Nan Niu

Requirements engineering for software product lines: A systematic literature review

Context: Software product line engineering (SPLE) is a growing area showing promising results in research and practice. In order to foster its further development and acceptance in industry, it is necessary to assess the quality of the research so that proper evidence for adoption and validity are ensured. This holds in particular for requirements engineering (RE) within SPLE, where a growing number of approaches have been proposed. Objective: This paper focuses on RE within SPLE and has the following goals: assess research quality, synthesize evidence to suggest important implications for practice, and identify research trends, open problems, and areas for improvement. Method: A systematic literature review was conducted with three research questions and assessed 49 studies, dated from 1990 to 2009. Results: The evidence for adoption of the methods is not mature, given the primary focus on toy examples. The proposed approaches still have serious limitations in terms of rigor, credibility, and validity of their findings. Additionally, most approaches still lack tool support addressing the heterogeneity and mostly textual nature of requirements formats as well as address only the proactive SPLE adoption strategy. Conclusions: Further empirical studies should be performed with sufficient rigor to enhance the body of evidence in RE within SPLE. In this context, there is a clear need for conducting studies comparing alternative methods. In order to address scalability and popularization of the approaches, future research should be invested in tool support and in addressing combined SPLE adoption strategies.

Enhancing candidate link generation for requirements tracing: The cluster hypothesis revisited

Modern requirements tracing tools employ information retrieval methods to automatically generate candidate links. Due to the inherent trade-off between recall and precision, such methods cannot achieve a high coverage without also retrieving a great number of false positives, causing a significant drop in result accuracy. In this paper, we propose an approach to improving the quality of candidate link generation for the requirements tracing process. We base our research on the cluster hypothesis which suggests that correct and incorrect links can be grouped in high-quality and low-quality clusters respectively. Result accuracy can thus be enhanced by identifying and filtering out low-quality clusters. We describe our approach by investigating three open-source datasets, and further evaluate our work through an industrial study. The results show that our approach outperforms a baseline pruning strategy and that improvements are still possible.

A case study of exploiting enterprise resource planning requirements

The requirements engineering (RE) processes have become a key to conceptualising corporate-wide integrated solutions based on packaged enterprise resource planning (ERP) software. The RE literature has mainly focused on procuring the most suitable ERP package. Little is known about how an organisation exploits the chosen ERP RE model to frame the business application development. This article reports an exploratory case study of a key tenet of ERP RE adoption, namely that aligning business applications to the packaged RE model leads to integral practices and economic development. The case study analysed a series interrelated pilot projects developed for a business division of a large IT manufacturing and service company, using Oracles appl1ication implementation method (AIM). The study indicated that AIM RE improved team collaboration and project management experience, but needed to make hidden assumptions explicit to support data visibility and integrity. Our study can direct researchers towards rigorous empirical evaluations of ERP RE adoption, collect experiences and lessons learned for practitioners, and help generate more effective and mature processes when exploiting ERP RE methods.

Source code indexing for automated tracing

Requirements-to-source-code traceability employs information retrieval (IR) methods to automatically link requirements to the source code that implements them. A crucial step in this process is indexing, where partial and important information from the software artifacts is converted into a representation that is compatible with the underlying IR model. Source code demands special attention in the indexing process. In this paper, we investigate source code indexing for supporting automatic traceability. We introduce a feature diagram that captures the key components and their relationships in the domain of source code indexing. We then present an experiment to examine the features of the diagram and their dependencies. Results show that utilizing comments has a significant effect on traceability link generation, and stemming is required when comments are considered.

On the role of semantics in automated requirements tracing

Abstract In this paper, we investigate the potential benefits of utilizing natural language semantics in automated traceability link retrieval. In particular, we evaluate the performance of a wide spectrum of semantically enabled information retrieval methods in capturing and presenting requirements traceability links in software systems. Our objectives are to gain more operational insights into these methods and to provide practical guidelines for the design and development of effective requirements tracing and management tools. To achieve our research objectives, we conduct an experimental analysis using three datasets from various application domains. Results show that considering more semantic relations in traceability link retrieval does not necessarily lead to higher quality results. Instead, a more focused semantic support, that targets specific semantic relations, is expected to have a greater impact on the overall performance of tracing tools. In addition, our analysis shows that explicit semantic methods, that exploit local or domain-specific sources of knowledge, often achieve a more satisfactory performance than latent methods, or methods that derive semantics from external or general-purpose knowledge sources.

Traceability-enabled refactoring for managing just-in-time requirements

Just-in-time requirements management, characterized by lightweight representation and continuous refinement of requirements, fits many iterative and incremental development projects. Being lightweight and flexible, however, can cause wasteful and procrastinated implementation, leaving certain stakeholder goals not satisfied. This paper proposes traceability-enabled refactoring aimed at fulfilling more requirements fully. We make a novel use of requirements traceability to accurately locate where the software should be refactored, and develop a new scheme to precisely determine what refactorings should be applied to the identified places. Our approach is evaluated through an industrial study. The results show that our approach recommends refactorings more appropriately than a contemporary recommender.

A Systems Approach to Product Line Requirements Reuse

Product line engineering has become the main method for achieving systematic software reuse. Embracing requirements in a product lines asset base enhances the effectiveness of reuse as engineers can work on the abstractions closer to the domains initial concepts. Conventional proactive approaches to product line engineering cause excessive overhead when codifying the assets. In this paper, we propose a systems-oriented approach to extracting functional requirements profiles. The validated extraction constructs are amenable to semantic case analysis and orthogonal variability modeling, so as to uncover the variation structure and constraints. To evaluate our approach, we present an experiment to quantify the extraction overhead and effectiveness and a case study to assess our approachs usefulness. The results show that our automatic support offers an order-of-magnitude saving over the manual extraction effort without significantly compromising quality and that our approach receives a positive adoption rate by systems engineers.

Visual requirements analytics: a framework and case study

For many software projects, keeping requirements on track needs an effective and efficient path from data to decision. Visual analytics creates such a path that enables the human to extract insights by interacting with the relevant information. While various requirements visualization techniques exist, few have produced end-to-end value to practitioners. In this paper, we advance the literature on visual requirements analytics by characterizing its key components and relationships in a framework. We follow the goal–question–metric paradigm to define the framework by teasing out five conceptual goals (user, data, model, visualization, and knowledge), their specific operationalizations, and their interconnections. The framework allows us to not only assess existing approaches, but also create tool enhancements in a principled manner. We evaluate our enhanced tool support through a case study where massive, heterogeneous, and dynamic requirements are processed, visualized, and analyzed. Working together with practitioners on a contemporary software project within its real-life context leads to the main finding that visual analytics can help tackle both open-ended visual exploration tasks and well-structured visual exploitation tasks in requirements engineering. In addition, the study helps the practitioners to reach actionable decisions in a wide range of areas relating to their project, ranging from theme and outlier identification, over requirements tracing, to risk assessment. Overall, our work illuminates how the data-to-decision analytical capabilities could be improved by the increased interactivity of requirements visualization.

Variability Modeling for Product Line Viewpoints Integration

Modern software product line development uses viewpoints to capture the needs of various stakeholders without resorting to a single complex model. Comparing and integrating different viewpoints help to gain insights into the product line and to derive products. Recent research has proposed conflict resolution rules for handling variability in the integration process. However, one benefit viewpoints bring is to tolerate inconsistency until the rationales about variability are better understood. In this paper, we propose a method for modeling variability when product line viewpoints are consolidated. Our method takes advantage of a lattice ordering to support late binding of variability and stakeholder traceability. We apply our method to viewpoints derived from the mobile phone domain, and show how delayed commitment can support product line evolution and product derivation.

ReCVisu: A tool for clustering-based visual exploration of requirements

Clustering is of great practical value in discovering natural groupings of large numbers of requirements artifacts. Clustering-based visualization has shown promise in supporting requirements tracing. In this paper, we transform the success to a wider range of clustering-based visual exploration tasks in requirements engineering. We describe ReCVisu, a requirements exploration tool based on quantitative visualizations. We discuss the key features of ReCVisu and its potential improvements over previous work.