A systematic review of software maintainability prediction and metrics

Riaz, Muhammad Sohail; Mendes, Emilia; Tempero, Ewan

doi:10.1109/esem.2009.5314233

Cited by 166 publications

(102 citation statements)

References 28 publications

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“…In the guidelines [3], it is suggested to extract the keywords also from the Comparison and Outcome, which is the common procedure in the field of medicine. However, as it stated also by Kitchenham in [14] and identified in other SLRs [15] and systematic mappings [11], this is not always applicable. For instance, it is applicable in SLRs when performing a comparison between two already known different approaches [3].…”

Section: Abstract Usedmentioning

confidence: 90%

Quality models for web services: A systematic mapping

Oriol

Marco

Franch

2014

Information and Software Technology

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Context: Quality of Service (QoS) is a major issue in various web service related activities. Quality models have been proposed as the engineering artefact to provide a common framework of understanding for QoS, by defining the quality factors that apply to web service usage. Objective: The goal of this study is to evaluate the current state of the art of the proposed quality models for web services, specifically: (1) which are these proposals and how are they related; (2) what are their structural characteristics; (3) what quality factors are the most and least addressed; and (4) what are their most consolidated definitions. Method: We have conducted a systematic mapping by defining a robust protocol that combines automatic and manual searches from different sources. We used a rigorous method to elicitate the keywords from the research questions and a selection criteria to retrieve the final papers to evaluate. We have adopted the ISO/IEC 25010 standard to articulate our analysis. Results: We have evaluated 47 different quality models from 65 papers that fulfilled the selection criteria. By analyzing in depth these quality models, we have: 1) distributed the proposals along the time dimension and identified their relationships; 2) analysed their size (visualizing the number of nodes and levels) and definition coverage (as indicator of quality of the proposals); 3) quantified the coverage of the different ISO/IEC 25010 quality factors by the proposals; 4) identified the quality factors that appeared in at least 30% of the surveyed proposals and provided the most consolidated definitions for them. Conclusions: We believe that this panoramic view on the anatomy of the quality models for web services may be a good reference for prospective researchers and practitioners in the field and especially may help avoiding the definition of new proposals that do not align with current research.

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Section: Abstract Usedmentioning

confidence: 90%

Quality models for web services: A systematic mapping

Oriol

Marco

Franch

2014

Information and Software Technology

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“…Other work has raised concerns about the value of such metrics in predicting design quality. Riaz et al's systematic review of maintenance prediction and metrics (Riaz et al 2009) found weaknesses in terms of comparison with expert opinion and external validity, as well as differences in the definition of maintenance used in the studies. Sjøberg et al found that a range of size, complexity, coupling, cohesion and inheritance metrics were not mutually consistent, and that only size and low cohesion were strongly associated with increased maintenance effort (Sjøberg et al 2012).…”

Section: Related Work 21 Software Design Qualitymentioning

confidence: 99%

Recognising object-oriented software design quality: a practitioner-based questionnaire survey

Stevenson

Wood

2017

Software Qual J

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Design quality is vital if software is to be maintainable. What practices do developers actually use to achieve design quality in their day-to-day work and which of these do they find most useful? To discover the extent to which practitioners concern themselves with object-oriented design quality and the approaches used when determining quality in practice, a questionnaire survey of 102 software practitioners, approximately half from the UK and the remainder from elsewhere around the world was used. Individual and peer experience are major contributors to design quality. Classic design guidelines, well-known lower level practices, tools and metrics all can also contribute positively to design quality. There is a potential relationship between testing practices and design quality. Inexperience, time pressures, novel problems, novel technology, and imprecise or changing requirements may have a negative impact on quality. Respondents with most experience are more confident in their design decisions, place more value on reviews by team leads and are more likely to rate design quality as very important. For practitioners, these results identify the techniques and tools that other practitioners find effective. For researchers, the results highlight a need for more work investigating the role of experience in the design process and the contribution experience makes to quality. There is also the potential for more in-depth studies of how practitioners are actually using design guidance, including Clean Code. Lastly, the potential relationship between testing practices and design quality merits further investigation.

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“…According to Riaz et al [22] the metric suites proposed by Li and Henry [15] and Chidamber and Kemerer [8] are the most accurate ones, while the model of van Koten and Gray [26] is the most stable one [22]. The metric suite that is used from the aforementioned study is presented in Table 1.…”

Section: Maintainability Predictorsmentioning

confidence: 99%

“…Also there is a vast literature on code metrics that affect the maintainability of software and consequently the corresponding effort required. According to Riaz et al [22] the metric suites proposed by Li and Henry [15] and Chidamber and Kemerer [8] are the most accurate ones for assessing software maintainability. On the other hand there are studies that explore the specific parameters that affect open source project development, quality and evolution [14], [20], [21].…”

Section: Related Workmentioning

confidence: 99%

A Bayesian Belief Network for Modeling Open Source Software Maintenance Productivity

Bibi

Ampatzoglou

Stamelos

2016

IFIP Advances in Information and Communication Technology

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Abstract. Maintenance is one of the most effort consuming activities in the software development lifecycle. Efficient maintenance within short release cycles depends highly on the underlying source code structure, in the sense that complex modules are more difficult to maintain. In this paper we attempt to unveil and discuss relationships between maintenance productivity, the structural quality of the source code and process metrics like the type of a release and the number of downloads. To achieve this goal, we developed a Bayesian Belief Network (BBN) involving several maintainability predictors and three managerial indices for maintenance (i.e., duration, production, and productivity) on 20 open source software projects. The results suggest that maintenance duration depends on inheritance, coupling, and process metrics. On the other hand maintenance production and productivity depend mostly on code quality metrics.

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A systematic review of software maintainability prediction and metrics

Cited by 166 publications

References 28 publications

Quality models for web services: A systematic mapping

Quality models for web services: A systematic mapping

Recognising object-oriented software design quality: a practitioner-based questionnaire survey

A Bayesian Belief Network for Modeling Open Source Software Maintenance Productivity

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