Zahra Shakeri Hossein Abad

Multi Surface Interactions with Geospatial Data: A Systematic Review

Even though Multi Surface Environments (MSE) and how to perform interactions in these environments have received much attention during recent years, interaction with geospatial data in these environments is still limited, and there are many design and interaction issues that need to be addressed. Alongside the rapid rise in the use of Geographic Information Systems (GIS) in group-based decision making, interaction with geospatial data has become highly important. In order to summarize the earlier research in this area, this paper presents a systematic review of MSE interactions with geospatial data; analyzing the existing studies on MSE interaction techniques, discussing issues related to interaction with geospatial data in MSEs and providing a comparison between common GIS tasks and existing interaction techniques in MSEs. Our results indicate that a substantial number of GIS tasks have not been investigated in MSEs.

Requirements Engineering Visualization: A Systematic Literature Review

Requirements Engineering (RE) is a decision-centric activity which is highly data-intensive. The results of this process are known to have key impact on the results of the project. As known from the experience in other fields and disciplines, visualization can potentially provide more insights into data, information and knowledge studied. While research in the area of information visualization and its application to software engineering has rapidly increased over the last decade, there is only a limited amount of studies addressing the usage and impact of visualization techniques for RE activities. In this paper, we report on the results of a Systematic Literature Review (SLR) related to RE visualization. Extending the established SLR process by the usage of grounded theory for the encoding of papers, we synthesize 18 usage patterns. Even though there are punctual applications, there is a clear deficit on a holistic perspective across the different RE activities. As another conclusion, we derive the clear need for more research on visualization support in particular for tackling requirements uncertainty, requirements verification, and modeling, as well as non-functional requirements (NFRs).

What Works Better? A Study of Classifying Requirements

Classifying requirements into functional requirements (FR) and non-functional ones (NFR) is an important task in requirements engineering. However, automated classification of requirements written in natural language is not straightforward, due to the variability of natural language and the absence of a controlled vocabulary. This paper investigates how automated classification of requirements into FR and NFR can be improved and how well several machine learning approaches work in this context. We contribute an approach for preprocessing requirements that standardizes and normalizes requirements before applying classification algorithms. Further, we report on how well several existing machine learning methods perform for automated classification of NFRs into sub-categories such as usability, availability, or performance. Our study is performed on 625 requirements provided by the OpenScience tera-PROMISE repository. We found that our preprocessing improved the performance of an existing classification method. We further found significant differences in the performance of approaches such as Latent Dirichlet Allocation, Biterm Topic Modeling, or Naïve Bayes for the sub-classification of NFRs.

A Visual Narrative Path from Switching to Resuming a Requirements Engineering Task

Requirements Engineering (RE) is closely tied to other development activities and is at the heart and foundation of every software development process. This makes RE the most data and communication intensive activity compared to other development tasks. The highly demanding communication makes task switching and interruptions inevitable in RE activities. While task switching often allows us to perform tasks effectively, it imposes a cognitive load and can be detrimental to the primary task, particularly in complex tasks as the ones typical for RE activities. Visualization mechanisms enhanced with analytical methods and interaction techniques help software developers obtain a better cognitive understanding of the complexity of RE decisions, leading to timelier and higher quality decisions. In this paper, we propose to apply interactive visual analytics techniques for managing requirements decisions from various perspectives, including stakeholders communication, RE task switching, and interruptions. We propose a new layered visualization framework that supports the analytical reasoning process of task switching. This framework consists of both data analysis and visualization layers. The visual layers offer interactive knowledge visualization components for managing task interruption decisions at different stages of an interruption (i.e. before, during, and after). The analytical layers provide narrative knowledge about the consequences of task switching decisions and help requirements engineers to recall their reasoning process and decisions upon resuming a task. Moreover, we surveyed 53 software developers to test our visual prototype and to explore more required features for the visual and analytical layers of our framework.

Agile Testing: A Systematic Mapping across Three Conferences: Understanding Agile Testing in the XP/Agile Universe, Agile, and XP Conferences

Unit and acceptance testing are central to agile software development, but is that all there is to agile testing? We build on previous work to provide a systematic mapping of agile testing publications at major agile conferences. The analysis presented in this paper allows us to answer research questions like: what is agile testing used for, what types of studies on agile testing have been published, what problems do people have when performing agile testing, and what benefits do these publications offer? We additionally explore topics such as: who are the major authors in this field, in which countries do these authors work, what tools are mentioned, and is the field driven by academics, practitioners, or collaborations? This paper presents our analysis of these topics in order to better structure future work in the field of agile testing and to provide a better understanding of what this field actually entails.

Choosing Requirements for Experimentation with User Interfaces of Requirements Modeling Tools

When designing a new presentation front-end called FlexiView for requirements modeling tools, we encountered a general problem: designing such an interface requires a lot of experimentation which is costly when the code of the tool needs to be adapted for every experiment. On the other hand, when using simplified user interface (UI) tools, the results are difficult to generalize. To improve this situation, we are developing an UI experimentation tool which is based on so-called ImitGraphs. ImitGraphs can act as a simple, but accurate substitute for a modeling tool. In this paper, we define requirements for such an UI experimentation tool based on an analysis of the features of existing requirements modeling tools.

Let’s Hear it from RETTA: A Requirements Elicitation Tool for TrAffic Management Systems

The area of Traffic Management (TM) is characterized by uncertainty, complexity, and imprecision. The complexity of software systems in the TM domain which contributes to a more challenging Requirements Engineering (RE) job mainly stems from the diversity of stakeholders and complexity of requirements elicitation in this domain. This work brings an interactive solution for exploring functional and non-functional requirements of software-reliant systems in the area of traffic management. We prototyped the RETTA tool which leverages the wisdom of the crowd and combines it with machine learning approaches such as Natural Language Processing and Naïve Bayes to help with the requirements elicitation and classification task in the TM domain. This bridges the gap among stakeholders from both areas of software development and transportation engineering. The RETTA prototype is mainly designed for requirements engineers and software developers in the area of TM and can be used on Android-based devices.

Transportation Engineering on Social Question and Answer Websites: An Empirical Case Study

In the last decade, the area of Transportation Engineering (TE), and its underlying disciplines such as public transit, connected vehicles, road planning, and air traffic management, has become increasingly prominent. A better understanding of what the most challenging topics related to TE are among practitioners will greatly help to identify the areas of TE that may require extra attention by researchers and project managers. However, there has been very little experimental work in regards to identify true practitioner’s needs on the implementation and understanding of TE activities and tasks. Therefore, in this paper, we use data from the popular social Q&A sites (e.g. Stack Overflow and Engineering Exchange), and analyze 2457 questions and answers in order to examine the needs of transportation engineers, and their concerns and questions. We applied Latent Dirichlet Allocation-based (LDA) topic models and statistical analysis to explore the main related topics to TE.

Understanding the impact of technical debt in coding and testing: an exploratory case study

Technical Debt (TD) refers to the long-term consequences of shortcuts taken during different phases of software development life cycle. Lack of attention to monitoring and managing testing and development debt can contribute to unexpectedly large cost overruns and severe quality issues in software development projects. This paper describes a case study conducted with an industry partner to explore the impact of TD in coding and testing. By conducting (i) a semi-structured interview, and (ii) a quantitative survey, we found that (1) the status of TD is largely project-independent, (2) we could not reject that there is no significant difference between the percentage of existing TD and the required time for reducing this TD in testing and development teams, (3) there is a statistically significant difference between the perceived influence of reducing TD on productivity increase in testing and development teams, (4) team members experience has impact on the existing percentage of TD and influences productivity increase that is caused by reducing TD, (5) allocating more resources such as time, budget, and infrastructure is considered a potential solution for reducing TD.

WaterVis: GeoVisual Analytics for Exploring Hydrological Data

Visualizing and analyzing large amounts of environmental and hydrological data on maps is difficult. Interaction and manipulation of data is crucial for decision making during natural disasters like floods. In this paper we present WaterVis: a geovisual Big Data analytics application to help analysts explore large amounts of hydrological data to create early flood warnings, and make strategic decisions in critical situations. The implications of WaterVis can help inform the design of future Big Data analytics applications.