Towards Resolving Software Quality-in-Use Measurement Challenges

Software quality-in-use comprehends the quality from user’s perspectives. It has gained its importance in e-learning applications, mobile service based applications and project management tools. User’s decisions on software acquisitions are often ad hoc or based on preference due to difficulty in quantitatively measure software quality-in-use. However, why qualityin- use measurement is difficult? Although there are many software quality models to our knowledge, no works surveys the challenges related to software quality-in-use measurement. This paper has two main contributions; 1) presents major issues and challenges in measuring software quality-in-use in the context of the ISO SQuaRE series and related software quality models, 2) Presents a novel framework that can be used to predict software quality-in-use, and 3) presents preliminary results of quality-in-use topic prediction. Concisely, the issues are related to the complexity of the current standard models and the limitations and incompleteness of the customized software quality models. The proposed framework employs sentiment analysis techniques to predict software quality-in-use

Towards the integration and development of a cross-European research network and infrastructure:the DEterminants of DIet and Physical ACtivity (DEDIPAC) Knowledge Hub

To address major societal challenges and enhance cooperation in research across Europe, the European Commission has initiated and facilitated ‘joint programming’. Joint programming is a process by which Member States engage in defining, developing and implementing a common strategic research agenda, based on a shared vision of how to address major societal challenges that no Member State is capable of resolving independently. Setting up a Joint Programming Initiative (JPI) should also contribute to avoiding unnecessary overlap and repetition of research, and enable and enhance the development and use of standardised research methods, procedures and data management. The Determinants of Diet and Physical Activity (DEDIPAC) Knowledge Hub (KH) is the first act of the European JPI ‘A Healthy Diet for a Healthy Life’. The objective of DEDIPAC is to contribute to improving understanding of the determinants of dietary, physical activity and sedentary behaviours. DEDIPAC KH is a multi-disciplinary consortium of 46 consortia and organisations supported by joint programming grants from 12 countries across Europe. The work is divided into three thematic areas: (I) assessment and harmonisation of methods for future research, surveillance and monitoring, and for evaluation of interventions and policies; (II) determinants of dietary, physical activity and sedentary behaviours across the life course and in vulnerable groups; and (III) evaluation and benchmarking of public health and policy interventions aimed at improving dietary, physical activity and sedentary behaviours. In the first three years, DEDIPAC KH will organise, develop, share and harmonise expertise, methods, measures, data and other infrastructure. This should further European research and improve the broad multi-disciplinary approach needed to study the interactions between multilevel determinants in influencing dietary, physical activity and sedentary behaviours. Insights will be translated into more effective interventions and policies for the promotion of healthier behaviours and more effective monitoring and evaluation of the impacts of such intervention

Analysis and Detection of Information Types of Open Source Software Issue Discussions

Most modern Issue Tracking Systems (ITSs) for open source software (OSS) projects allow users to add comments to issues. Over time, these comments accumulate into discussion threads embedded with rich information about the software project, which can potentially satisfy the diverse needs of OSS stakeholders. However, discovering and retrieving relevant information from the discussion threads is a challenging task, especially when the discussions are lengthy and the number of issues in ITSs are vast. In this paper, we address this challenge by identifying the information types presented in OSS issue discussions. Through qualitative content analysis of 15 complex issue threads across three projects hosted on GitHub, we uncovered 16 information types and created a labeled corpus containing 4656 sentences. Our investigation of supervised, automated classification techniques indicated that, when prior knowledge about the issue is available, Random Forest can effectively detect most sentence types using conversational features such as the sentence length and its position. When classifying sentences from new issues, Logistic Regression can yield satisfactory performance using textual features for certain information types, while falling short on others. Our work represents a nontrivial first step towards tools and techniques for identifying and obtaining the rich information recorded in the ITSs to support various software engineering activities and to satisfy the diverse needs of OSS stakeholders.Comment: 41st ACM/IEEE International Conference on Software Engineering (ICSE2019

Exploiting a Goal-Decomposition Technique to Prioritize Non-functional Requirements

Business stakeholders need to have clear and realistic goals if they want to meet commitments in application development. As a consequence, at early stages they prioritize requirements. However, requirements do change. The effect of change forces the stakeholders to balance alternatives and reprioritize requirements accordingly. In this paper we discuss the problem of priorities to non-functional requirements subjected to change. We, then, propose an approach to help smooth the impact of such changes. Our approach favors the translation of nonoperational specifications into operational definitions that can be evaluated once the system is developed. It uses the goal-question-metric method as the major support to decompose non-operational specifications into operational ones. We claim that the effort invested in operationalizing NFRs helps dealing with changing requirements during system development. Based on\ud this transformation and in our experience, we provide guidelines to prioritize volatile non-functional requirements

The Wide Integral Field Infrared Spectrograph: Commissioning Results and On-sky Performance

We have recently commissioned a novel infrared ($0.9-1.7$ $\mu$m) integral field spectrograph (IFS) called the Wide Integral Field Infrared Spectrograph (WIFIS). WIFIS is a unique instrument that offers a very large field-of-view (50$^{\prime\prime}$ x 20$^{\prime\prime}$) on the 2.3-meter Bok telescope at Kitt Peak, USA for seeing-limited observations at moderate spectral resolving power. The measured spatial sampling scale is $\sim1\times1^{\prime\prime}$ and its spectral resolving power is $R\sim2,500$ and $3,000$ in the $zJ$ ($0.9-1.35$ $\mu$m) and $H_{short}$ ($1.5-1.7$ $\mu$m) modes, respectively. WIFIS's corresponding etendue is larger than existing near-infrared (NIR) IFSes, which are mostly designed to work with adaptive optics systems and therefore have very narrow fields. For this reason, this instrument is specifically suited for studying very extended objects in the near-infrared such as supernovae remnants, galactic star forming regions, and nearby galaxies, which are not easily accessible by other NIR IFSes. This enables scientific programs that were not originally possible, such as detailed surveys of a large number of nearby galaxies or a full accounting of nucleosynthetic yields of Milky Way supernova remnants. WIFIS is also designed to be easily adaptable to be used with larger telescopes. In this paper, we report on the overall performance characteristics of the instrument, which were measured during our commissioning runs in the second half of 2017. We present measurements of spectral resolving power, image quality, instrumental background, and overall efficiency and sensitivity of WIFIS and compare them with our design expectations. Finally, we present a few example observations that demonstrate WIFIS's full capability to carry out infrared imaging spectroscopy of extended objects, which is enabled by our custom data reduction pipeline.Comment: Published in the Proceedings of SPIE Astronomical Telescopes and Instrumentation 2018. 17 pages, 13 figure

Scaffolding Reflection: Prompting Social Constructive Metacognitive Activity in Non-Formal Learning

The study explores the effects of three different types of non-adaptive, metacognitive scaffolding on social, constructive metacognitive activity and reflection in groups of non-formal learners. Six triads of non-formal learners were assigned randomly to one of the three scaffolding conditions: structuring, problematising or epistemological. The triads were then asked to collaboratively resolve an ill-structured problem and record their deliberations. Evidence from think-aloud protocols was analysed using conversational and discourse analysis. Findings indicate that epistemological scaffolds produced more social, constructive metacognitive activity than either of the two other scaffolding conditions in all metacognitive activities except for task orientation, as well as higher quality interactions during evaluation and reflection phases. However, participants appeared to be less aware of their activities as forming a strategic, self-regulatory response to the problem. This may indicate that for learning transfer, it may be necessary to employ an adaptive, facilitated reflection on learners' activities