Tailoring IEEE 1471 for MDE Support

Welcome to the International Conference on Software and Systems Process (ICSSP) held in Zurich, Switzerland, on June 2nd and 3rd, 2012. Having grown from a Software Process Workshop in 2005 to the International Conference on Software Process (ICSP) in 2007, and finally to the International Conference on Software and Systems Process (ICSSP) in 2011, this conference series has established its place in the software engineering community as a respected conference focusing on research and practice related to software and systems development process. Software and software systems development use processes as one major means for achieving and ensuring the quality of the final product. This leads to specific challenges regarding software processes such as simplicity, adaptability, standard conformance, the coordination of multiple domains and lifecycles, etc. Processes from other domains (e.g., health care, manufacturing, business, aerospace, automotive systems, and others) face similar challenges. Yet, they share interesting similarities with and differences to software processes. The question is: How can we in the software domain learn from other domains to meet our software process engineering challenges? The ICSSP conferences hence connect the traditional software and systems process community with outside views and insights, broadening its scope of software development processes to system development and explicitly including processes of other domains such as health care, business, and manufacturing. By sharing process development theories and practices from such domains, ICSSP 2012 is investigating novel solutions to today's process challenges. Correspondingly, the main theme of ICSSP 2012 is Beyond Software and Software Systems Processes, signaling our goal of learning from domains other than the traditional software process community.

Software companies need to cope with permanent changes in market. To stay competitive it is often inevitable to improve processes and adopt to new technologies. Indeed, it is well known that software processes and model-driven engineering (MDE) are subject to evolution. Simultaneously, it is known that MDE can affect process tailoring, which makes it possible that evolution in MDE triggers process evolution and vice versa. This can lead to undesired process changes and additional cost, when process adaptations constitute a need for further investments in MDE tooling. However, there is little knowledge so far whether this co-evolution exists and how it looks like. In this chapter, we present two industrial case studies on co-evolution of MDE and software process. Based on these case studies, we present an initial list of co-evolution drivers and observations made on co-evolution of software processes and MDE. Furthermore, we compile our lessons learned to directly help process managers dealing with co-evolution.

During the last decade, Model Driven Engineering (MDE) has been proposed for supporting the development, maintenance and evolution of software systems. Model Driven Architecture (MDA), Software Factories and Eclipse Modeling Framework (EMF) are among the most representatives MDE approaches. Nowadays, it is well recognized that model transformation is at the heart of MDE approaches and, consequently represents one of the most important operations in MDE. However, despite the multitude of model transformation language proposals emerging from academic world and industry, these transformations are often manually specified; which is a tedious and error-prone task, and therefore an expensive process. Matching operation between metamodels is the keystone toward a (semi-)automatic transformation process. In this paper, the authors review metamodel matching techniques of the literature and then analyze their pros and cons in order to show how they can be useful for a semi-automatic transformation process. The result is a comparison of metamodel matching techniques, highlighting their similarities and differences in terms of information used for matching, demonstrating significant similarities between these techniques. Next, the authors compare four well-known metamodel matching techniques namely Similarity flooding, SAMT4MDE+ (extended Semi-Automatic Matching Tool for Model Driven Engineering), ModelCVS and AML (AtlanMod Matching Language) on ten couples of metamodels. For this comparison, the authors define a set of six criteria inspired from the database schema matching. One among these criteria is relevant to the quality of matching and for which we define a quality measure metrics. Furthermore, the authors develop a plug-in under Eclipse to support our comparison using ten couples of metamodels.

work of W. Edwards Deming has convinced industry that must first measure quality and then emphasise process to improve quality. In response to Deming's arguments and in light of perception that software industry is unable to produce quality products on schedule, and within budget, more software development organisations are now emphasising process measurement, monitoring, and assessment. This paper describes what is meant by software process and discusses an approach for its measurement and improvement. INTRODUCTION Unreliable software makes big news, from emergency services disasters to social security payment blunders. Improved software quality is essential to ensure reliable products and services, and gain customer satisfaction. While software development has existed for more than four decades, we failed so far to make as an industry and as an engineering discipline rather than craft. Developing reliable and usable software that is delivered on and within budget still represents difficult endeavour for many organisations. As role of software becomes increasingly critical for businesses as well as for human lives, problems caused by software products that are late, over budget, or that do not work, become magnified. If lives are lost or people inconvenienced due to incapable computer software, news media is there to make big stories. Organisations are realising that their fundamental problems is immaturity of their software process. Robert Lai (1993) proposes that process improvement is second maturity wave of software industry. He states that the first wave of software was developed using waterfall model in 1970's. Today we are Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517 216 Software Management in midst of second wave maturity movement as we attempt to formally define development process and best ways to continuously improve it (Lai 1993). Taking lead in this area has been Watts Humphrey (Humphrey 1989, 1990, 1991), and Software Engineering Institute (SEI) at Carnegie Mellon University. SEI started in 1986 to develop process maturity framework to help organisations appraise maturity of their software process, and to provide guidance for organisations to improve their software process capability. A brief description of framework was released in September 1987, including maturity questionnaire. SEI evolved model and questionnaire into 5 -Level Capability Maturity Model (CMM) in 1991. In February 1993, released CMM version 1.1 (Paulk et al 1993). This paper discusses software process and describes capability maturity model (CMM). It also shows how CMM can be used as basis to measure maturity of software process of an organisation and plan its improvement. SOFTWARE QUALITY AND PROCESS IMPROVEMENT In his book Quality is Free Phil Crosby states that: Quality is free. It is not gift, is free. What cost money are unqualify of things all actions that involve not doing jobs right first time (Crosby 1980). If such statement is true for many disciplines, is particularly true for evidence is abundant in number of software products which exceeded their budget, were produced late, failed to satisfy user requirements, and are full of bugs. demand for improved software quality is increasing to ensure reliable products and services. benefits of improved quality comes in form of reduction in failure costs. For software projects failure costs include (DTI 1992): • costs of correcting defects, both before and after delivery • overruns against and budget • unnecessary high maintenance costs • indirect costs which users incur due to poor quality software link between process maturity and software quality is expressed in premise that The quality of software system is governed by quality of process used to develop and maintain it. One stumbling block to improving software quality seems to be that not enough attention is paid to overall development process itself. While software professionals typically devote their to developing, testing or documenting software products, no one has prime responsibility for improving software process. Experience has shown that if Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517 Managing Systems 217 no one is working on software process, orderly improvement is unlikely. process certainly won't improve itself, rather, most likely, will deteriorate over time. Continuous improvement can occur only if process infrastructure is in place. Watts Humphrey argues in an early article published in Datamation, April 1989 that: Without work on process, there will be little or no progress in improving software. THE SOFTWARE PROCESS Adopting process view of software development represents revolutionary change in perspective. A process orientation to software development involves elements of structure, focus, measurement, ownership, skills, and supporting technology. In this section we investigate what is meant by software process. What Is Software Process According to Webster's dictionary, process is a system of operations in producing something .. series of actions, changes, or functions that achieve an end result. Chambers Concise Dictionary defines process as a series of actions or events .. sequence of operations or changes undergone. IEEE defines process as a sequence of steps performed for given purpose. In general business context, process is defined as a structured, measured set of activities designed to produce specified output for particular customer or market (Davenport 1993). These definitions put strong emphasis on HOW work is done, in contrast to product focus's emphasis on WHAT. Accordingly, process can be considered as a specific ordering of work activities across and place, with beginning, an end, and clearly identified inputs and outputs: structure for action. In this paper we will adopt following definitions quoted in (Humphrey 1990, Paulk et al 1993) are intended to encompass software throughout its life, which covers new development, enhancement, and repair. software process is The set of activities, methods, and practices used in production and evolution of software. software engineering process is The total set of software engineering activities needed to transform user's requirements into software. Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517 218 Software Management People and Software Process Software development is still people-intensive activity. Talented people are most important element in any software organisation. Even if you get best people available, if they do not follow common process, if everyone wrote in different programming languages, used different conventions, or didn't co-ordinate their design and code changes with their peers, results will be chaos. Successful software organisations have learned that even best professionals need structured and disciplined environment in which to do cooperative work. Software organisations that do not establish such disciplines condemn their people to endless hours of repetitively solving technically trivial problems. obvious fact is that attracting best people is vital, but is also essential to support them with an effectively managed software process. Technology and Software Process Another myth is widespread belief that some technologically advanced tool or method will provide magic answer to software crisis. This is not only wrong, but is dangerous. Organisations which jumped on bandwagon of CASE tools, and ended up in failure and wasted and effort have learned their lesson hard way. Just ask yourself before introducing technology: What do I want to automate? In absence of defined, practised, and managed process, introducing automation can lead to increased chaos. There are several factors which limit effective use of software technology: an illdefined process, inconsistent process implementation, and poor process management. Software technology cannot be fully effective until these problems have been properly addressed. Need for Defined Process If no effort is made to define and enhance software development process across whole organisation, each software development project latches on to its own tools, methods, and practices with little guidance available on how to use them. This ad hoc approach will not be sufficient to tackle task of developing complex software systems. goal of software process management is to enable organisations to produce software that meets cost, schedules, and quality objectives. principles are same that underpins statistical process control-principles that have been successfully used in controlling scientific experiments and in high -volume manufacturing operations. Statistical concepts have been found to be just as applicable to software development as they are to production of manufactured goods such as motor cars. Applying such concepts will only be possible if there is defined and managed process. Software Process Models Transactions on Information and Communications Technologies vol 8, © 1994 WIT Press, www.witpress.com, ISSN 1743-3517

Lessons learned from applying model-driven engineering in 5 domains: The success story of the MontiGem generator framework

Model-Driven Engineering (MDE) is changing the way we build, operate, and maintain our software-intensive systems. Several projects using MDE practices are reporting significant improvements in quality and performance but, to be able to handle these projects, software engineers need a set of technical and interpersonal skills that are currently not widely available. The MDE postgraduate diploma intends to fill this gap by offering a full-time one year formation onMDE. The course syllabus is designed to teach students how to work at a higher abstraction level by the rigorous use of (software) models as the main artifacts in all software engineering activities. Contents include the conceptual framework of MDE plus all techniques and tools (e.g. for defining modeling languages, models, and model transformations) required to successfully complete software engineering projects following a MDE approach. The organizational impact (and challenges) of adopting MDE are exemplified using real industrial experiences. This article describes the MDE Diploma and the lessons that we learned after completing its first edition.

<p dir="ltr">Model-Driven Engineering (MDE) is a methodology in software development which emphasizes the use of models throughout the development process. Key aspects of MDE include process modelling and enactment, which provide a systemic approach to developing software. Traceability is currently gaining prominence within MDE, since it facilitates the tracking of artefacts through the development and management process, from inception to final output.</p><p dir="ltr">We propose an approach that integrates end-to-end traceability with process modelling. In our research, process models represent MDE workflows that span platform-independent modelling, platform-specific modelling, and code generation phases. Process execution is automated using megamodels and model transformation chains. The generation of end-to-end traceabillity information enables global model traceability, from high-level input models to generated code, forming the basis for traceability analysis.</p><p dir="ltr">We have built an Eclipse-based framework, ProMoTA, to support our approach. ProMoTA extends the Acceleo model transformation language, introducing local traceability support. Our tool suite within ProMoTA encompasses a global traceability map generator and end-to-end traceability analysis modules, providing users with a holistic view of the entire transformation process. To validate the efficacy and versatility of ProMoTA, we modelled and analyzed two distinct systems; a Digital Signal Processing Filter Designer which we both implemented and analyzed, and a WSNbased IoT system which we analyzed. Through analysis using our framework, we demonstrate ProMoTA’s capability to effectively address traceability challenges, underscoring its potential as a tool in modern MDE processes. In particular, ProMoTA allows us to examine global traceability of large systems and processes using change impact and origin tracking analysis techniques.</p>

In Software Engineering as in all other engineering fields, the product to be build is divided into sub-parts that are independently constructed and subsequently assembled. This procedure reduces the complexity and improves the reuse of the developed products. MDE (Model Driven Engineering) is a recent software engineering discipline that focuses this approach. It has allowed several significant improvements in the development of complex software systems by providing the means that enable to switch from one abstraction level into another or from one modeling space into another. However, models management may be tedious and costly. Thus, it is necessary to provide some flexible and reliable tools for automatic management of models and some techniques for their transformations in order to live up to user expectations. In this context, model composition has become an important artifact in the MDE domain that allows constructing and composing an efficient assembly process. In this paper, we present the state of the art of recent works in the model composition methods and techniques by focusing on the various parameters that govern and characterize their behavior.

: In this era of increasingly complex software and mushrooming software development and maintenance costs, the software engineering community needs to improve its practices to remain competitive and to produce software that can meet complex software requirements. Projects often overrun costs, miss deadlines, and fail to meet the requirements of the customer. Now new software process technologies are evolving to help address these concerns in the areas of process assessment, definition, simulation, and enactment. A software process is a set of activities, methods, practices, and transformations that people use to develop and maintain software and associated products. The quality of a product stems, in large part, from the quality of the process used to create it. To consistently improve products, the process used for developing them should be understood, defined, measured, and progressively improved. Software process assessment is the act of determining the maturity of an organization's software process. Software process definition is the act of specifying in some detail an organization's software process. Software process simulation is the act of executing a software process definition. The term modeling will often be used in this report to encompass both process definition and simulation. The term enactment denotes the use of a formal process definition to guide and control the software process. In this report, software process technologies will be described, their benefits outlined, and their implications assessed. Technology maturity will be discussed and recommendations will be given for technologies that can be effectively used today.

The Model-Driven Engineering (MDE) research must manage a diversity of conceptions despite the global truth about the use of conceptual models as one way for representing and managing the development of complex information systems. Due to this diversity of conceptions and the multiple MDE compliance interpretations, a pletora of definitions about quality in models are emerging, each one tackling specific dimensions involved in MDE projects. In order to explore a consensus about quality in models and model-driven contexts an identification of the previous proposals for quality in models is needed. The main contribution of this work is the identification of representative trends about quality definition in MDE, and therefore, exposing the implications of the multiple quality interpretations as consequence of the diversity in MDE compliance works.

Model composition in Model Driven Engineering: A systematic literature review

Since its emergence in 2009, DevOps has significantly advanced software development. Numerous studies have explored the evolution of DevOps and its related methodologies. Some of this research has investigated how model-driven engineering (MDE) can enhance the adoption and implementation of CI/CD practices, commonly known as DevOps pipelines. MDE, originating in the 1980s, offers a distinct approach to software development compared to the traditional “code is the model” mindset. This paper examines the potential synergies between MDE and DevOps, specifically reviewing existing studies on the key artifacts of DevOps pipelines. Our findings indicate that current efforts have not yet sufficiently generalized or formalized reusable transformation rules for a DevOps pipeline model and its corresponding meta-model. These elements are crucial for a successful MDE approach. Therefore, this study proposes an application of the model transformation concept to the DevOps pipeline model. Furthermore, it conceptualizes a reusable model transformation solution capable of generating both the DevOps pipeline model and its resulting code from a software architecture model. The broad research presented here identifies requirements for a potentially groundbreaking future DevOps solution.

This paper details the application of software product lines (SPL) and model-driven engineering (MDE) to the software defined radio domain. More specifically it is an experience report emphasizing the synergy resulting from combining MDE and SPL technologies. The software defined radio domain has very unique characteristics as its systems typically are a confluence of a number of typically challenging aspects of software development. To name a few, these systems are usually described by modifiers such as, embedded, real-time, distributed, object-oriented, portable, heterogeneous, multithreaded, high performance, dynamic, resource-constrained, safety-critical, secure, networked, component based and fault-tolerant. Each one of these modifiers by themselves carries with it a set of unique challenges but building systems characterized by all of these modifiers all at the same time makes for quite an adventure in software development. In addition to all of these, it is quite common in these embedded systems for components to have multiple implementations that must run on disparate processing elements. With all of this taken into account, it stands to reason that these systems could and should benefit greatly from advances in software technology such as product line engineering, domain-specific modeling and model-driven engineering. It is our experience that one big boon to the software development industry is the combination of the software product lines and model driven engineering technologies.

We share experience in supporting development and evolution of a large banking product using a homegrown model driven engineering (MDE) toolset. We discuss improvements that needed to be introduced in the MDE toolset to support collaborative development with teams distributed across different geographical locations. Though experience is shared in a specific context, we believe, MDE researchers, enthusiasts, practitioners and tool vendors will find the takeaways from this experience applicable even in a more general context of large scale software development.

The Model Driven Engineering (MDE) supports software development, promoting quality and speed enhancement in providing new products. The development of more accurate models is obtained through the employment of the Object Constraint Language (OCL). Given the increasing use of mobile devices and the need for new applications, the MDE together with the OCL constraints promote the development of quality mobile applications when the development time is reduced. This research paper focuses on the definition and use of OCL constraints to support the development of Android models in the MDE context.