Social media through the requirements lens:a case study of Google Maps

Social media serves as an extensive repository of user interaction related to software applications. Users discuss application features and express their sentiments about them in both qualitative (usually in natural language) and quantitative ways (for example, via votes). Further, many social media applications support explicit social networks of users and measures such as user reputation. Naturally, content on social media has the potential to inform requirements engineering. However, models of requirements and associated tools that enable software engineers to make sense of this information are currently lacking. In this paper, we present a preliminary study of interaction among users about Google Maps on the forum Reddit. We highlight important artifacts relevant to requirements in these interactions. We discuss goal modeling as an archetypal requirements modeling approach and use that as a basis for enhancing requirements modeling with notions that capture user interaction

Applying acceptance requirements to requirements modeling tools via gamification: a case study on privacy and security.

Requirements elicitation, analysis and modeling are critical activities for software success. However, software systems are increasingly complex, harder to develop due to an ever-growing number of requirements from numerous and heterogeneous stakeholders, concerning dozens of requirements types, from functional to qualitative, including adaptation, security and privacy, ethical, acceptance and more. In such settings, requirements engineers need support concerning such increasingly complex activities, and Requirements Engineering (RE) modeling tools have been developed for this. However, such tools, although effective, are complex, time-consuming and requiring steep learning curves. The consequent lack of acceptance and abandonment in using such tools, by engineers, paves the way to the application of RE techniques in a more error-prone, low-quality way, increasing the possibility to have failures in software systems delivered. In this paper, we identify main areas of lack of acceptance, affecting RE engineers, for such tools, and propose an approach for making modeling tools more effective in engaging the engineer in performing RE in a tool-based way, receiving adequate feedback and staying motivated to use modeling tools. This is accomplished by performing acceptance requirements analysis (through the Agon Framework) and using gamification to increase the engagement of engineers during the usage of RE modeling tools. Towards this end, we performed a case study, within the VisiOn European Project, for enhancing a tool for modeling privacy and security requirements. Our case study provides preliminary evidence that our approach supports in making RE modeling tools more engaging from the engineer perspective

Agent-Based Modelling: A New Tool for Legal Requirements Engineering: Introduction and Use Case (KEI)

Foundational assumptions under legal systems come adrift with innovation in non-law disciplines. In an effort towards improved understanding of what is going on (and what can be done) we turn to agent-based modeling as a tool. We use the KEI project for our use case, apply Holland’s ECHO framework as legal requirements engineering tool and use NetLogo as platform for implementation (resulting in an application we call Epiframer). We study parameter-change induced behavioral dynamics in the resulting artificial society. Findings are in two tiers: (i) on the role of the law in a multi-force field and (ii) on the role of institutions (also: sibling disciplines) for informing specialist legal professionals. We submit epiframer’s assumptions for diverse-disciplinary scrutiny as a closure. We have not yet reached a level that warrants the deployment of statistical learning methods onto data provided by simulation runs and are aware that such an approach has - where legal requirements engineering events tend to be sparsely punctuated - limited added value for legal requirements engineering situations anyway. With De Marchi (2005) our claim is that under such conditions computational, mathematical and, indeed, qualitative methods have complementary uses

A Systems Engineering Methodology for Wide Area Network Selection using an Analytical Hierarchy Process

In this paper, we apply a systems engineering methodology to select the most appropriate wide area network (WAN) media suite, according to organizational technical requirements, using an Analytic Hierarchy Process (AHP). AHP is a mathematical decision modeling tool that utilizes decomposition, determination, and synthesis to solve complex engineering decision problems. AHP can deal with the universal modeling of process engineering decision-making, which is difficult to describe quantitatively, by integrating quantitative and qualitative analysis. We formulate and apply AHP to a hypothetical case study in order to examine its feasibility for the WAN media selection problem. The results indicate that our model can improve the decision-making process by evaluating and comparing all alternative WANs. This shows that AHP can support and assist an organization in choosing the most effective solution according to its demands. AHP is an effective resource-saver from many perspectives—it gives high performance, economic, and high quality solutions. Keywords: Analytical Hierarchy Process, Wide Area Network, AHP Consistency, WAN alternatives

Semi-Automated Analysis of Large Privacy Policy Corpora

Regulators, policy makers, and consumers are interested in proactively identifying services with acceptable or compliant data use policies, privacy policies, and terms of service. Academic requirements engineering researchers and legal scholars have developed qualitative, manual approaches to conducting requirements analysis of policy documents to identify concerns and compare services against preferences or standards. In this research, we develop and present an approach to conducting large-scale, qualitative, prospective analyses of policy documents with respect to the wide-variety of normative concerns found in policy documents. Our approach uses techniques from natural language processing, including topic modeling and summarization. We evaluate our approach in an exploratory case study that attempts to replicate a manual legal analysis of roughly 200 privacy policies from seven domains in a semi-automated fashion at a larger scale. Our findings suggest that this approach is promising for some concerns

An Exploratory Study of Forces and Frictions affecting Large-Scale Model-Driven Development

In this paper, we investigate model-driven engineering, reporting on an exploratory case-study conducted at a large automotive company. The study consisted of interviews with 20 engineers and managers working in different roles. We found that, in the context of a large organization, contextual forces dominate the cognitive issues of using model-driven technology. The four forces we identified that are likely independent of the particular abstractions chosen as the basis of software development are the need for diffing in software product lines, the needs for problem-specific languages and types, the need for live modeling in exploratory activities, and the need for point-to-point traceability between artifacts. We also identified triggers of accidental complexity, which we refer to as points of friction introduced by languages and tools. Examples of the friction points identified are insufficient support for model diffing, point-to-point traceability, and model changes at runtime.Comment: To appear in proceedings of MODELS 2012, LNCS Springe