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Measuring Software Quality in Use: State-of-the-Art and Research Challenges

Software quality in use comprises quality from the user's perspective. It has gained its importance in e-government applications, mobile-based applications, embedded systems, and even business process development. User's decisions on software acquisitions are often ad hoc or based on preference due to difficulty in quantitatively measuring software quality in use. But, why is quality-in-use measurement difficult? Although there are many software quality models, to the authors' knowledge no works survey the challenges related to software quality-in-use measurement. This article has two main contributions: 1) it identifies and explains major issues and challenges in measuring software quality in use in the context of the ISO SQuaRE series and related software quality models and highlights open research areas; and 2) it sheds light on a research direction that can be used to predict software quality in use. In short, the quality-in-use measurement issues are related to the complexity of the current standard models and the limitations and incompleteness of the customized software quality models. A sentiment analysis of software reviews is proposed to deal with these issues.

and 2) it sheds light on a research direction that can be used to predict software quality in use. In short, the quality-in-use measurement issues are related to the complexity of the current standard models and the limitations and incompleteness of the customized software quality models. A sentiment analysis of software reviews is proposed to deal with these issues.

INTRODUCTION
With a large amount of software published online it is essential for users to find the software that matches their stated or implied needs (quality in use). Users often seek adequate software quality. It is important to quantify software quality from a user's perspective in order to compare different types of software, thus allowing users to acquire the best software quality. To understand what is meant by inadequate or adequate software quality, it helps to define quality.
Defining quality is not easy in that quality is based on many possible disciplines: philosophy, economics, marketing, and so on. Garvin (1984) identified five views/approaches of quality. The closest definition to this work is the user-based approach definition "meeting customer needs." As referred to by Deming (2000), Shewhart (1931) defines quality: "There are two common aspects of quality: One of them has to do with the consideration of the quality of a thing as an objective reality independent of the existence of man. The other has to do with what we think, feel or sense as a result of the objective reality.
That is to say, there is a subjective side of quality." This side is yet another meaning of quality in use. If the customer is satisfied, then a product or service has adequate quality.
Quality in use or perceived quality by users is very important to many applications. Quality in use is gaining more attention, especially in applications where end users are the core of a successful project.
There are many benefits that can be gained if qual-ity is adopted early in the software development life cycle. Quality in use, a user-centered approach, will get users' feedback early; thus, different ways to access software, including content and user interface, are adopted early, hence software success. A good software design will let the user work effectively and efficiently, saving time; thus, it will increase user productivity. Moreover, if the user interface (one aspect of quality in use) takes into account user needs and expectations, it will reduce system errors. On the other hand, if the system interface is poorly designed, it will result in increased training time and malfunction errors. On one hand, given these benefits, it is more likely that the user will use the application; on the other hand, software vendors will get improved user acceptance. In fact, systematic evaluation of quality in use is important because it allows continuous software recommendations and improvements.
Moving from the general concept of quality of software, software quality can be conceptualized from three dimensions: software quality requirements, the quality model, and quality characteristics. Quality require-ments are what the user needs in the software, such as performance, user interface, or security requirements. The quality model is how characteristics are related to each other and to final product quality. Measuring software quality will check if user requirements are met and determine the degree of quality. The final objective of software quality is to know whether the software is of adequate or inadequate quality. To identify the so-called adequate or inadequate quality, a software quality model is needed. The quality model categorizes quality into characteristics overseen by measurement methods. The quality model is a "defined set of characteristics and of relationships between them, which provides a framework for specifying quality requirements and evaluating quality" (ISO/IEC 2005, 7). The quality model identifies the adequate or inadequate quality attributes. The quality characteristic is the "category of software quality attributes that bears on software quality" (ISO/ IEC 2005, 9), simply the main factors or properties that determine whether quality is adequate or inadequate. Measurements are "sets of operations having the object of determining a value of a measure" (ISO/IEC 2011, 52). That is to say, the measurement is the actual score of adequate and inadequate quality attributes.
The ISO/IEC 25010:2010 standard (referred to as ISO 25010 hereafter), a part of a series known as software quality requirements and evaluation (SQuaRE), has two major dimensions: quality in use (QinU) and product quality. The former specifies characteristics related to the human interaction with the system and the latter specifies characteristics intrinsic to the product. QinU is defined as the "capability of a software product to influence users' effectiveness, productivity, safety, and satisfaction to satisfy their actual needs when using the software product to achieve their goals in a specified context of use" (ISO/IEC 2005, 17). The QinU model consists of five characteristics: effectiveness, efficiency, satisfaction, freedom from risk, and context coverage. Figure 1 illustrates the definition of these characteristics.

Problem Statement
This article investigates these problems: 1. There are a limited number of literature reviews on software QinU. Although there are many research articles about software quality, to the authors' knowledge this is the first work that specifically identifies the problems of measuring QinU.
2. There is insufficient research on other possible research directions to tackle the first problem.
To the authors' knowledge, few works target to resolve the QinU problem systematically (Leopairote, Surarerks, and Prompoon 2012).

Research Contributions
This article makes the following contributions: • Presents a research direction to envision software QinU from software reviews. Given the issues related to measurement, sentiment analysis, an emerging branch of natural language processing, can be used to analyze textual user judgments about software (Mei et al. 2007;Taboada et al. 2011).

SOFTWARE QUALITY-IN-USE MODELS
There have been many works in software quality models, but to the authors' knowledge no research has been conducted to summarize the main problems of measuring quality in use. Measuring software quality in use can be divided in two main frameworks: standard model frameworks and customized model frameworks.

Standard Frameworks
There have been many standards that can support software quality, but they do not contain any specific model for software quality, but rather checklist guides. For example, it is suggested in the literature that the ISO 9000 family of standards not be used for software quality (Stelzer, Mellis, and Herzwurm 1997). IEEE Std. 730 supports quality assurance plans. Capability Maturity Model Integration (CMMI) (Ahern, Clouse, and Turner 2008) is a process improvement training and certification program. These standards are not designed to address quality in use or specific characteristics of software product quality.
Recently, the SQuaRE ISO standard series is a result of blending the ISO/IEC 9126 and ISO/IEC 14598 series of standards. The purpose of the SQuaRE series of standards is to assist in developing and acquiring software products with the specification of quality requirements and evaluation. From the stakeholder's viewpoint, the quality requirements are specified, and the quality of the product is evaluated based on this specification using the chosen quality model, quality measurement, and quality management process.
To measure QinU, five divisions of the SQuaRE series must be considered. Figure 2 illustrates the organization of the SQuaRE series representing families of standards, which are further called divisions. To measure QinU effectively, the Quality Management Division has to be considered by taking standard definitions; the QinU model is part of the Quality Model Division; the Quality Measurement Division contains the measurement for-mulas. The Quality Requirement and Quality Evaluation Divisions are used to specify quality requirements and evaluate quality. Thus, the quality model is defined, managed, and measured according to quality require-ments and quality evaluation processes.  (2013) adopted the It is important to note that product dimension has a effectiveness and productivity of the ISO 9126 model for direct impact on QinU measurement. For example, the a service-based mobile ecosystem. Motivated by the 9126 functional suitability, performance efficiency, usability, model structure, Osman and Osman (2013) proposed reliability, and security of product quality will have a sigthree categories to model quality in use for mobile nificant influence on quality in use for primary users. This government systems. They are usability, acceptance, will add more complication to the measurement process. and user experience. With a defined set of tasks and a Based on the ISO standards, measuring the QinU post-test questionnaire, they calculated the quality in use. is not achieved directly. While the standards provide Oliveira, Tereso, and Machado (2014) linked the ISO 9126 avenues for customization, they need careful quality characteristics functionality, usability, and operability assurance to provide apparent integration between to a set of criteria/requirement of project management related standards. Even more, customizing such stantools in order to help project managers evaluate project dards is not defined clearly in the standards. More issues management tools. The quality, quality in use, usability, on these standards can be found in a later section. and user experience (2Q2U) model (Lew, Olsina, and Next, other models of QinU, the customized models, Zhang 2010) extends the ISO 25010 model with informaare discussed.
tion quality and learnability in use characteristics, and

Customized Models
actual usability and user experience. The Semantic Web Exploration Tools Quality in Use Model (SWET-QUM) There have been many models that have been developed to (González et al. 2012) extends ISO 25010 with several measure software quality; some of these models have some metrics related to semantic Web exploration tools. In of the quality-in-use characteristics such as user experience SWET-QUM tasks are customized to Web exploration and usability, but do not consider all the characteristics as tools, and are manually linked to the ISO QinU model. defined in the ISO 25010 standard. Moreover, term defini-Strategic quality models Quality in use can be achieved tions across different models are sometimes confusing, indirectly by affecting product quality, using a new evaluwhich limits the accurate mapping of quality-in-use ation technique, or by using a completely new framework. characteristics (García et al. 2006). Following are some Becker, Lew, and Olsina (2012) proposed SIQinU (a strategy related models assembled in logical order. These groups for understanding and improving quality in use) to evalucould be overlapping or intersecting with each other. ate product quality in order to recognize quality-in-use problems. They also suggested improving quality in use by changing product quality attributes' operability (learnability, ease of use) and information quality. Alaa, Menshawi, and Saeed (2013)  Quality in use is proposed as an added value to business process development (Heinrich et al. 2011). The added measures are extracted from the literature. Heinrich, Kappe, and Paech (2014) proposed the Business Process Quality Reference Model to provide a comprehensive understanding of business process quality.
Paradigm-specific models Some quality models are specific to software paradigm style (procedural vs. objectoriented approach) or programming language. To ease and manage the design of object-oriented software, the strategy factor model is proposed (Marinescu and Ratiu 2004). It explicitly relates the quality of a design to its conformance to a set of essential principles, rules, and heuristics. Bansiya SQUID is designed for the telescience project and is more conserved with product quality rather the QinU.

Hierarchical Models
These models link various quality characteristics together at different levels, which in turn are finally linked with root product quality. Following are some examples of these quality models.
McCall's quality model (McCall, Richards, and Walters 1977)  Boehm's quality model (Boehm et al. 1978 Dromey's quality model (Dromey 1995) Dromey states that quality characteristics cannot be built directly into the software; the quality evaluation differs for each product; and a dynamic process is needed to cover dif-ferent systems.
Dromey distinguishes between product components from externally visible quality attributes. The QinU of the ISO standard is implied by both the descrip-tive and correctness characteristics of the Dromey model.

Usability-Based Models
There are many works that aim to measure one aspect of quality in use called usability. The International Organization for Standardization defines usability as the effectiveness, efficiency, and satisfaction with which specified users achieve specified goals in particular environments (ISO 1998). There is no consensus agreement on this definition; it might refer to user interface, ease of use, or user friendliness (Bačíková and Porubän 2014; Carvajal et al. 2013;Holzinger 2005;ISO 1998;Shackel and Richardson 1991). Usability is frequently linked with user experience with the software (Brooks and Hestnes 2010;Masip, Oliva, and Granollers 2011;Scholtz 2006).
According to the definition of ISO 25010, usability, or sometimes called friendliness, is not covering freedom from risk or context coverage characteristics. The intended goal of this work is to highlight the problems of quality in use covering the global definition of quality in use as per ISO 25010. Following is a sample of related works to usability. Huang and Chiu (2014) proposed a new process to evaluate the usability of the healthcare system (Kincet Game) to enhance the user experience. The process predefines a set of tasks to be followed by users.

Medical domain
A questionnaire was then used to evaluate the usability of (tasks) and using six quality aspects, including usability.

Provider-Specific Models
Here is a set of specific quality models of certain organizations. Grady (1992) and later extended and owned by IBM Rational Software (Ambler, Nalbone, and Vizdos 2005;Jacobson 1999;Kruchten 2004). FURPS stands for functionality, usability, reliability, performance, and supportability. The FURPS+ includes additionally design constraints, implementation requirements, interface requirements, and physical requirements. The QinU of the ISO standards is implied by usability and performance characteristics.

Summary of Studied Quality-in-Use Models
A direct mapping between different quality-in-use models is difficult due to the tight relationship with product quality and discrepancies in used terminologies; however, several conclusions from the previously discussed works are drawn.
To enable a fair comparison between quality models, a baseline is needed. Whether to choose custom-ized or standard models is a dilemma. Many quality-in-use models are context specific and there is no complete model. Kläs et al. (2014) proposed using comprehensive quality model landscapes (CQMLs) as a scheme for quality model relationship comparison. Bakota et al. (2011) identified that a good quality model should be interpretable, explicable, consistent, scalable, extendible, and comparable. However, these approaches are subjective. In this article the ISO 25010 standard quality model is the chosen baseline to compare with other models because it is assumed to be an acceptable approach globally. Figure 4 shows the QinU characteristics of ISO 25010 as compared to studied works.
From the previously studied models, several challenges must be tackled. Following is a list of challenges.

QUALITY-IN-USE CHALLENGES
For readability and understandability, following are some major challenges that can be faced while measuring software quality in use in general, measuring quality in use using standard frameworks, and measuring quality in use using customized models.

General Challenges
Task measurement To measure QinU there is a need to agree with the software user on a set of tasks that he or

Effectiveness
Many models suggested adoption of lower properties of effectiveness, such as the user interface (Alnanih, Ormandjieva, and Radhakrishnan 2014;Hsu and Lee 2014), navigation (Ardito et al. 2014) and learnability (Lew, Olsina, and Zhang 2010), while others employ a higher-level usability to represent this characteristic. It is concluded that a consensus agreement should be applied to effectiveness properties. Hence, the literature lacks research to measure the accuracy of achieving a goal to complete the effectiveness definition. Efficiency Some quality models add the role of users as resources in quality requirement process (Bakota et al. 2011); conversely, the resources can also include the computer system infrastructure that is consumed to achieve user goals. Possibly these resource statistics are collected during run time as product quality model characteristics. So, it is believed a linkage with software reliability, performance, and portability can enhance this characteristic calculation. Freedom from risk This characteristic tends to be vague in studied works. Many works do not consider the data loss, for example, as a potential risk to software usage. In the ISO 25010, it is not clear how it is linked to the measurement of data quality. ISO 25024 information has been added as part of quality model (Becker, Lew, and Olsina 2012;Lew, Olsina, and Zhang 2010), but it was not shown how it will be used. Satisfaction The subjective parts of quality in use were modeled by user experience (Lew, Olsina, and Zhang 2010) and learnability. In fact the effectiveness, efficiency, and risk mitigation are direct factors to satisfaction characteristic. Quantifying this characteristic is difficult, as satisfaction can be just word of mouth. Context coverage This characteristic has not yet been studied intensively in the literature. It has been shown that users have different profiles, software platforms, educational background, and interests. Also, the software itself has different trends in its life cycle. The software may gain attraction at the beginning, but later it may get less attraction due to extra features needed by the users or other service-related factors such as software delivery and support.
The assumption that all users should have used the software in its context of use may be a vague assumption. Consequently, this characteristic needs more focus.
she needs to execute to accomplish a pragmatic goal ("do goals" to achieve the task, such as pay a bill). This means the user should be involved in the quality requirements specification, which might not be applicable at all times.
Another issue related to task measurement embraces the variability of tasks from one software function to another and from one software to another. For example, a task to open a file for writing is different than a task of removing special characters from a text file. Worse off, defining what the tasks are is by itself a major challenge. Hedonic tasks (the "be goals") that imply user satisfaction cannot be specified; thus, they cannot be measured directly.
The Web software development life cycle Users of publicly available online software are rarely asked to be part of the system development life cycle, but usually the software companies/developers make assumptions on user needs. In cases where software is designed to be used by global users such as operating systems or antivirus software, then software companies have to find other ways to determine user needs. However, it might be a disaster when users start using the software. This is not because of software bugs-that is usually not the major problem-but rather because users are not satisfied. Users need to see software doing what they were thinking of without draining their minds with the life cycle of the software.
Dynamic customer needs Customer needs are dynamic and they can change from time to time, so quantitative measures might not be suitable. Ishikawa (1985) states that "We must also keep in mind that consumer requirements change from year to year and even frequently updated standards cannot keep the pace with consumer requirements." These needs are usually resolved by new versions of software; however, software might get complicated or buggy due to extra features added that were not planned ahead. If users are involved ahead of time, these needs might be planned for in advance. Therefore, this problem returns one to the first and second unsolved issues mentioned previously.

Standard Quality Frameworks
Quality model critiques There are problems intrinsic to quality models. Deissenboeck et al. (2009) identified critiques to many software quality models; they are unclear of their purposes, not satisfying users on how to use the quality models, and there is no uniform terminology between different models (García et al. 2006). Masip, Oliva, and Granollers (2011) stated that user experience is implied in ISO 25010 but is not defined. Deissenboeck et al. (2007) showed that the abilities of ISO/IEC 9126 are abstract and hard to measure. Alnanih, Ormandjieva, and Radhakrishnan (2014) showed that the existing standards do not satisfy the requirements for measuring the quality in use of the mobile user interface in the healthcare domain. Kläs et al. (2014) showed that "no guidance is available on how to select, adapt, define, combine, use, and evolve quality models." So, the standard models do not clarify how to customize or use quality models; thus, the aggregation of the evaluation score is challenging (Mordal et al. 2013).

Evaluation requirements
Looking into the mathematical formulas for quality in use in ISO 25022 and the proposed methods to measure quality in use, quality managers might find it a hard job. For example, to measure the effectiveness, task completion, task effectiveness, and error frequency must be calculated.
To get such values an evaluator needs to measure user performance, such as the number of tasks completed, total number of tasks, and number of errors made by users. Practically embedding monitoring tasks with operating software is a major failure because it will consume lots of resources, while software maximum performance is one goal of quality. Even if a usability lab is exploited, it has to be equipped with tools such as eye trackers, monitoring key pressing or mouse movement (González et al. 2012). Using such labs is not feasible for a single user if he or she wants to measure the software quality in use alone.

Quality standards integration requirements
Measurement of quality in use has to be done in line with the ISO standards ISO 2502n to ISO 25024, and in line with the ISO 25010 model (see Figure 2 and Figure 3).
Integrating the related quality processes of these models is a problem for quality engineers. The reason behind this problem is the need of experienced engineers given limited information in the standard models on how to customize them, especially for small-sized companies. In an extension to ISO 25010, Lew, Olsina, and Zhang (2010)

QinU boundary factors
While a quality-in-use model tries to measure the human computer system interaction, there are many factors that affect quality in use at the same time. They are: the information system, target computer system, target software, target data, usage environment, and user type (primary, secondary, or indirect user). These factors possibly draw a nonlinear dynamic relationship over time.

Challenges Related to Customized Models
ISO-based models (González et al. 2012;La and Kim 2013;Lew, Olsina, and Zhang 2010;Oliveira et al. 2014;Orehovački et al. 2013;Orehovački 2011;Osman and Osman 2013) are rather incomplete and inherit the problems of the standard models. Many of them are specialized to certain quality applications: mobile-based applications (Alnanih, Ormandjieva, and Radhakrishnan 2014;La and Kim 2013;Osman and Osman 2013) or Web applications (González et al. 2012;Orehovački et al. 2013;Orehovački 2011). The strategic-based models are not yet mature (Alaa, Menshawi, and Saeed 2013;Hsu and Lee 2014) or incomplete (Becker, Lew, and Olsina 2012). The incompleteness is a result of using a subset of quality-in-use characteristics. These models, for example, do not consider risk mitigation nor context coverage characteristics. Paradigm-specific (Marinescu and Ratiu 2004;Wagner et al. 2012) models are programming language specific, thus limited. Hierarchical models (Dromey 1995;McCall, Richards, and Walters 1977) target the software product or process characteristics and do not suit software quality in use or require user involvement (Al-Qutaish 2010;Samadhiya, Wang, and Chen 2010). The usability-based models (Bačíková and Porubän 2014;Bond et al. 2014;Huang and Chiu 2014;Zheng et al. 2014) are domain specific and do not cover the complete definition of quality in use. This usually excludes freedom from risk and context coverage QinU characteristics. Extending such models might end up with something close to the ISO 25010 QinU model.
So what is a possible solution to these challenges? Next, a research direction based on natural language processing of software reviews is presented.

FUTURE RESEARCH DIRECTION
Modern Internet technology is an invaluable source of business information. For instance, the product reviews on social media sites composed collaboratively by many independent Internet reviewers through social media can help consumers make purchasing decisions and enable enterprises to improve their business strategies. Various studies show that online reviews have real economic value for the products they target (Ghose and Ipeirotis 2011).
Opinion mining or sentiment analysis is an emerging research direction of natural language processing that targets to analyze textual user judgments about products or services (Mei et al. 2007;Taboada et al. 2011). Reviews' text snippets are a good source for user decision making and a goldmine for a product's reputation. Analysis of reviews text manually is obviously hard. The average reader will have difficulty accurately summarizing relevant information and identifying opinions contained in reviews about a product. Moreover, human analysis of textual information is subject to considerable biases resulting from preferences and different understandings of written textual expressions.
Measuring software quality in use automatically from software reviews is challenging due to the anticipated complexity of designing an appropriate approach for a large volume of software reviews. As the number of reviews is increasing dramatically, going through product reviews can be a painful process and is usually laboriously lengthy.
Most of the time, product reviewing can be confusing. For example, comments like "I just don't like this product" and "The product took forever to be here" lack construc-tive expressions, as these comments are not targeted to the product. Thus, there is a limited human capability to produce consistent results. Therefore, opinion mining is needed to identify important reviews and opinions to answer users' queries (Qiu et al. 2009;Zhang, Xu, and Wan 2012).
A major task of opinion mining involves identifying and summarizing sentimental expressions (Duric and Song 2012;Lu, Zhai, and Sundaresan 2009;Zhang and Liu 2011).
Current opinion mining is restricted to reveal bipolarity of the reviews: positive and negative (Shein and Nyunt 2010;Turney 2002). In a bipolar approach under a voting mechanism, the qualities of evaluations are affected by imbalanced vote bias. Thus, there is a vital need for effective evaluation of product quality. Although there are studies reported to extend opinion mining to using a scaling system, they suffer the same predicament: determining the polarity of the review. The flaw with the polarity system is that the overall review can be easily tampered with because of the existing opinion spam. Furthermore, a truthful reviewing process should center on the efficiency and effectiveness of the product to users . The more fine-grain works are on feature or aspect-based sentiment analysis where it determines the opinions on the features of the reviewed entity such as a cell phone, tablet, and so on. However, this has the same problems mentioned previously, as it is difficult to identify relevant entities and polarity. In addition, the review may not focus on the entity itself. To the authors' knowledge, little research has been published in software reviews opinion mining. Mining software reviews can save users time and can help them in the software selection process, which is time consuming.
Despite the difficulties of the sentiment analysis approach, it can be used to overcome the issues discussed previously. Sentiment analysis can seemingly work on user reviews without active user involvement. So, future improvements to quality can be directed. Sentiment analysis has been applied in many domains such as movie reviews (Thet, Na, and Khoo 2010), customer reviews of electronic products (Hu and Liu 2004) or net-book computers (Brody and Elhadad 2010), services (Long, Zhang, and Zhut, 2010), and restaurants (Brody and Elhadad 2010;Ganu, Elhadad, and Marian 2009).
To the authors' knowledge, few works aim to resolve QinU problems systematically. Bond et al. (2014) proposed natural language processing (NLP) techniques to enhance user friendliness of electronic dictionaries. They used syntactic analysis, morphological analysis of inflection, and word formation to improve guidance of text produc-tion and access to lexical data. Leopairote, Surarerks, and Prompoon (2012) proposed a quality-in-use model based on software reviews. They proposed to seed an ontology with tokens extracted manually from the ISO 9126 document. Then the ontology was expanded with antonyms and synonyms using WordNet. Experts were used to map review sentences to the created ontology. Atoum and Bong (2014) proposed a framework to predict software quality in use from user reviews. Their work is based on using latent Dirichlet allocation (LDA) to identify important aspects of software quality in user reviews (Blei, Ng, and Jordan 2003;Blei and McAuliffe 2010). The framework employs opinion-feature double propagation to expand predefined lists of software quality-in-use features.

RELATED WORK
To the authors' knowledge little research has been conducted to identify problems in quality-in-use measurement. Most of the reviewed works are not rather comprehensive. Hirasawa (2013) identified several challenges in QinU management while incorporating quality in use for embedded systems' developments in Japan. The identified challenges relate to terminology disparity, system engineer capabilities, and lack of user process. He suggested implementing user requirements, understanding the outcome as a service rather than a product, and managing functional safety as part of quality in use. Bevan (2001; identified several barriers to qualityin-use measurement: 1) incomplete requirements, as user requirements are not taken into consideration early; 2) additional cost resulting from adding user activities and software and hardware requirements in the software life cycle; and 3) barriers resulting from the unclear definition of who should use the system and in which circumstances.

CONCLUSION
Quality in use represents software quality from a user's viewpoint. This article presents the major issues in measuring software quality in use. Quality in use can be measured using the standard SQuaRE series, while many characteristics of software quality in use are scattered in many customized software quality models.
Measuring quality in use is challenging due to the complexity of current standard models and the incompleteness of other related customized models. The viewpoint of software users is hard to implement within the software life cycle ahead of time, especially for hedonic tasks. Sentiment analysis is proposed to cope with these challenges.