Using system dynamics to teach about dependencies, correlation and systemic thinking on the software process workflows

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

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 engineers have always been experimenting with various models in an endeavor to improve upon software processes. Recently, a new area of software process improvement through experience management has got attention of the software engineering community. Software developers are experimenting with experience management to improve software process. This chapter explores the role of experience management in mitigating the effects of software crisis and investigates the current state of EM in Indian software engineering environment. The chapter discusses the need and integration of knowledge and experience management practices in software engineering environments. The chapter begins with the discussion of the ills of software engineering, classically referred to as “software crisis,” like late delivery of the systems, ill-functionality, and cost overruns, and justifies how managing the knowledge and experience of software engineers and practitioners can ward off these evils. The chapter then discusses the models and methodologies for knowledge and experience management in software engineering. Finally, the chapter sheds light on the major works carried out in this area and suggests possible future research avenues in this domain.

Empathy, defined as the ability to understand and share others’ perspectives and emotions, is essential in software engineering (SE), where developers often collaborate with diverse stakeholders. It is also considered as a vital competency in many professional fields such as medicine, healthcare, nursing, animal science, education, marketing, and project management. Despite its importance, empathy remains under-researched in SE. To further explore this, we conducted a socio-technical grounded theory (STGT) study through in-depth semi-structured interviews with 22 software developers and stakeholders. Our study explored the role of empathy in SE and how SE activities and processes can be improved by considering empathy. Through applying the systematic steps of STGT data analysis and theory development, we developed a theory that explains the role of empathy in SE. Our theory details the contexts in which empathy arises, the conditions that shape it, the causes and consequences of its presence and absence. We also identified contingencies for enhancing empathy or overcoming barriers to its expression. Our findings provide practical implications for SE practitioners and researchers, offering a deeper understanding of how to effectively integrate empathy into SE processes.

The International Conference on Software and System Processes (ICSSP), continuing the success of Software Process Workshop (SPW), the Software Process Modeling and Simulation Workshop (ProSim) and the International Conference on Software Process (ICSP) conference series, has become the established premier event in the field of software and systems engineering processes. It provides a leading forum for the exchange of research outcomes and industrial best-practices in process development from software and systems disciplines. ICSSP 2018 was held in Gothenburg, Sweden, 26-27 May 2018, co-located with the 40th International Conference on Software Engineering (ICSE). The theme of ICSSP 2018 was studying \Demands on Processes, Processes on Demand" by recognizing the demands on processes that include the need for both welldeveloped plans and incremental deliveries (agile and hybrid processes), utilization of increased automation (model-based engineering and DevOps), higher degrees of customer collaboration, comprehensive analysis of existing products for reuse (open source and COTS), and performance requirements of enterprise-level architectures. Papers presented at ICSSP discussed these issues across different domains, providing concepts, evidence, and experiences.

Software process is the most important part of software project management, and software process models are important means of implementing the software process in any software organization. When there is need to improve the software process, then the need to improve the work-task part (software process models) of the software process must arise. As, there is need of increasing the commitment of software project managers through out the software development life cycle (SDLC), so we need to give them the list of activities in Waterfall Model, which should be made efficient by the software development team, to get the 80% productivity (output) easily, by reducing the effort of software development and ultimately increasing the performance of the software process. So, the idea of 80/20 rule (Pareto Principle, 1935) can be applied in the software engineering process model, in this regard. The Pareto Principle (1935) directed us to focus on what is really important in any field and field's work. Software process is most important part of software project management (SPM). This is also then ultimately needed for software project management (SPM) improvement. Our main research work is to improve the work-task part of the software process (i.e. software process models by applying the Pareto Principle - 80/20 Rule (1935) (or law of vital few) (1935), in the software engineering process models (or work-task part of the software process). This will be to facilitate the software project manager, using the software process models practically more efficient than without application of 80/20 Rule in software engineering Waterfall model. This has resulted in the reduction of the software development effort and increase in the performance of the software process. The results (efficient and improved software process models) will be implemented in the software industry, by software project managers, by focusing on the list of activities giving 80 percent of the overall productivity of the software process. The results will be the list of activities having the capability to give 20 percent of the overall productivity of the software Waterfall process, to be ignored, eliminated or designated to reduce the effort.

168 Impact of Connecticut’s Good Samaritan Laws in Preventing Opioid Overdose Deaths – An Applied System Dynamics Approach

Software engineering environments have a history of about two decades. Early environments provided support for small fragments of the software process (usually focusing on programming-in-the small). Then there was a trend towards support for more complete software processes (from early phases like requirements analysis and design down to testing and configuration management). Ten years ago the notion of process-centered software engineering environments initiated a new field in software engineering: software process research. The key idea is to use a model of a software process as input parameter for a software engineering environment. The environment is supposed to “behave” in accordance to the process model. Some aspects of this vision became true, others turned out to be of little practicability. In this article, we discuss the history of software engineering environments with a particular focus on process-centered software engineering environments (PCSEEs). We discuss the notion of distributed software processes (as one of the most substantial current trends in software process research) and we motivate the notion of a software process middleware which serves as basis of real-world software processes spread over various sites. In addition, we discuss some other trends in the software process research arena.

The software engineering process is a growing concern for many software development organizations. The need for well-educated software engineers is bringing new software engineering programs to universities. In many programs, software process education adds up to a few hours of lectures in an introductory software engineering course. This paper presents the structure and the content for a full, one-semester course on software processes, which has been designed in close collaboration with industry. The course is based on a software process called UPEDU (Unified Process for EDUcation), pronounced Yoopeedoo, and has been customized from the Rational Unified Process (RUP) for the educational environment. Many artifacts derived from a project case study are used as examples or templates. The content of the course is oriented towards the cognitive skills needed to perform the various activities required in the software process.

Reflections on adapting group model building scripts into online workshops

As a global community we are faced with many systemic problems. An analytical approach that has proven successful in the study of dynamic feedback systems is systems thinking and system dynamics modeling. If systems thinking and system dynamics have been successfully applied to many systemic problems, why are we not teaching this analytical method to our children? It might be suggested that system dynamics is too sophisticated—much too difficult for children to learn. This suggestion would be wrong. Systems thinking and system dynamics modeling concepts that have been successfully taught for 20 years to students in the U.S.A., ages 5–18 years, are presented, with highlights describing some of the lessons/activities used. Copyright © 2011 System Dynamics Society

In this chapter, an overview of the research progress both in software processes and software evolution are presented from the viewpoints of methodologies, technologies, tools and management. Firstly, the basic concepts related to software processes are discussed. In addition, an overview of the research progress in the areas of software process modelling and descriptions, software process modelling languages and description languages, software process improvement, CMM, software process reuse and process-centred software engineering environments is presented. Furthermore, the basic concepts related to software evolution are discussed. Finally, the work in the areas of software evolution and software reengineering is also discussed. The research outlined in this chapter shows that both software evolution and software process have become the hot spots in software engineering. The combination of software evolution and software process will promote smooth and effective software evolution.

This paper describes a multi-level system dynamics (SD) / discrete event simulation (DES) approach for assessing planning and scheduling problems within an aviation training continuum. The aviation training continuum is a complex system, consisting of multiple aviation schools interacting through interschool student and instructor flows that are affected by external triggers such as resource availability and the weather. SD was used to model the overall training continuum at a macro level to ascertain relationships between system entities. SD also assisted in developing a shared understanding of the training continuum, which involves constructing the definitions of the training requirements, resources and policy objectives. An end-to-end model of the continuum is easy to relate to, while dynamic visualisation of system behaviour provides a method for exploration of the model. DES was used for micro level exploration of an individual school within the training continuum to capture the physical aspects of the system including resource capacity requirements, bottlenecks and student waiting times. It was also used to model stochastic events such as weather and student availability. DES has the advantage of being able to represent system variability and accurately reflect the limitations imposed on a system by resource constraints. Through sharing results between the models, we demonstrate a multi-level approach to the analysis of the overall continuum. The SD model provides the school’s targeted demand to the DES model. The detailed DES model is able to assess schedules in the presence of resource constraints and variability and provide the expected capacity of a school to the high level SD model, subjected to constraints such as instructor availability or budgeted number of training systems. The SD model allows stakeholders to assess how policy and planning affect the continuum, both in the short and the long term. The development of this approach permits moving the analysis of the continuum between SD and DES models as appropriate for given system entities, scales and tasks. The resultant model outcomes are propagated between the continuum and the detailed DES model, iteratively generating an assessment of the entire set of plans and schedule across the continuum. Combining data and information between SD and DES models and techniques assures relevance to the stakeholder needs and effective problem scoping and scaling that can also evolve with dynamic architecture and policy requirements. An example case study shows the combined use of the two models and how they are used to evaluate a typical scenario where increased demand is placed on the training continuum. The multi-level approach provides a high level indication of training requirements to the model of the new training school, where the detailed model indicates the resources required to achieve those particular student levels.

article Free Access Share on The software engineering process: definition and scope Author: W. S. Humphrey Software Engineering Institute, Carnegie-Mellon University Software Engineering Institute, Carnegie-Mellon UniversityView Profile Authors Info & Claims ACM SIGSOFT Software Engineering NotesVolume 14Issue 4June 1989 pp 82–83https://doi.org/10.1145/75111.75122Online:01 April 1988Publication History 23citation2,737DownloadsMetricsTotal Citations23Total Downloads2,737Last 12 Months164Last 6 weeks13 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Many problematic outcomes in agricultural and food systems have important dynamic dimensions and arise due to underlying system structure. Thus, understanding the linkages between system structure and dynamic behavior often is important for the design and implementation of interventions to achieve sustained improvements. System Dynamics (SD) modeling represents system structure using stock-flow-feedback structures expressed as systems of differential equations solved by numerical integration methods. SD methods also encompass a broader methodological approach that emphasizes model structural development and data inputs to replicate one of a limited number of problematic behavioral modes, anticipates dynamic complexity and focuses on feedback processes arising from endogenous system elements. A variety of data sources may be used in SD model development, and parametric sensitivity analysis with SD models can determine priority information needs in feedback-rich systems when data are lacking. Although numerous applications of SD modeling to agriculture exist, the approach is underutilized as a useful tool for research, instruction and programmatic development. This presentation highlights key elements of SD modeling using two examples from animal agriculture at different scales. A dynamic version of the Cornell Net Carbohydrate and Protein System (CNCPS) that represents outcomes for an individual dairy cow is formulated as an SD model, and illustrates the benefits of the SD approach in animal nutrition research and for farm-level nutritional management decisions. At a very different scale, an SD model of the Brazilian dairy supply chain (farms, processing and consumers) illustrates the country-level impacts of efforts to improve cow productivity and how impacts differ if productivity improvement occurs on small farms rather than large farms. The presentation concludes with recommendations to increase awareness and training is SD methods to enhance its appropriate use in research and instruction.