Open source tools for measuring the Internal Quality of Java software products. A survey

Collecting metrics and indicators to assess objectively the different products resulting during the lifecycle of a software project is a research area that encompasses many different aspects, apart from being highly demanded by companies and software development teams. Focusing on software products, one of the most used methods by development teams for measuring Internal Quality is the static analysis of the source code. This paper works in this line and presents a study of the stateof- the-art open source software tools that automate the collection of these metrics, particularly for developments in Java. These tools have been compared according to certain criteria defined in this study.Ministerio de Ciencia e Innovación TIN2010-20057-C03-02Junta de Andalucía TIC-578

Software Measurement Activities in Small and Medium Enterprises: an Empirical Assessment

An empirical study for evaluating the proper implementation of measurement/metric programs in software companies in one area of Turkey is presented. The research questions are discussed and validated with the help of senior software managers (more than 15 years’ experience) and then used for interviewing a variety of medium and small scale software companies in Ankara. Observations show that there is a common reluctance/lack of interest in utilizing measurements/metrics despite the fact that they are well known in the industry. A side product of this research is that internationally recognized standards such as ISO and CMMI are pursued if they are a part of project/job requirements; without these requirements, introducing those standards to the companies remains as a long-term target to increase quality

Mutation testing on an object-oriented framework: An experience report

This is the preprint version of the article - Copyright @ 2011 ElsevierContext The increasing presence of Object-Oriented (OO) programs in industrial systems is progressively drawing the attention of mutation researchers toward this paradigm. However, while the number of research contributions in this topic is plentiful, the number of empirical results is still marginal and mostly provided by researchers rather than practitioners. Objective This article reports our experience using mutation testing to measure the effectiveness of an automated test data generator from a user perspective. Method In our study, we applied both traditional and class-level mutation operators to FaMa, an open source Java framework currently being used for research and commercial purposes. We also compared and contrasted our results with the data obtained from some motivating faults found in the literature and two real tools for the analysis of feature models, FaMa and SPLOT. Results Our results are summarized in a number of lessons learned supporting previous isolated results as well as new findings that hopefully will motivate further research in the field. Conclusion We conclude that mutation testing is an effective and affordable technique to measure the effectiveness of test mechanisms in OO systems. We found, however, several practical limitations in current tool support that should be addressed to facilitate the work of testers. We also missed specific techniques and tools to apply mutation testing at the system level.This work has been partially supported by the European Commission (FEDER) and Spanish Government under CICYT Project SETI (TIN2009-07366) and the Andalusian Government Projects ISABEL (TIC-2533) and THEOS (TIC-5906)

SCCharts: The Mindstorms Report

SCCharts are a visual language proposed in 2012 for specifying safety-critical reactive systems. This is the second SCCharts report towards the usability of the SCCharts visual language and its KIELER SCCharts implementation. KIELER is an open-source project which researches the pragmatics of model-based languages and related fields. Nine case-studies that were conducted between 2015 and 2019 evaluate the pros and cons in the context of small-scale Lego Mindstorms models and similar projects. Par-ticipants of the studies included undergraduate and graduate students from our local and also external facilities, as well as academics from the synchronous community. In the surveys, both the SCCharts language and the SCCharts tools are compared to other modeling and classical programming languages and tools

Social media analytics: a survey of techniques, tools and platforms

This paper is written for (social science) researchers seeking to analyze the wealth of social media now available. It presents a comprehensive review of software tools for social networking media, wikis, really simple syndication feeds, blogs, newsgroups, chat and news feeds. For completeness, it also includes introductions to social media scraping, storage, data cleaning and sentiment analysis. Although principally a review, the paper also provides a methodology and a critique of social media tools. Analyzing social media, in particular Twitter feeds for sentiment analysis, has become a major research and business activity due to the availability of web-based application programming interfaces (APIs) provided by Twitter, Facebook and News services. This has led to an ‘explosion’ of data services, software tools for scraping and analysis and social media analytics platforms. It is also a research area undergoing rapid change and evolution due to commercial pressures and the potential for using social media data for computational (social science) research. Using a simple taxonomy, this paper provides a review of leading software tools and how to use them to scrape, cleanse and analyze the spectrum of social media. In addition, it discussed the requirement of an experimental computational environment for social media research and presents as an illustration the system architecture of a social media (analytics) platform built by University College London. The principal contribution of this paper is to provide an overview (including code fragments) for scientists seeking to utilize social media scraping and analytics either in their research or business. The data retrieval techniques that are presented in this paper are valid at the time of writing this paper (June 2014), but they are subject to change since social media data scraping APIs are rapidly changing