5,111 research outputs found

    A Quality Model for Actionable Analytics in Rapid Software Development

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    Background: Accessing relevant data on the product, process, and usage perspectives of software as well as integrating and analyzing such data is crucial for getting reliable and timely actionable insights aimed at continuously managing software quality in Rapid Software Development (RSD). In this context, several software analytics tools have been developed in recent years. However, there is a lack of explainable software analytics that software practitioners trust. Aims: We aimed at creating a quality model (called Q-Rapids quality model) for actionable analytics in RSD, implementing it, and evaluating its understandability and relevance. Method: We performed workshops at four companies in order to determine relevant metrics as well as product and process factors. We also elicited how these metrics and factors are used and interpreted by practitioners when making decisions in RSD. We specified the Q-Rapids quality model by comparing and integrating the results of the four workshops. Then we implemented the Q-Rapids tool to support the usage of the Q-Rapids quality model as well as the gathering, integration, and analysis of the required data. Afterwards we installed the Q-Rapids tool in the four companies and performed semi-structured interviews with eight product owners to evaluate the understandability and relevance of the Q-Rapids quality model. Results: The participants of the evaluation perceived the metrics as well as the product and process factors of the Q-Rapids quality model as understandable. Also, they considered the Q-Rapids quality model relevant for identifying product and process deficiencies (e.g., blocking code situations). Conclusions: By means of heterogeneous data sources, the Q-Rapids quality model enables detecting problems that take more time to find manually and adds transparency among the perspectives of system, process, and usage.Comment: This is an Author's Accepted Manuscript of a paper to be published by IEEE in the 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA) 2018. The final authenticated version will be available onlin

    A research review of quality assessment for software

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    Measures were recommended to assess the quality of software submitted to the AdaNet program. The quality factors that are important to software reuse are explored and methods of evaluating those factors are discussed. Quality factors important to software reuse are: correctness, reliability, verifiability, understandability, modifiability, and certifiability. Certifiability is included because the documentation of many factors about a software component such as its efficiency, portability, and development history, constitute a class for factors important to some users, not important at all to other, and impossible for AdaNet to distinguish between a priori. The quality factors may be assessed in different ways. There are a few quantitative measures which have been shown to indicate software quality. However, it is believed that there exists many factors that indicate quality and have not been empirically validated due to their subjective nature. These subjective factors are characterized by the way in which they support the software engineering principles of abstraction, information hiding, modularity, localization, confirmability, uniformity, and completeness

    An overview of process model quality literature - The Comprehensive Process Model Quality Framework

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    The rising interest in the construction and the quality of (business) process models resulted in an abundancy of emerged research studies and different findings about process model quality. The lack of overview and the lack of consensus hinder the development of the research field. The research objective is to collect, analyse, structure, and integrate the existing knowledge in a comprehensive framework that strives to find a balance between completeness and relevance without hindering the overview. The Systematic Literature Review methodology was applied to collect the relevant studies. Because several studies exist that each partially addresses this research objective, the review was performed at a tertiary level. Based on a critical analysis of the collected papers, a comprehensive, but structured overview of the state of the art in the field was composed. The existing academic knowledge about process model quality was carefully integrated and structured into the Comprehensive Process Model Quality Framework (CPMQF). The framework summarizes 39 quality dimensions, 21 quality metrics, 28 quality (sub)drivers, 44 (sub)driver metrics, 64 realization initiatives and 15 concrete process model purposes related to 4 types of organizational benefits, as well as the relations between all of these. This overview is thus considered to form a valuable instrument for both researchers and practitioners that are concerned about process model quality. The framework is the first to address the concept of process model quality in such a comprehensive way

    Analyzing the Importance of Learnability and Understandability Quality Attributes in Reference to SPL Feature Models

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    The modeling foundation of SPL is promoting software reuse by segregation of variant features of all the products whi ch belong to a family. The analysis of various quality attribute s is very important in reference to SPL feature models. Identifying whether a feature model is easy to use and learn will help develop a successful product line. Two important quality sub factors of usability i.e. understandability and communicativeness play a great role in development of successful product line feature model. If the understanding of any feature model is low, it will result in lesser use of that feature model. Same applies to communicativeness , the more the communicativeness of a feature model, the more the usability. In other words, the successful reuse of any feature model will depend on the degree of its understa nding and communicativeness. C urrent analysis methods usually focus only on functional requirements of the product lines and do not focus on product quality. Whereas, non functional requirement s like maintainability, dependability and usability etc are essential dimensions of variability. This paper is intended to study the role of understandability and communicativeness over feature models. It also throws light on t he effect of these quality su b factors on SPL feature models and suggests ways to improve their degr

    IDENTIFICATION AND QUANTIFICATION OF VARIABILITY MEASURES AFFECTING CODE REUSABILITY IN OPEN SOURCE ENVIRONMENT

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    Open source software (OSS) is one of the emerging areas in software engineering, and is gaining the interest of the software development community. OSS was started as a movement, and for many years software developers contributed to it as their hobby (non commercial purpose). Now, OSS components are being reused in CBSD (commercial purpose). However, recently, the use of OSS in SPL is envisioned recently by software engineering researchers, thus bringing it into a new arena. Being an emerging research area, it demands exploratory study to explore the dimensions of this phenomenon. Furthermore, there is a need to assess the reusability of OSS which is the focal point of these disciplines (CBSE, SPL, and OSS). In this research, a mixed method based approach is employed which is specifically 'partially mixed sequential dominant study'. It involves both qualitative (interviews) and quantitative phases (survey and experiment). During the qualitative phase seven respondents were involved, sample size of survey was 396, and three experiments were conducted. The main contribution of this study is results of exploration of the phenomenon 'reuse of OSS in reuse intensive software development'. The findings include 7 categories and 39 dimensions. One of the dimension factors affecting reusability was carried to the quantitative phase (survey and experiment). On basis of the findings, proposal for reusability attribute model was presented at class and package level. Variability is one of the newly identified attribute of reusability. A comprehensive theoretical analysis of variability implementation mechanisms is conducted to propose metrics for its assessment. The reusability attribute model is validated by statistical analysis of I 03 classes and 77 packages. An evolutionary reusability analysis of two open source software was conducted, where different versions of software are analyzed for their reusability. The results show a positive correlation between variability and reusability at package level and validate the other identified attributes. The results would be helpful to conduct further studies in this area

    Weighted Class Complexity: A Measure of Complexity for Object Oriented System

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    Software complexity metrics are used to predict critical information about reliability and maintainability of software systems. Object oriented software development requires a different approach to software complexity metrics. In this paper, we propose a metric to compute the structural and cognitive complexity of class by associating a weight to the class, called as Weighted Class Complexity (WCC). On the contrary, of the other metrics used for object oriented systems, proposed metric calculates the complexity of a class due to methods and attributes in terms of cognitive weight. The proposed metric has been demonstrated with OO examples. The theoretical and practical evaluations based on the information theory have shown that the proposed metric is on ratio scale and satisfies most of the parameters required by the measurement theor

    On the role of pre and post-processing in environmental data mining

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    The quality of discovered knowledge is highly depending on data quality. Unfortunately real data use to contain noise, uncertainty, errors, redundancies or even irrelevant information. The more complex is the reality to be analyzed, the higher the risk of getting low quality data. Knowledge Discovery from Databases (KDD) offers a global framework to prepare data in the right form to perform correct analyses. On the other hand, the quality of decisions taken upon KDD results, depend not only on the quality of the results themselves, but on the capacity of the system to communicate those results in an understandable form. Environmental systems are particularly complex and environmental users particularly require clarity in their results. In this paper some details about how this can be achieved are provided. The role of the pre and post processing in the whole process of Knowledge Discovery in environmental systems is discussed

    Automatically assessing and improving code readability and understandability

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    Proposal and Validation of Usability Model for Component Based Software System

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    Increasing demand of rapid and cost effective development of software system has increased the demand of Component Based Software Engineering (CBSE). In CBSE, software system is developed by using existing components. These components can be in-house components or third party components. To develop a Component Based Software System (CBSS), it is important to select the suitable component in such a manner that the components of the software system do not affect each other. To increase the acceptance of the CBSS among the users and the market value of the software industries, it is important to increase the usability of the CBSS. Several usability models have been proposed for traditional and object-oriented software system (OOSS), but there is no usability model for CBSS. Existing traditional and object-oriented models can’t be perfectly suitable for CBSS because of the unique characteristics of the components. This paper presents a usability model (UMCBSS) for CBSS. The proposed usability model is based on most significant usability factors. These factors are analysed from CBSS quality models. With the help of proposed model, usability is evaluated by using two different techniques i.e., centroid method and bisector method in MATLAB. Experimental results are also validated by using Center of Gravity (COG) and Mean-Max method. With the help of the proposed model, developers of the CBSS will be able to measure the usability of CBSS and to remove the usability flaws from the software system
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