum of the quality scores of its documents; 2. The quality score average; 3. The publication time range; and 4. The 12-month average of Google Trends called the Google Relative Search Index [22]. The first two indicators are related to research intensity, while the third one is related to the duration of research on a software product quality model family, none of which are normalised.