| 1. |
- Badampudi, Deepika, et al.
(författare)
-
Perspectives on Productivity and Delays in Large-Scale Agile Projects
- 2013
-
Konferensbidrag (refereegranskat)abstract
- Many large and distributed companies run agile projects in development environments that are inconsistent with the original agile ideas. Problems that result from these inconsistencies can affect the productivity of development projects and the timeliness of releases. To be effective in such contexts, the agile ideas need to be adapted. We take an inductive approach for reaching this aim by basing the design of the development process on observations of how context, practices, challenges, and impacts interact. This paper reports the results of an interview study of five agile development projects in an environment that was unfavorable for agile principles. Grounded theory was used to identify the challenges of these projects and how these challenges affected productivity and delays according to the involved project roles. Productivity and delay-influencing factors were discovered that related to requirements creation and use, collaboration, knowledge management, and the application domain. The practitioners’ explanations about the factors' impacts are, on one hand, a rich empirical source for avoiding and mitigating productivity and delay problems and, on the other hand, a good starting point for further research on flexible large-scale development.
|
|
| 2. |
- Betz, Stefanie, et al.
(författare)
-
An Evolutionary Perspective on Socio-Technical Congruence:The Rubber Band Effect
- 2013
-
Ingår i: International Symposium on Empirical Software Engineering and Measurement. - Baltimore : IEEE Xplore.
-
Konferensbidrag (refereegranskat)abstract
- Conway’s law assumes a strong association between the system’s architecture and the organization’s communication structure that designs it. In the light of contemporary software development, when many companies rely on geographically distributed teams, which often turn out to be temporarily composed and thus having an often changing communication structure, the importance of Conway’s law and its inspired work grows. In this paper, we examine empirical research related to Conway’s law and its application for cross-site coordination. Based on the results obtained we conjecture that changes in the communication structure alone sooner or later trigger changes in the design structure of the software products to return the sociotechnical system into the state of congruence. This is further used to formulate a concept of a rubber band effect and propose a replication study that goes beyond the original idea of Conway’s law by investigating the evolution of socio-technical congruence over time.
|
|
| 3. |
|
|
| 4. |
- Eivazzadeh, Shahryar, et al.
(författare)
-
Evaluating Health Information Systems Using Ontologies
- 2016
-
Ingår i: JMIR Medical Informatics. - : JMIR Publications. - 2291-9694. ; 4:2
-
Tidskriftsartikel (refereegranskat)abstract
- Background: There are several frameworks that attempt to address the challenges of evaluation of health information systems by offering models, methods, and guidelines about what to evaluate, how to evaluate, and how to report the evaluation results. Model-based evaluation frameworks usually suggest universally applicable evaluation aspects but do not consider case-specific aspects. On the other hand, evaluation frameworks that are case specific, by eliciting user requirements, limit their output to the evaluation aspects suggested by the users in the early phases of system development. In addition, these case-specific approaches extract different sets of evaluation aspects from each case, making it challenging to collectively compare, unify, or aggregate the evaluation of a set of heterogeneous health information systems.Objectives: The aim of this paper is to find a method capable of suggesting evaluation aspects for a set of one or more health information systems—whether similar or heterogeneous—by organizing, unifying, and aggregating the quality attributes extracted from those systems and from an external evaluation framework.Methods: On the basis of the available literature in semantic networks and ontologies, a method (called Unified eValuation using Ontology; UVON) was developed that can organize, unify, and aggregate the quality attributes of several health information systems into a tree-style ontology structure. The method was extended to integrate its generated ontology with the evaluation aspects suggested by model-based evaluation frameworks. An approach was developed to extract evaluation aspects from the ontology that also considers evaluation case practicalities such as the maximum number of evaluation aspects to be measured or their required degree of specificity. The method was applied and tested in Future Internet Social and Technological Alignment Research (FI-STAR), a project of 7 cloud-based eHealth applications that were developed and deployed across European Union countries.Results: The relevance of the evaluation aspects created by the UVON method for the FI-STAR project was validated by the corresponding stakeholders of each case. These evaluation aspects were extracted from a UVON-generated ontology structure that reflects both the internally declared required quality attributes in the 7 eHealth applications of the FI-STAR project and the evaluation aspects recommended by the Model for ASsessment of Telemedicine applications (MAST) evaluation framework. The extracted evaluation aspects were used to create questionnaires (for the corresponding patients and health professionals) to evaluate each individual case and the whole of the FI-STAR project.Conclusions: The UVON method can provide a relevant set of evaluation aspects for a heterogeneous set of health information systems by organizing, unifying, and aggregating the quality attributes through ontological structures. Those quality attributes can be either suggested by evaluation models or elicited from the stakeholders of those systems in the form of system requirements. The method continues to be systematic, context sensitive, and relevant across a heterogeneous set of health information systems.
|
|
| 5. |
|
|
| 6. |
- Fotrousi, Farnaz, et al.
(författare)
-
Analytics for Product Planning : In-depth Interview Study with SaaS Product Managers
- 2013
-
Konferensbidrag (refereegranskat)abstract
- SaaS cloud computing, in contrast to packaged products, enables permanent contact between users of a software product and the product-owning company. When planning the development and evolution of a software product, a product manager depends on reliable information about feature attractiveness. So far, planning decisions were based on stakeholder opinion and the customer's willingness to buy. Whether or not a feature actually is used was out of consideration. Analytics that measure the interaction between users and the SaaS gives product managers unprecedented access to information about product usage. To understand whether and how SaaS analytics can be used for product planning decision, we performed 17 in-depth interviews with experienced managers of SaaS products and analyzed the results analyzed with a mixed-method strategy. The empirical results characterize the relevance of a broad range of analytics for product planning decisions, and the strengths and limitations of an analytics-based product planning approach.
|
|
| 7. |
- Fotrousi, Farnaz
(författare)
-
Combining User Feedback and Monitoring Data to Support Evidence-based Software Evolution
- 2020
-
Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Context. Companies continuously explore their software systems to acquire evidence for software evolution, such as bugs in the system and new functional or quality requirements. So far, managers have made decisions about software evolution based on evidence gathered from interpreting user feedback and monitoring data collected separately from software in use. These evidence-collection processes are usually unmethodical, lack a systematic guide, and have practical issues. This lack of a systematic approach leaves unexploited opportunities for detecting evidence for system evolution. Objective. The main research objective is to improve evidence collection from software in use and guide software practitioners in decision-making about system evolution. Understanding useful approaches to collect user feedback and monitoring data, two important sources of evidence, and combining them are key objectives as well. Method. We proposed a method for gathering evidence from software in use (GESU) using design-science research. We designed the method over three iterations and validated it in the European case studies FI-Start, Supersede, and Wise-IoT. To acquire knowledge for the design, we conducted further research using surveys and systematic mapping methods. Results. The results show that GESU is not only successful in industrial environments but also yields new evidence for software evolution by bringing user feedback and monitoring data together. This combination helps software practitioners improve their understanding of end-user needs and system drawbacks, ultimately supporting continuous requirements elicitation and product evolution. GESU suggests monitoring a software system based on its goals to filter relevant data (i.e., goal-driven monitoring) and gathering user feedback when the system requests feedback about the software in use (i.e., system-triggered user feedback). The system identifies interesting situations of system use and issues automated requests for user feedback to interpret the evidence from user perspectives. We justified using goal-driven monitoring and system-triggered user feedback with complementary findings of the thesis. That showed the goals and characteristics of software systems constrain monitoring data. We thus narrowed the monitoring and observational focus on data aligned with goals instead of a massive amount of potentially useless data. Finally, we found that requesting feedback from users with a simple feedback form is a useful approach for motivating users to provide feedback. Conclusion. Combining user feedback and monitoring data is helpful to acquire insights into the success of a software system and guide decision-making regarding its evolution. This work can be extended in the future by implementing an adaptive system for gathering evidence from combined user feedback and monitoring data
|
|
| 8. |
|
|
| 9. |
- Fotrousi, Farnaz, et al.
(författare)
-
KPIs for software ecosystems : A systematic mapping study
- 2014
-
Ingår i: Software Business. - Cham : Springer. - 9783319087382
-
Konferensbidrag (refereegranskat)abstract
- To create value with a software ecosystem (SECO), a platform owner has to ensure that the SECO is healthy and sustainable. Key Performance Indicators (KPI) are used to assess whether and how well such objectives are met and what the platform owner can do to improve. This paper gives an overview of existing research on KPI-based SECO assessment using a systematic mapping of research publications. The study identified 34 relevant publications for which KPI research and KPI practice were extracted and mapped. It describes the strengths and gaps of the research published so far, and describes what KPI are measured, analyzed, and used for decision-making from the researcher's point of view. For the researcher, the maps thus capture stateof- knowledge and can be used to plan further research. For practitioners, the generated map points to studies that describe how to use KPI for managing of a SECO.
|
|
| 10. |
- Fotrousi, Farnaz, et al.
(författare)
-
QoE probe : A requirement-monitoring tool
- 2016
-
Ingår i: CEUR Workshop Proceedings. - : CEUR-WS.
-
Konferensbidrag (refereegranskat)abstract
- Runtime requirement monitoring is used for verification and validation of implemented requirements. To monitor the requirements in runtime; we propose a "QoE probe" tool, a mobile application integrated through an API, to collect usage logs as well as users’ Quality of Experience (QoE) in the form of user feedback. The analysis of the collected data guides requirement monitoring of functional and non-functional requirements as well as capturing new requirements.
|
|
