Garm Lucassen

Forging high-quality User Stories: Towards a discipline for Agile Requirements

User stories are a widely used notation for formulating requirements in agile development projects. Despite their popularity in industry, little to no academic work is available on assessing their quality. The few existing approaches are too generic or employ highly qualitative metrics. We propose the Quality User Story Framework, consisting of 14 quality criteria that user story writers should strive to conform to. Additionally, we introduce the conceptual model of a user story, which we rely on to design the AQUSA software tool. AQUSA aids requirements engineers in turning raw user stories into higher-quality ones by exposing defects and deviations from good practice in user stories. We evaluate our work by applying the framework and a prototype implementation to three user story sets from industry.

The Use and Effectiveness of User Stories in Practice

[Context and motivation] User stories are an increasingly popular textual notation to capture requirements in agile software development. [Question/Problem] To date there is no scientific evidence on the effectiveness of user stories. The goal of this paper is to explore how practicioners perceive this artifact in the context of requirements engineering. [Principal ideas/results] We explore perceived effectiveness of user stories by reporting on a survey with 182 responses from practitioners and 21 follow-up semi-structured interviews. The data shows that practitioners agree that using user stories, a user story template and quality guidelines such as the INVEST mnemonic improve their productivity and the quality of their work deliverables. [Contribution] By combining the survey data with 21 semi-structured follow-up interviews, we present 12 findings on the usage and perception of user stories by practitioners that employ user stories in their everyday work environment.

Gamified Requirements Engineering: Model and Experimentation

[Context & Motivation] Engaging stakeholders in requirements engineering RE influences the quality of the requirements and ultimately of the system to-be. Unfortunately, stakeholder engagement is often insufficient, leading to too few, low-quality requirements. [Question/problem] We aim to evaluate the effectiveness of gamification to improve stakeholder engagement and ultimately performance in RE. We focus on agile requirements that are expressed as user stories and acceptance tests. [Principal ideas/results] We develop the gamified requirements engineering model GREM that relates gamification, stakeholder engagement, and RE performance. To evaluate GREM, we build an online gamified platform for requirements elicitation, and we report on a rigorous controlled experiment where two independent teams elicited requirements for the same system with and without gamification. The findings show that the performance of the treatment group is significantly higher, and their requirements are more numerous, have higher quality, and are more creative. [Contribution] The GREM model paves the way for further work in gamified RE. Our evaluation provides promising initial empirical insights, and leads us to the hypothesis that competitive game elements are advantageous for RE elicitation, while social game elements are favorable for RE phases where cooperation is demanded.

Automated Extraction of Conceptual Models from User Stories via NLP

Natural language (NL) is still the predominant notation that practitioners use to represent software requirements. Albeit easy to read, NL does not readily highlight key concepts and relationships such as dependencies and conflicts. This contrasts with the inherent capability of graphical conceptual models to visualize a given domain in a holistic fashion. In this paper, we propose to automatically derive conceptual models from a concise and widely adopted NL notation for requirements: user stories. Due to their simplicity, we hypothesize that our approach can improve on the low accuracy of previous works. We present an algorithm that combines state-of-the-art heuristics and that is implemented in our Visual Narrator tool. We evaluate our work on two case studies wherein we obtained promising precision and recall results (between 80% and 92%). The creators of the user stories perceived the generated models as a useful artifact to communicate and discuss the requirements, especially for team members who are not yet familiar with the project.

Ecosystem Health of Cloud PaaS Providers

Customers of Platform as a Service providers are unable to evaluate the risk of their provider going bankrupt. Lacking this information, businesses are effectively putting their critical business services in jeopardy. In this paper, we present a method to evaluate the ecosystem health of eight different PaaS providers. The results of our research enable businesses and individuals to make an informed decision on what PaaS providers to do business with. Additionally, the PaaS providers themselves are given insight into the current state of their ecosystem compared to competitors.

Comparison of Visual Business Modeling Techniques for Software Companies

Despite the widespread adoption of business modeling techniques in academic research and business, no research has been done into how efficient and effective business modeling techniques document and communicate business models. This paper compares three visual business modeling techniques with a visual approach and identifies the strong and weak points of each modeling technique, based on applying the techniques to three startups and interviews with industry experts. With this comparison, visual business modeling technique developers can improve their own techniques and software companies can determine which technique to apply in their specific case.

Visualizing User Story Requirements at Multiple Granularity Levels via Semantic Relatedness

The majority of practitioners express software requirements using natural text notations such as user stories. Despite the readability of text, it is hard for people to build an accurate mental image of the most relevant entities and relationships. Even converting requirements to conceptual models is not sufficient: as the number of requirements and concepts grows, obtaining a holistic view of the requirements becomes increasingly difficult and, eventually, practically impossible. In this paper, we introduce and experiment with a novel, automated method for visualizing requirements—by showing the concepts the text references and their relationships—at different levels of granularity. We build on two pillars: (i) clustering techniques for grouping elements into coherent sets so that a simplified overview of the concepts can be created, and (ii) state-of-the-art, corpus-based semantic relatedness algorithms between words to measure the extent to which two concepts are related. We build a proof-of-concept tool and evaluate our approach by applying it to requirements from four real-world data sets.

Alignment of software product management and software architecture with discussion models

How to achieve alignment of software product management with software architecture and whether there is a business case for doing so is scientifically unknown. Yet, software architecture has large, direct impact on product success factors: creating a winning product and delivering value to customers. In this exploratory case study paper we identify the most critical processes for SPM and SA alignment: requirements gathering and refinement. These processes require effective communication supported by high level architectural views. Our respondents, however, rely on simple methods due to their negative experiences with formalized models. Based on these findings, we propose the Accurate Architectural Models Approach (AAMA) which prevents architectural model divergence.

Extracting conceptual models from user stories with Visual Narrator

Extracting conceptual models from natural language requirements can help identify dependencies, redundancies, and conflicts between requirements via a holistic and easy-to-understand view that is generated from lengthy textual specifications. Unfortunately, existing approaches never gained traction in practice, because they either require substantial human involvement or they deliver too low accuracy. In this paper, we propose an automated approach called Visual Narrator based on natural language processing that extracts conceptual models from user story requirements. We choose this notation because of its popularity among (agile) practitioners and its focus on the essential components of a requirement: Who? What? Why? Coupled with a careful selection and tuning of heuristics, we show how Visual Narrator enables generating conceptual models from user stories with high accuracy. Visual Narrator is part of the holistic Grimm method for user story collaboration that ranges from elicitation to the interactive visualization and analysis of requirements.

Improving User Story Practice with the Grimm Method: A Multiple Case Study in the Software Industry

Context and motivation: Previous research shows that a considerable amount of real-world user stories contain easily preventable syntactic defects that violate desired qualities of good requirements. However, we still do not know the effect of user stories’ intrinsic quality on practitioners’ work. Question/Problem: We study the effects of introducing the Grimm Method’s Quality User Story framework and the AQUSA tool on the productivity and work deliverable quality of 30 practitioners from 3 companies over a period of 2 months. Principal ideas/results: Our multiple case study delivered mixed findings. Despite an improvement in the intrinsic user story quality, practitioners did not perceive such a change. They explained, however, there was more constructive user story conversation in the post-treatment period leading to less unnecessary rework. Conversely, project management metrics did not result in statistically significant changes in the number of comments, issues, defects, velocity, and rework. Contribution: Introducing our treatment has a mildly positive effect but a larger scale investigation is crucial to decisively assess the impact on work practice. Also, our case study protocol serves as an example for evaluating RE research in practice.