Elicitation and management of user requirements in market-driven software development

Market-driven software development companies experience challenges in requirements management that many traditional requirements engineering methods and techniques do not acknowledge. Large markets, limited contact with end users, and strong competition forces the market-driven software development company to constantly invent new, selling requirements, frequently release new versions with an accompanying pressure of short time-to-market, and take both the technical and financial risks of development. This thesis presents empirical results from case studies in requirements elicitation and management at a software development company. The results include techniques to explore, understand, and handle bottlenecks in the requirements process where requirements continuously arrive at a high rate from many different stakeholders. Through simulation of the requirements process, potential bottlenecks are identified at an early stage, and fruitless improvement attempts may be avoided. Several techniques are evaluated and recommended to support the market-driven organisation in order to increase software quality and avoid process overload situations. It is shown that a quick and uncomplicated in-house usability evaluation technique, an improved heuristic evaluation, may be adequate to get closer to customer satisfaction. Since needs and opportunities differ between markets, a distributed prioritisation technique is suggested that will help the organisation to pick the most cost-beneficial and customer satisfying requirements for development. Finally, a technique based on automated natural language analysis is investigated with the aim to help resolve congestion in the requirements engineering process, yet retaining ideas that may bring a competitive advantage

Supporting Change in Product Lines within the Context of Use Case-Driven Development and Testing

Product Line Engineering (PLE) is becoming a common practice in industry to enhance product quality, to reduce development costs, and to improve time-to-market. At the same time, many development contexts are use case-driven and this strongly influences their requirements engineering and system testing practices. In this PhD project, we aim to achieve automated and effective change management in a product family within the context of use case-driven development and system testing. To this end, we first provide a modeling method for capturing variability information explicitly in Product Line (PL) use case and domain models. Then, we propose an automated configuration approach to automatically generate Product Specific (PS) use case and domain models from PL models. In addition, we plan to provide a change impact analysis approach for PL use case and domain models and automated regression test selection for system test cases derived from PL use case models

Undulate : A framework for data-driven software engineering enabling soft computing

Context. Especially web-facing software systems enable the collection of usage data at a massive scale. At the same time, the scale and scope of software processes have grown substantively. Automated tools are needed to increase the speed and quality of controlling software processes. The usage data has great potential as a driver for software processes. However, research still lacks constructs for collecting, refining and utilising usage data in controlling software processes.Objective. The objective of this paper is to introduce a framework for data-driven software engineering. The UNDULATE framework covers generating, collecting and utilising usage data from software processes and business processes supported by the software produced. In addition, we define the concepts and process of extreme continuous experimentation as an exemplar of a software engineering process.Method. We derive requirements for the framework from the research literature, with a focus on papers inspired by practical problems. In addition, we apply a multilevel modelling language to describe the concepts related to extreme continuous experimentation.Results. We introduce the UNDULATE framework and give requirements and provide an overview of the processes of collecting usage data, augmenting it with additional dimensional data, aggregating the data along the dimensions and computing different metrics based on the data and other metrics.Conclusions. The paper represents significant steps inspired by previous research and practical insight towards standardised processes for data-driven software engineering, enabling the application of soft computing and other methods based on artificial intelligence.Peer reviewe

DECIMAL: A requirements engineering tool for product families

Today, many software organizations are utilizing product families as a way of improving productivity, improving quality and reducing development time. When a new member is added to a product family, there must be a way to verify whether the new member\u27s specific requirements are met within the reuse constraints of its product family. The contribution of this paper is to demonstrate such a verification process by describing a requirements engineering tool called DECIMAL. DECIMAL is an interactive, automated, GUI driven verification tool that automatically checks for completeness (checking to see if all commonalities are satisfied) and consistency (checking to see if dependencies between variabilities are satisfied) of the new member\u27s requirements with the product family\u27s requirements. DECIMAL also checks that variabilities are within the range and data type specified for the product family. The approach is to perform the verification using a database as the underlying analysis engine. A pilot study of a virtual reality device driver product family is also described which investigates the feasibility of this approach by evaluating the tool

The dimensions of software engineering success

Software engineering research and practice are hampered by the lack of a well-understood, top-level dependent variable. Recent initiatives on General Theory of Software Engineering suggest a multifaceted variable – Software Engineering Success. However, its exact dimensions are unknown. This paper investigates the dimensions (not causes) of software engineering success. An interdisciplinary sample of 191 design professionals (68 in the software industry) were interviewed concerning their perceptions of success. Non-software designers (e.g. architects) were included to increase the breadth of ideas and facilitate comparative analysis. Transcripts were subjected to supervised, semi-automated semantic content analysis, including a software developer vs. other professionals comparison. Findings suggest that participants view their work as time-constrained projects with explicit clients and other stakeholders. Success depends on stakeholder impacts – financial, social, physical and emotional – and is understood through feedback. Concern with meeting explicit requirements is peculiar to software engineering and design is not equated with aesthetics in many other fields. Software engineering success is a complex multifaceted variable, which cannot sufficiently be explained by traditional dimensions including user satisfaction, profitability or meeting requirements, budgets and schedules. A proto-theory of success is proposed, which models success as the net impact on a particular stakeholder at a particular time. Stakeholder impacts are driven by project efficiency, artifact quality and market performance. Success is not additive, e.g., ‘low’ success for clients does not average with ‘high’ success for developers to make ‘moderate’ success overall; rather, a project may be simultaneously successful and unsuccessful from different perspectives

Reliability prediction in model driven development

Evaluating the implications of an architecture design early in the software development lifecycle is important in order to reduce costs of development. Reliability is an important concern with regard to the correct delivery of software system service. Recently, the UML Profile for Modeling Quality of Service has defined a set of UML extensions to represent dependability concerns (including reliability) and other non-functional requirements in early stages of the software development lifecycle. Our research has shown that these extensions are not comprehensive enough to support reliability analysis for model-driven software engineering, because the description of reliability characteristics in this profile lacks support for certain dynamic aspects that are essential in modeling reliability. In this work, we define a profile for reliability analysis by extending the UML 2.0 specification to support reliability prediction based on scenario specifications. A UML model specified using the profile is translated to a labelled transition system (LTS), which is used for automated reliability prediction and identification of implied scenarios; the results of this analysis are then fed back to the UML model. The result is a comprehensive framework for addressing software reliability modeling, including analysis and evolution of reliability predictions. We exemplify our approach using the Boiler System used in previous work and demonstrate how reliability analysis results can be integrated into UML models

Requirements traceability in model-driven development: Applying model and transformation conformance

The variety of design artifacts (models) produced in a model-driven design process results in an intricate relationship between requirements and the various models. This paper proposes a methodological framework that simplifies management of this relationship, which helps in assessing the quality of models, realizations and transformation specifications. Our framework is a basis for understanding requirements traceability in model-driven development, as well as for the design of tools that support requirements traceability in model-driven development processes. We propose a notion of conformance between application models which reduces the effort needed for assessment activities. We discuss how this notion of conformance can be integrated with model transformations

Automated Functional Testing based on the Navigation of Web Applications

Web applications are becoming more and more complex. Testing such applications is an intricate hard and time-consuming activity. Therefore, testing is often poorly performed or skipped by practitioners. Test automation can help to avoid this situation. Hence, this paper presents a novel approach to perform automated software testing for web applications based on its navigation. On the one hand, web navigation is the process of traversing a web application using a browser. On the other hand, functional requirements are actions that an application must do. Therefore, the evaluation of the correct navigation of web applications results in the assessment of the specified functional requirements. The proposed method to perform the automation is done in four levels: test case generation, test data derivation, test case execution, and test case reporting. This method is driven by three kinds of inputs: i) UML models; ii) Selenium scripts; iii) XML files. We have implemented our approach in an open-source testing framework named Automatic Testing Platform. The validation of this work has been carried out by means of a case study, in which the target is a real invoice management system developed using a model-driven approach.Comment: In Proceedings WWV 2011, arXiv:1108.208