A non-invasive approach to product metrics collection

Scotto, Marco; Sillitti, Alberto; Succi, Giancarlo; Vernazza, Tullio

doi:10.1016/j.sysarc.2006.06.010

Cited by 66 publications

(21 citation statements)

References 14 publications

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“…In the future we intend to adopt a systematic approach to evaluate the maturity of parsers, e. g., using the Open Maturity Model [30] or automatic measurement techniques [31,32].…”

Section: Discussionmentioning

confidence: 99%

How to Calculate Software Metrics for Multiple Languages Using Open Source Parsers

Janes

Piatov

Sillitti

et al. 2013

Open Source Software: Quality Verification

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Abstract. Source code metrics help to evaluate the quality of the code, for example, to detect the most complex parts of the program. When writing a system which calculates metrics, especially when it has to support multiple source code languages, the biggest problem which arises is the creation of parsers for each supported language. In this paper we suggest an unusual Open Source solution, that avoids creating such parsers from scratch. We suggest and explain how to use parsers contained in the Eclipse IDE as parsers that support contemporary language features, are actively maintained, can recover from errors, and provide not just the abstract syntax tree, but the whole type information of the source program. The findings described in this paper provide to practitioners a way to use Open Source parsers without the need to deal with parser generators, or to write a parser from scratch.

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“…In the future we intend to adopt a systematic approach to evaluate the maturity of parsers, e. g., using the Open Maturity Model [30] or automatic measurement techniques [31,32].…”

Section: Discussionmentioning

confidence: 99%

How to Calculate Software Metrics for Multiple Languages Using Open Source Parsers

Janes

Piatov

Sillitti

et al. 2013

Open Source Software: Quality Verification

Self Cite

View full text Add to dashboard Cite

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“…To validate our approach, we will deploy an experiment consisting on the retrieval of a sample of assorted mobile applications from Google Play (Android OS market) and calculating from them the mobile software quality metrics defined the GQM. An automatic evaluation effort will be done using a noninvasive measurement framework able to analyze the source code and compute user-defined metrics [7,8]. This will let us execute a multi-dimensional evaluation of the code without adding human-operator bias.…”

Section: Evaluation Methodologymentioning

confidence: 99%

Standard-based strategy to assure the quality of the mobile software product

Corral

2012

Proceedings of the 3rd Annual Conference on Systems, Programming, and Applications: Software for Humanity

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The high relevance gained by mobile software applications, the large number of users, and the growing development competition, trigger a need for a method to measure and track the quality of mobile software products from a domain-specific, quantitative point of view. We pursue the implementation of a strategy to extend software quality standards to supply mechanisms to measure the quality of mobile software products, for developers to have a wellfounded understanding of whether their applications meet the market's demands and user expectations. MotivationThe impact of the mobile software product grows every day, reaching a point in which mobile devices become one of the most important platforms for the distribution and utilization of user-oriented software. Mobile application stores are a primary channel for the dissemination of enduser software products, hosting thousands of apps, and reporting millions of downloads per day. Smartphones are driven by powerful operating systems that allow users to add and remove applications employing an architecture that is similar to a regular personal computer. However, these applications have to cope with several constraints inherent to the mobile ecosystem, not present in conventional desktop computing. In consequence, the quality of the mobile software product is driven by the conjunction of the traditional software quality characteristics with additional factors. The quality of mobile applications is usually regulated by application market policies, and may also be communicated via customer's ratings and reviews. However, currently it has not been established a link between the quality goals posed on mobile applications, and specific characteristics that can be measured to determine the fulfillment of those quality goals quantitatively. Developers should have a solid understanding about whether their apps meet market demands and users' expectations, and they would benefit from knowing how a successful app was designed. Research ProblemMobile software engineers should put in practice a development strategy that considers several quality drivers: the mobile environment itself, the expectations of the end-user, and the restrictions set by application markets. After releasing a product, software developers may obtain an indirect quality appraisal from these drivers; for example, if their products are compliant with the market guidelines, they will be included in the application store; if their products satisfy customer expectations, they will receive positive reviews and high ratings. Several software development processes have been proposed to guide software engineers to produce high-quality mobile applications. These development processes are typically based on Agile methods, claiming that this approach is the most effective way to address the diverse and evolving requirements of the mobile environment [1][2][3]. Nevertheless, none of these lifecycles provide an appraisal model that delivers goals, methods and metrics to directly assess the software product in light of the c...

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“…Data are extracted from a non-invasive measurement tool, PROM (PRO Metrics) [4]. It collects process metrics by using plug-ins for mass-market applications such as office automation suites, software development tools, etc.…”

Section: Architecturementioning

confidence: 99%