Metric and Tool Support for Instant Feedback of Source Code Readability

In the software maintenance phase, comprehending the legacy source code is inevitable, which consumes most of the time of the phase. The better the code is readable, the easier it is for code readers to comprehend the system based on the source code. This paper proposes an enhanced source code readability metric to quantitatively measure the extent of code readability. In addition, we developed a tool support named Instant R. Gauge to update the code on the fly based on the readability feedback of the current code. The tool also provides the history of the readability change so that developers recognize the more readable code and gradually change their coding habit without any annoying advice. The suggested readability metric achieves 75.74% of explanatory power, and our experiment showed that readability of most of the methods authored in our tool is higher than that of the methods without our approach

Taxonomy of Software Readability Changes

Software readability has emerged as an important software quality metric. Numerous pieces of research have highlighted the importance of readability. Developers generally spend a large amount of their time reading and understanding existing code, rather than writing new code. By creating more readable code, engineers can limit the mental load required to understand specific code segments. With this importance established, research has been done into how to improve software readability. This research looked for ways of measuring readability, how to create more readable software, and how to potentially improve readability. While some research has examined the changes developers make, their use of automatic source code analysis may miss some aspects of these changes. As such, this study conducted a manual review of software readability commits to identify what changes developers tend to make. In this study, we identified 1,782 potential readability commits for 800 open-source Java projects, by mining keyword patterns in commit messages. These commits were then reviewed by human reviewers to identify the changes made by the developers. The observations made by the reviewers were then reviewed for trends, from which several categories would be established. These categories would be further reviewed for additional trends, developing a taxonomy of readability changes. Overall, this research looked at 314 changes from 194 commits across 154 unique projects. This study shows the developers’ actions when improving software readability, identifying the common trends of method extraction, identifier renaming, and code formatting, supported by existing research. In addition, this research presents less observed trends, such as code removal or keyword modification, which were changes not seen in other research. Overall, this work provides a taxonomy of the trends seen, identifying high level trends as well as subgroups within those trends

A SOFTWARE LIBRARY FOR MEASUREMENT OF READABILITY OF TEXTS AND A NEW READABILITY METRIC FOR TURKISH

Bu makalede, Doğal Dil İşleme (DDİ)‟nin bir konusu olan okunabilirlik kavramı ve kullanım alanları ele alınmıştır. İngilizce için tanımlanmış olan ve günümüzde farklı alanlarda kullanılan, birbirinden farklı niceliklerle oluşturulmuş okunabilirlik ölçütleri incelenmiştir. Sözkonusu formüllerin Türkçe için uygunlukları ve uyarlanabilirlikleri, geliştirilen bir yazılım kütüphanesi ile farklı türlerde ve seviyelerdeki Türkçe kitap metinleri kullanılarak incelenmiştir. Ayrıca, Türkçe‟nin bir takım istatistiksel özellikleri belirlenerek Türkçe için yeni bir okunabilirlik ölçütü formülü önerilmiştir. C programlama dilinde geliştirilen ve platform bağımsız olarak kullanılabilen söz konusu kütüphanenin, bu konuda çalışacak araştırmacılara bir kaynak olacağı; önerilen okunabilirlik ölçütünün de Türkçe metinlerin seviyesi hakkında fikir vermesi açısından yaygın kullanım alanı bulabileceği öngörülmektedir. In this article, as a matter of Natural Language Processing, the concept of readability and its possible areas of application have been considered. Readability metrics, which have so far been defined for English by considering different aspects and used in different areas, are investigated quantitatively. Eligibility and applicability of the existing metrics for Turkish have been analyzed via Turkish books of various types and levels by means of a software library developed by ourselves. In addition, statistical characteristics of Turkish were determined and a new readability formula for Turkish is proposed. Being developed with the C programming language with the main feature of platform independency, the software library is expected to serve as a resource for the upcoming researches in this topic; meanwhile the proposed readability metric is expected to find wide application area for prediction of the readability levels of Turkish texts

Evaluating readability as a factor in information security policies

Researchers have designed a number of software readability metrics that evaluate how difficult a passage is to comprehend; yet, little is known about the impact of readability on the interpretation of information security policies (ISPs) and whether experiment of readability may prove to be a useful factor. This paper examines and compares eight ISP documents on nine mechanical readability formula results with outcomes from a human-based comprehension test. The primary focus is to identify if we might rely on a software readability measure for assessing the difficulty of a text document in the domain of Information Security Policies. Our results reveal that traditional readability metrics are ineffective in predicting the human estimation. Nevertheless, readability, as measured using a bespoke readability metric, may yield useful insight upon the likely difficulty that end-users face in comprehending an ISP document. Thereby, our study aims to provide a means to enhance the comprehensibility of ISPs

Assessing the usability of two declarative programming languages to model geometric events

When space missions plan scientific actions for robotic spacecraft to execute, they frequently do so within a geometric context called an opportunity. Although there are geometric software libraries that let users write code to search for opportunities, they require knowledge of algorithms and imperative programming languages, which is a condition that might exclude a potentially large population of scientists. Additionally, there might be more user-friendly software systems for scientists to model and search for opportunities, but those might exclude other missions due to export concerns or an inability to maintain such software due to lack of staff or funding. To address these concerns, we designed two different computer languages to model opportunities. In this paper, we present these two languages, our study to evaluate their relative readability and usability, and results obtained in our research along with an interpretation of the same. The metric for this study has been a questionnaire with active exercises, statements with corresponding responses on a Likert scale, and open-ended questions to elicit qualitative responses. The study’s quantitative results provide us with relative and absolute quantification of the usability and readability of each language, while the study’s qualitative results help us direct future language design decisions.Peer ReviewedPostprint (author's final draft

Evaluating readability as a factor in information security policies

This thesis was previously held under moratorium from 26/11/19 to 26/11/21Policies should be treated as rules or principles that individuals can readily comprehend and follow as a pre-requisite to any organisational requirement to obey and enact regulations. This dissertation attempts to highlight one of the important factors to consider before issuing any policy that staff members are required to follow. Presently, there is no ready mechanism for estimating the likely efficacy of such policies across an organisation. One factor that has a plausible impact upon the comprehensibility of policies is their readability. Researchers have designed a number of software readability metrics that evaluate how difficult a passage is to comprehend; yet, little is known about the impact of readability on the interpretation of information security policies and whether analysis of readability may prove to be a useful insight. This thesis describes the first study to investigate the feasibility of applying readability metrics as an indicator of policy comprehensibility through a mixed methods approach, with the formulation and implementation of a seven phase sequential exploratory fully mixed methods design. Each one was established in light of the outcomes from the previous phase. The methodological approach of this research study is one of the distinguishing characteristics reported in the thesis, which was as follows: * eight policies were selected (from a combination of academia and industry sector institutes); * specialists were requested their insights on key policy elements; * focus group interviews were conducted; * comprehension tests were developed (Cloze tests); * a pilot study of comprehension tests was organised (preceded by a small-scale test); * a main study of comprehension tests was performed with 600 participants and reduce that for validation to 396; * a comparison was made of comprehension results against readability metrics. The results reveal that the traditional readability metrics are ineffective in predicting human estimation. Nevertheless, readability, as measured using a bespoke readability metric, may yield useful insight upon the likely difficulty that end-users may face in comprehending a written text. Thereby, our study aims to provide an effective approach to enhancing the comprehensibility of information security policies and afford a facility for future research in this area. The research contributes to our understanding of readability in general and offering an optimal technique to measure the readability in particular. We recommend immediate corrective actions to enhance the ease of comprehension for information security policies. In part, this may reduce instances where users avoid fully reading the information security policies, and may also increase the likelihood of user compliance. We suggest that the application of appropriately selected readability assessment may assist policy makers to test their draft policies for ease of comprehension before policy release. Indeed, there may be grounds for a readability compliance test that future information security policies must satisfy.Policies should be treated as rules or principles that individuals can readily comprehend and follow as a pre-requisite to any organisational requirement to obey and enact regulations. This dissertation attempts to highlight one of the important factors to consider before issuing any policy that staff members are required to follow. Presently, there is no ready mechanism for estimating the likely efficacy of such policies across an organisation. One factor that has a plausible impact upon the comprehensibility of policies is their readability. Researchers have designed a number of software readability metrics that evaluate how difficult a passage is to comprehend; yet, little is known about the impact of readability on the interpretation of information security policies and whether analysis of readability may prove to be a useful insight. This thesis describes the first study to investigate the feasibility of applying readability metrics as an indicator of policy comprehensibility through a mixed methods approach, with the formulation and implementation of a seven phase sequential exploratory fully mixed methods design. Each one was established in light of the outcomes from the previous phase. The methodological approach of this research study is one of the distinguishing characteristics reported in the thesis, which was as follows: * eight policies were selected (from a combination of academia and industry sector institutes); * specialists were requested their insights on key policy elements; * focus group interviews were conducted; * comprehension tests were developed (Cloze tests); * a pilot study of comprehension tests was organised (preceded by a small-scale test); * a main study of comprehension tests was performed with 600 participants and reduce that for validation to 396; * a comparison was made of comprehension results against readability metrics. The results reveal that the traditional readability metrics are ineffective in predicting human estimation. Nevertheless, readability, as measured using a bespoke readability metric, may yield useful insight upon the likely difficulty that end-users may face in comprehending a written text. Thereby, our study aims to provide an effective approach to enhancing the comprehensibility of information security policies and afford a facility for future research in this area. The research contributes to our understanding of readability in general and offering an optimal technique to measure the readability in particular. We recommend immediate corrective actions to enhance the ease of comprehension for information security policies. In part, this may reduce instances where users avoid fully reading the information security policies, and may also increase the likelihood of user compliance. We suggest that the application of appropriately selected readability assessment may assist policy makers to test their draft policies for ease of comprehension before policy release. Indeed, there may be grounds for a readability compliance test that future information security policies must satisfy

A Topic-Agnostic Approach for Identifying Fake News Pages

Fake news and misinformation have been increasingly used to manipulate popular opinion and influence political processes. To better understand fake news, how they are propagated, and how to counter their effect, it is necessary to first identify them. Recently, approaches have been proposed to automatically classify articles as fake based on their content. An important challenge for these approaches comes from the dynamic nature of news: as new political events are covered, topics and discourse constantly change and thus, a classifier trained using content from articles published at a given time is likely to become ineffective in the future. To address this challenge, we propose a topic-agnostic (TAG) classification strategy that uses linguistic and web-markup features to identify fake news pages. We report experimental results using multiple data sets which show that our approach attains high accuracy in the identification of fake news, even as topics evolve over time.Comment: Accepted for publication in the Companion Proceedings of the 2019 World Wide Web Conference (WWW'19 Companion). Presented in the 2019 International Workshop on Misinformation, Computational Fact-Checking and Credible Web (MisinfoWorkshop2019). 6 page

Estimating readability with the Strathclyde readability measure

Despite their significant limitations, readability measures that are easy to apply have definite appeal. With this in mind, we have been exploring the prospects for more insightful measures that are computer-based and, thereby, still easily applied. The orthodox reliance on intrinsic syntactic features is an inherent limitation of most readability measures, since they have no reference to the likelihood that readers will be acquainted with the constituent words and phrases. To accommodate this feature of 'human familiarity', we have devised a metric that combines traditional factors, such as Average Sentence Length, with a measure of word 'commonality' based upon word frequency. This paper details the derivation, nature and application of the Strathclyde Readability Measure (SRM)