Agile product line planning: A collaborative approach and a case study

Agile methods and product line engineering (PLE) have both proven successful in increasing customer satisfaction and decreasing time to market under certain conditions. Key characteristics of agile methods are lean and highly iterative development with a strong emphasis on stakeholder involvement. PLE leverages reuse through systematic approaches such as variability modeling or product derivation. Integrating agile approaches with product line engineering is an interesting proposition which – not surprisingly – entails several challenges: Product lines (PL) rely on complex plans and models to ensure their long-term evolution while agile methods emphasize simplicity and short-term value-creation for customers. When incorporating agility in product line engineering, it is thus essential to define carefully how agile principles can support particular PLE processes. For instance, the processes of defining and setting up a product line (domain engineering) and deriving products (application engineering) differ significantly in practices and focus with implications on the suitability of agile principles. This paper presents practical experiences of adopting agile principles in product line planning (a domain engineering activity). ThinkLets, i.e., collaborative practices from the area of collaboration engineering, are the building blocks of the presented approach as they codify agile principles such as stakeholder involvement, rapid feedback, or value-based prioritization. We discuss how our approach balances agility and the intrinsic needs of product line planning. A case study carried out with an industrial partner indicates that the approach is practicable, usable, and useful.     

Structuring the modeling space and supporting evolution in software product line engineering

The scale and complexity of product lines means that it is practically infeasible to develop a single model of the entire system, regardless of the languages or notations used. The dynamic nature of real-world systems means that product line models need to evolve continuously to meet new customer requirements and to reflect changes of product line artifacts. To address these challenges, product line engineers need to apply different strategies for structuring the modeling space to ease the creation and maintenance of models. This paper presents an approach that aims at reducing the maintenance effort by organizing product lines as a set of interrelated model fragments defining the variability of particular parts of the system. We provide support to semi-automatically merge fragments into complete product line models. We also provide support to automatically detect inconsistencies between product line artifacts and the models representing these artifacts after changes. Furthermore, our approach supports the co-evolution of models and their respective meta-models. We discuss strategies for structuring the modeling space and show the usefulness of our approach using real-world examples from our ongoing industry collaboration.     

A formal framework for software product lines

ContextA Software Product Line is a set of software systems that are built from a common set of features. These systems are developed in a prescribed way and they can be adapted to fit the needs of customers. Feature models specify the properties of the systems that are meaningful to customers. A semantics that models the feature level has the potential to support the automatic analysis of entire software product lines.ObjectiveThe objective of this paper is to define a formal framework for Software Product Lines. This framework needs to be general enough to provide a formal semantics for existing frameworks like FODA (Feature Oriented Domain Analysis), but also to be easily adaptable to new problems.MethodWe define an algebraic language, called SPLA, to describe Software Product Lines. We provide the semantics for the algebra in three different ways. The approach followed to give the semantics is inspired by the semantics of process algebras. First we define an operational semantics, next a denotational semantics, and finally an axiomatic semantics. We also have defined a representation of the algebra into propositional logic.ResultsWe prove that the three semantics are equivalent. We also show how FODA diagrams can be automatically translated into SPLA. Furthermore, we have developed our tool, called AT, that implements the formal framework presented in this paper. This tool uses a SAT-solver to check the satisfiability of an SPL.ConclusionThis paper defines a general formal framework for software product lines. We have defined three different semantics that are equivalent; this means that depending on the context we can choose the most convenient approach: operational, denotational or axiomatic. The framework is flexible enough because it is closely related to process algebras. Process algebras are a well-known paradigm for which many extensions have been defined.     

Software product line scoping and requirements engineering in a small and medium-sized enterprise: An industrial case study

Software product line (SPL) engineering has been applied in several domains, especially in large-scale software development. Given the benefits experienced and reported, SPL engineering has increasingly garnered interest from small to medium-sized companies. It is possible to find a wide range of studies reporting on the challenges of running a SPL project in large companies. However, very little reports exist that consider the situation for small to medium-sized enterprises and these studies try develop universal truths for SPL without lessons learned from empirical evidence need to be contextualized. This study is a step towards bridging this gap in contextual evidence by characterizing the weaknesses discovered in the scoping (SC) and requirements (RE) disciplines of SPL. Moreover, in this study we conducted a case study in a small to medium sized enterprises (SMEs) to justify the use of agile methods when introducing the SPL SC and RE disciplines through the characterization of their bottlenecks. The results of the characterization indicated that ineffective communication and collaboration, long iteration cycles, and the absence of adaptability and flexibility can increase the effort and reduce motivation during project development. These issues can be mitigated by agile methods.     

Experience of using a lightweight formal specification method for a commercial embedded system product line

A simple specification method is introduced and the results of its application to a series of projects in Philips are reported. The method is principally designed to ensure that that every unusual scenario is considered in a systematic way. In practice, this has led to high-quality specifications and accelerated product development. While the straightforward tabular notation used has proved readily understandable to non-technical personnel, it is also a formal method, producing a model of system behaviour as a finite state machine. In this respect, the notation is unusual in being designed to preserve as far as possible a view of the overall system state and how this changes. The notation also features a constraint table which may be described as a kind of spreadsheet for invariants to help define the states of the system.

A digital twin-enhanced system for engineering product family design and optimization

Engineering product family design and optimization in complex environments has been a major bottleneck in today’s industrial transformation towards smart manufacturing. Digital twin (DT), as a core part of cyber-physical system (CPS), can provide decision support to enhance engineering product lifecycle management workflows via remote monitoring and control, high-fidelity simulation, and solution generation functionalities. Although many studies have proven DT to be highly suited for industry needs, little has been reported on the product family design and optimization capabilities specifically with context awareness, which could be leaving many enterprises ambivalent on its adoption. To fill this gap, a reusable and transparent DT capable of situational recognition and self-correction is essentially required. This paper develops a generic DT architecture reference model to enable the context-aware product family design optimization process in a cost-effective manner. A case study featuring asset re-/configuration within a dynamic environment is further described to demonstrate its in-context decision-aiding capabilities. The authors hope this study can provide valuable insights to both academia and industry in improving their engineering product family management process.     

Survey on mechatronic engineering: A focus on design methods and product models

According to the principles of concurrent engineering and integrated design, engineers intend to develop a mechatronic system with a high level integration (functional and physical integrations) based on a well-organised design method. As a result, two main categories of issues have been pointed out: the process-based problems and the design data-related problems. Several approaches to overcome these issues have been put forward. To solve process-based problems, a dynamic perspective is generally used to present how collaboration can be improved during the mechatronic design. For design data-related problems, solutions generally come from product models and how to structure and store the data thanks to the functionality of data and documents management of Product Lifecycle Management systems. To be able to assess design methods and product models, some criteria are proposed in the paper and used to evaluate their added value on integrated design of mechatronic system. After this assessment, main outcomes which focus on the combination of design method and product model for improving the design of mechatronic system are finally discussed.     

Experiences applying formal approaches in the development of swarm-based space exploration systems

NASA is researching advanced technologies for future exploration missions using intelligent swarms of robotic vehicles. One of these missions is the Autonomous Nano-Technology Swarm (ANTS) mission that will explore the asteroid belt using 1,000 cooperative autonomous spacecraft. The emergent properties of intelligent swarms make it a potentially powerful concept, but at the same time more difficult to design and ensure that the proper behaviors will emerge. NASA is investigating formal methods and techniques for verification of such missions. The advantage of using formal methods is the ability to mathematically verify the behavior of a swarm, emergent or otherwise. Using the ANTS mission as a case study, we have evaluated multiple formal methods to determine their effectiveness in modeling and ensuring desired swarm behavior. This paper discusses the results of this evaluation and proposes an integrated formal method for ensuring correct behavior of future NASA intelligent swarms.     

Empirical evaluation of a decision support model for adopting software product line engineering

ContextThe software product line engineering (SPLE) community has provided several different approaches for assessing the feasibility of SPLE adoption and selecting transition strategies. These approaches usually include many rules and guidelines which are very often implicit or scattered over different publications. Hence, for the practitioners it is not always easy to select and use these rules to support the decision making process. Even in case the rules are known, the lack of automated support for storing and executing the rules seriously impedes the decision making process.ObjectiveWe aim to evaluate the impact of a decision support system (DSS) on decision-making in SPLE adoption. In alignment with this goal, we provide a decision support model (DSM) and the corresponding DSS.MethodFirst, we apply a systematic literature review (SLR) on the existing primary studies that discuss and present approaches for analyzing the feasibility of SPLE adoption and transition strategies. Second, based on the data extraction and synthesis activities of the SLR, the required questions and rules are derived and implemented in the DSS. Third, for validation of the approach we conduct multiple case studies.ResultsIn the course of the SLR, 31 primary studies were identified from which we could construct 25 aspects, 39 questions and 312 rules. We have developed the DSS tool Transit-PL that embodies these elements.ConclusionsThe multiple case study validation showed that the adoption of the developed DSS tool is justified to support the decision making process in SPLE adoption.     

An approach to competitive product line design using conjoint data

In today’s highly competitive environment, where market oriented firms aim to maximize profits through customer satisfaction, there is an increasing need to design a product line, rather than a single product. The main goal of designing a profit maximizing product line is to target the ‘right product’ to the ‘right customer’. Although conjoint analysis has turned out to be one of the most widely used techniques for product line design, it falls to explicitly consider retaliatory reactions from competitors. In this paper, we propose a new conjoint-based approach to competitive new product line design, employing the Nash equilibrium concept. The optimal product line design problem for each firm is formulated as a nonlinear integer programming problem. In the absence of a closed-form solution, to compute the Nash equilibrium and to determine the optimal product line, we propose a two-phase procedure: a sequential iterative procedure in the first phase, and backward induction in the second. To solve the optimization problem in each of the iterations of the sequential procedure, we used the branch-and-bound method. The proposed approach is illustrated under several scenarios of competition using previously published conjoint data.     

Multiresolution model based extraction of product feature lines in reverse engineering

In this paper, multiresolution models are employed in the context of reverse engineering for feature line extraction. Starting with a proper triangulation of the cloud point data as a priori, our feature line extraction algorithm has three steps: (1) establishing a Gauss normal sphere and creating multiresolution models for the Gauss sphere based on different levels of subdivisions for the sphere regions; (2) mapping the unit normal vectors of triangular faces in the multiresolution Gauss sphere and merging those connected triangular faces whose unit normal vectors fallen on the same Gauss sphere region with a given resolution to form super-faces (the collection of triangular facets with similar normal); and (3) extracting the boundaries from the super-faces and generating the feature lines from the extracted boundaries. We then use these feature lines as a base for tracing boundary curves for B-spline surface construction. Since feature lines maintain the characteristics of the original product models, in this way, we have a good chance to reconstruct B-spline surfaces with high quality. Examples are given in the paper to show the feature line extraction, the influence of the feature lines extracted under different resolutions, and the final reconstructed B-spline surfaces based on these feature lines.     

An empirical research agenda for understanding formal methods productivity

ContextFormal methods, and particularly formal verification, is becoming more feasible to use in the engineering of large highly dependable software-based systems, but so far has had little rigorous empirical study. Its artefacts and activities are different to those of conventional software engineering, and the nature and drivers of productivity for formal methods are not yet understood.ObjectiveTo develop a research agenda for the empirical study of productivity in software projects using formal methods and in particular formal verification. To this end we aim to identify research questions about productivity in formal methods, and survey existing literature on these questions to establish face validity of these questions. And further we aim to identify metrics and data sources relevant to these questions.MethodWe define a space of GQM goals as an investigative framework, focusing on productivity from the perspective of managers of projects using formal methods. We then derive questions for these goals using Easterbrook et al.’s (2008) taxonomy of research questions. To establish face validity, we document the literature to date that reflects on these questions and then explore possible metrics related to these questions. Extensive use is made of literature concerning the L4.verified project completed within NICTA, as it is one of the few projects to achieve code-level formal verification for a large-scale industrially deployed software system.ResultsWe identify more than thirty research questions on the topic in need of investigation. These questions arise not just out of the new type of project context, but also because of the different artefacts and activities in formal methods projects. Prior literature supports the need for research on the questions in our catalogue, but as yet provides little evidence about them. Metrics are identified that would be needed to investigate the questions. Thus although it is obvious that at the highest level concepts such as size, effort, rework and so on are common to all software projects, in the case of formal methods, measurement at the micro level for these concepts will exhibit significant differences.ConclusionsEmpirical software engineering for formal methods is a large open research field. For the empirical software engineering community our paper provides a view into the entities and research questions in this domain. For the formal methods community we identify some of the benefits that empirical studies could bring to the effective management of large formal methods projects, and list some basic metrics and data sources that could support empirical studies. Understanding productivity is important in its own right for efficient software engineering practice, but can also support future research on cost-effectiveness of formal methods, and on the emerging field of Proof Engineering.     

Formal methods software engineering for the CARA system

This paper discusses the application of formal methods software engineering (FMSE) to the development of the Computer Automated Resuscitation A (CARA) medical device at Walter Reed Army Institute of Research. Because this system is potentially life critical, a high level of quality was required. A formal engineering approach to the software development activities was chosen to satisfy this need. Specifically, a technique called sequence enumeration was applied to elicit and refine requirements while deriving a formal specification. The fundamentals of the specification process that was used on the project are described along with a brief summary of the project experience in the development and testing phases. The project employed recent advances in Cleanroom software engineering methods along with older box-structured development and usage-model-based statistical testing techniques.     

Limits of formal methods

Formal methods can help to increase the correctness and trustworthiness of the software developed. However, they do not solve all the problems of software development. This paper analyses some limitations of formal methods.     

基于产品线体系结构的软件工程过程模型研究

在借鉴现代工业的组织体系、管理规范、生产流程的基础上,针对基于软件产品线体系结构的软件工程方法和开发过程进行了系统研究,提出了基于产品线体系结构而实现软件工程化生产的N-生命周期模型.该模型的建立,对研究基于软件产品线体系结构的集成化软件工程环境,进而实现软件产品的工业化生产是非常有益且重要的.     

STEP-based product modeling system for remote collaborative reverse engineering

Production of high-quality products with lower cost and shorter time-to-market is an important challenge in the face of increased global competition, and reverse engineering plays an important role in accelerating product and process development. With the advent of new technologies such as network, multimedia and product data exchange standard STEP (STandard for Exchange of Product model data), there are many advantages to adopt these technologies to enhance the competitiveness of an enterprise. In this paper, a product information recording module for reverse engineering is developed to enhance the performance of product development. A STEP development tool, ST-Developer, and Visual C++ were used to develop this module, which can be used to record key information expeditiously during a collaborative process, and can also be used for further exchange of information, or as the basis for manufacturability evaluation. In this paper, the developed STEP-based information recording system is further integrated with the conventional Computer Supported Cooperative Work methods such as videoconferencing and application-sharing to form a remote collaborative reverse engineering system, which can provides a new strategy for an enterprise to speed up the product development cycle, reducing production cost, as well as sharing knowledge and experience.     

Ontology-based similarity for product information retrieval

Product development of today is becoming increasingly knowledge intensive. Specifically, design teams face considerable challenges in making effective use of increasing amounts of information. In order to support product information retrieval and reuse, one approach is to use case-based reasoning (CBR) in which problems are solved “by using or adapting solutions to old problems.” In CBR, a case includes both a representation of the problem and a solution to that problem. Case-based reasoning uses similarity measures to identify cases which are more relevant to the problem to be solved. However, most non-numeric similarity measures are based on syntactic grounds, which often fail to produce good matches when confronted with the meaning associated to the words they compare. To overcome this limitation, ontologies can be used to produce similarity measures that are based on semantics. This paper presents an ontology-based approach that can determine the similarity between two classes using feature-based similarity measures that replace features with attributes. The proposed approach is evaluated against other existing similarities. Finally, the effectiveness of the proposed approach is illustrated with a case study on product–service–system design problems.     

On the use of a formal requirements engineering language: The Generalized Railroad Crossing Problem

In this paper, we report on the use of theAlbert II requirements specification language through the handling of the Generalized Railroad Crossing case study. This formal language is based on an ontology of concepts used for capturing requirements inherent in real-time, distributed systems. Because of itsnaturalness, the language supports a direct mapping of customers’ informal needs onto formal statements, without having to introduce artificial elements. The language is founded on a formal framework (real-time temporal logic) which supports the reasoning process of the analyst during the elaboration of the specification. Such support for the reasoning is illustrated in the context of a goal-oriented approach adopted for the elaboration of the case study.     

Process fusion: An industrial case study on agile software product line engineering

This paper presents a case study of a software product company that has successfully integrated practices from software product line engineering and agile software development. We show how practices from the two fields support the company’s strategic and tactical ambitions, respectively. We also discuss how the company integrates strategic, tactical and operational processes to optimize collaboration and consequently improve its ability to meet market needs, opportunities and challenges. The findings from this study are relevant to software product companies seeking ways to balance agility and product management. The findings also contribute to research on industrializing software engineering.     

The UML as a formal modeling notation

The Unified Modeling Language (UML) is an Object Management Group (OMG) object-oriented (OO) modeling notation standard. It consists of a set of notations for modeling systems from a variety of views and at varying levels of abstraction. While the UML reflects some of the best OO modeling experiences available, it suffers from a lack of precise semantics that is necessary if one is to use the notations to precisely model systems and to rigorously reason about the models. In this paper we discuss some of the problems with the current UML semantic document and present the approach that the precise UML group (pUML) group is using to develop a precise semantics for the UML. The approach utilizes mathematical techniques to explore and gain insights into appropriate semantics for UML modeling concepts. The insights and formal expressions will then be used to develop a UML semantics document written in natural language that defines the semantics in a precise, consistent, and understandable manner.