Our worst current development practices

Successful software projects can result from avoiding the more serious mistakes that lead to disaster. Specifically, we must look at the actual results of similar projects; make planning and estimating formal activities; plan for and control creeping requirements; use formal inspections as milestones for tracking project progress and software disasters; and collect accurate measurement data, during the current project, to use with future projects. There is no substitute for solid empirical data used by capable project managers who are supported by automated estimating and planning tools. This combination can almost always be successful. By contrast, no data at all, unprepared managers, and manual estimating and planning are consistently characteristic of our industry's major software disasters     

Could large UK corporations and computing companies use software cost estimating tools? – a survey

Software cost estimating tools were developed to address the problem of estimating the size and cost of software projects. Recent surveys, however, have shown that few managers use such tools. This survey formulated and tested a number of propositions in order to explain this apparent lack of use. Large UK corporations and computing companies were targeted, since it was believed that such companies would give more information on the use of estimating tools. It was found that while almost all saw estimation as a problem and used some form of project planning tool, fewer than a third used any form of estimating tool. The lack of a framework to support their development and use, and a failure of publicity on the part of the vendors, appear to be the two most common explanations for the non-use of estimating tools. However, it seems that a substantial proportion of companies which could use estimating tools simply choose not to do so.     

A Planning Framework for Systems Development Projects

As part of any systems development project, JS professionals must perform a variety of tasks. One such important task, estimating, is often done incorrectly and, as a result, can lead to errors in the final system or a cancellation of the project. To estimate projects accurately, data on previous project estimates should be readily available. This article describes a systems development planning framework that essentially creates an estimating knowledge data base, which enables IS managers to prepare better project plans.     

A Rule-Based Approach to Developing Software Development Prediction Models

Managers of software development projects increasingly recognize the importance of planning and estimation and now have many sophisticated tools at their disposal. Despite this many systems are still delivered way behind schedule, cost far more to produce than original budget estimates and fail to meet user requirements.It is the contention of the authors that many existing tools are inadequate because they fail to embrace the significant body of knowledge accumulated by past and present project managers.This paper presents a new approach to planning which enables project managers to learn from the experience of others. The authors have adopted a bottom-up approach to planning which goes from the specific (planning the requirements capture and analysis process—RCA) to the general (planning the whole development process). A model, called MARCS, was constructed to give predictions of the resources (time, effort, cost, people) needed for the completion of and outcomes of the RCA process. Based on the predictions about the RCA process, the model then attempts to predict the resources and outcomes of the whole development process. MARCS is a combination of rule-based models and its main advantage is that it incorporates both qualitative and quantitative factors that can be easily identified and measured in the beginning of the development process.Empirical data concerning 107 projects developed by more than 70 organizations within UK, gathered through a two-stage mail survey was used for the construction and validation of the MARCS planning model.     

Toward High Confidence Software

Moving toward high confidence software that can meet ever increasing demands for critical DOD applications will require planning, specifying, selecting, and managing the necessary development and testing activities that will ensure the success of the software project. In order to trust the decisions being made, there must be evidence (i.e., an information base of data and facts) that techniques and tools being chosen for application on critical projects will perform as expected. Today, these expectations are mostly intuitive; there is little hard evidence available to guide acquisition managers and software developers in making necessary decisions.     

Tools to Improve the Production of Emergency Plans for Floods: Are They Being Used by the People that Need Them?

Recently emergency plans for floods have started to be developed in England and France. At present, tools, such as checklists, guidance and specialized software appear to be used rarely to improve the effectiveness of these plans. Research was undertaken with flood managers in the two countries. The objective was to establish why tools that can usefully contribute to improving emergency plans for floods are often not being used. Many flood managers are not aware of the tools that are available to assist them in formulating emergency plans for floods. It was concluded that there is a need for guidance on the tools and how they can be used to help to improve emergency planning for floods.     

测算在软件开发中的实践①

软件测算是软件开发工程化管理的重要技术。但软件本身的复杂性、历史经验的缺乏、估算工具不完备性以及人为错误,导致软件项目的估算结果往往和实际情况相差甚远。为了改进测算结果,根据软件生命周期理论,结合COCOMOⅡ模型,指出了软件开发模型中的关键测算点及相应可采用的测算方法,并且明确了软件测算人员应具备的素质要求及在典型的软件组织中的地位。最后通过实例,使用USC提供的一个免费软件测算工具对一个具体的软件项目进行测算,较好地控制开发过程。     

Estimating,planning and managing Agile Web development projects under a value-based perspective

ContextThe processes of estimating, planning and managing are crucial for software development projects, since the results must be related to several business strategies. The broad expansion of the Internet and the global and interconnected economy make Web development projects be often characterized by expressions like delivering as soon as possible, reducing time to market and adapting to undefined requirements. In this kind of environment, traditional methodologies based on predictive techniques sometimes do not offer very satisfactory results. The rise of Agile methodologies and practices has provided some useful tools that, combined with Web Engineering techniques, can help to establish a framework to estimate, manage and plan Web development projects.ObjectiveThis paper presents a proposal for estimating, planning and managing Web projects, by combining some existing Agile techniques with Web Engineering principles, presenting them as an unified framework which uses the business value to guide the delivery of features.MethodThe proposal is analyzed by means of a case study, including a real-life project, in order to obtain relevant conclusions.ResultsThe results achieved after using the framework in a development project are presented, including interesting results on project planning and estimation, as well as on team productivity throughout the project.ConclusionIt is concluded that the framework can be useful in order to better manage Web-based projects, through a continuous value-based estimation and management process.     

Management competences,not tools and techniques: A grounded examination of software project management at WM-data

Traditional software project management theory often focuses on desk-based development of software and algorithms, much in line with the traditions of the classical project management and software engineering. This can be described as a tools and techniques perspective, which assumes that software project management success is dependent on having the right instruments available, rather than on the individual qualities of the project manager or the cumulative qualities and skills of the software organisation. Surprisingly, little is known about how (or whether) these tools techniques are used in practice. This study, in contrast, uses a qualitative grounded theory approach to develop the basis for an alternative theoretical perspective: that of competence. A competence approach to understanding software project management places the responsibility for success firmly on the shoulders of the people involved, project members, project leaders, managers. The competence approach is developed through an investigation of the experiences of project managers in a medium sized software development company (WM-data) in Denmark. Starting with a simple model relating project conditions, project management competences and desired project outcomes, we collected data through interviews, focus groups and one large plenary meeting with most of the company’s project managers. Data analysis employed content analysis for concept (variable) development and causal mapping to trace relationships between variables. In this way we were able to build up a picture of the competences project managers use in their daily work at WM-data, which we argue is also partly generalisable to theory. The discrepancy between the two perspectives is discussed, particularly in regard to the current orientation of the software engineering field. The study provides many methodological and theoretical starting points for researchers wishing to develop a more detailed competence perspective of software project managers’ work.     

Estimating Freight Flows for Metropolitan Area Highway Networks Using Secondary Data Sources

We present a method for estimating intra-metropolitan freight flows on a highway network. The work is part of a larger project aimed at developing an automated, integrated system for freight flow analysis and planning. To overcome the limitations of current estimation methods for commodity flows, we use reliable secondary sources, including small-area employment data, and derive estimates in a plausible way by means of a computational workflow. When available, we extract the data automatically from online sources, so that estimations can be continuously updated. Using widely available data sources allows for transferability. In this paper we provide an overview of our modeling approach and the major data sources used. We apply the model using data from the Los Angeles region, and compare our traffic assignment results with available screenline counts. Results are encouraging. Our approach should be easily applied to other metropolitan areas, allowing planners and policymakers to make more informed decisions by utilizing the most recent data from many sources and enhancing the ability to explore different scenarios.     

Evaluating and selecting testing tools

A system using process and forms to give managers and tool evaluators a reliable way to identify the tool that best fits their organization's needs is discussed. It is shown that a tool evaluator must analyze user needs, establish selection criteria (including general criteria, environment-dependent criteria, tool-dependent functional criteria, tool-dependent nonfunctional criteria, and weighting), search for tools, select the tools, and then reevaluate the tools. Forms for recording tool selection criteria, classifying testing tools, profiling tool-to-organization interconnections, creating hardware and software profiles, and creating tool-interconnection profiles are presented. It is argued that, with these forms, evaluators have a reasonably accurate and consistent system for identifying and quantifying user needs, establishing tool-selection criteria, finding available tools, and selecting tools and estimating return on investment     

A controlled experiment to assess the benefits of estimating with analogy and regression models

To have general validity, empirical results must converge. To be credible, an experimental science must understand the limitations and be able to explain the disagreements of empirical results. We describe an experiment to replicate previous studies which claim that estimation by analogy outperforms regression models. In the experiment, 68 experienced practitioners each estimated a project from a dataset of 48 industrial COTS projects. We applied two treatments, an analogy tool and a regression model, and we used the estimating performance when aided by the historical data as the control. We found that our results do not converge with previous results. The reason is that previous studies have used other datasets and partially different data analysis methods, and last but not least, the tools have been validated in isolation from the tool users. This implies that the results are sensitive to the experimental design: the characteristics of the dataset, the norms for removing outliers and other data points from the original dataset, the test metrics, significance levels, and the use of human subjects and their level of expertise. Thus, neither our results nor previous results are robust enough to claim any general validity.     

A quantitative model for the support of software management

The software production and maintenance management support project (SPMMS) will define and produce a complete, consistent and efficient information system supporting all management activities in the life cycle of software.Adequate management of the production and maintenance of software can be achieved only with the support of quantitative analysis. This analysis must examine all attributes of the process by which software is developed and maintained. Initial results are available of an investigation into the use of quantitative models within an SPMMS.There are several issues and problems of project management. Existing models for cost and some approaches to the measurement of quality have disadvantages. An experience database helps estimating and planning and control. Criteria for model selection can be given (as a basis for assessing external and internal models). A CQA model is incorporated within SPMMS. This is part of the SPMMS approach to integrated and automatic management support.     

Managing uncertainty in project portfolio cost estimation

Although typically a software development organisation is involved in more than one project simultaneously, the available tools in the area of software cost estimation deal mostly with single software projects. In order to calculate the possible cost of the entire project portfolio, one must combine the single project estimates taking into account the uncertainty involved. In this paper, statistical simulation techniques are used to calculate confidence intervals for the effort needed for a project portfolio. The overall approach is illustrated through the adaptation of the analogy-based method for software cost estimation to cover multiple projects.     

Reconciling user and project manager perceptions of IT project risk: a Delphi study1

Abstract. In an increasingly dynamic business environment characterized by fast cycle times, shifting markets and unstable technology, a business organization’s survival hinges on its ability to align IT capabilities with business goals. To facilitate the successful introduction of new IT applications, issues of project risk must be addressed, and the expectations of multiple stakeholders must be managed appropriately. To the extent that users and developers may harbour different perceptions regarding project risk, areas of conflict may arise. By understanding the differences in how users and project managers perceive the risks, insights can be gained that may help to ensure the successful delivery of systems. Prior research has focused on the project manager’s perspective of IT project risk. This paper explores the issue of IT project risk from the user perspective and compares it with risk perceptions of project managers. A Delphi study reveals that these two stakeholder groups have different perceptions of risk factors. Through comparison with a previous study on project manager risk perceptions, zones of concordance and discordance that must be reconciled are identified.     

Cybersecurity Economic Issues: Clearing the Path to Good Practice

Software project managers have limited project resources. Requests for security improvements must compete with other requests, such as for new tools, more staff, or additional testing. Deciding how and whether to invest in cybersecurity protection requires knowing the answer to at least two questions: What is the likelihood of an attack, and what are its likely consequences? Security analysts understand a system's vulnerability to potential cyberattacks fairly well, but to date, research on the economic consequences of cyberattacks has been limited, dealing primarily with microanalyses of attacks' direct impacts on a particular organization. Many managers recognize the significant potential of a cyberattack's effects to cascade from one computer or business system to another, but there have been no significant efforts to develop a methodology to account for both direct and indirect costs. Without such a methodology, project managers and their organizations are hard pressed to make informed decisions about how much to invest in cybersecurity and how to ensure that security resources are used effectively. In this article, we explore how others have sought answers to our two questions. We describe the data available to inform decisions about investing in cybersecurity and look at research models of the trade-offs between investment and protection. The framework we present can help project managers find appropriate models with credible data so that they can make effective security decisions.     

Assessing effort estimation models for corrective maintenance through empirical studies

We present an empirical assessment and improvement of the effort estimation model for corrective maintenance adopted in a major international software enterprise. Our study was composed of two phases. In the first phase we used multiple linear regression analysis to construct effort estimation models validated against real data collected from five corrective maintenance projects. The model previously adopted by the subject company used as predictors the size of the system being maintained and the number of maintenance tasks. While this model was not linear, we show that a linear model including the same variables achieved better performances. Also we show that greater improvements in the model performances can be achieved if the types of the different maintenance tasks is taken into account. In the second phase we performed a replicated assessment of the effort prediction models built in the previous phase on a new corrective maintenance project conducted by the subject company on a software system of the same type as the systems of the previous maintenance projects. The data available for the new project were finer grained, according to the indications devised in the first study. This allowed to improve the confidence in our previous empirical analysis by confirming most of the hypotheses made. The new data also provided other useful indications to better understand the maintenance process of the company in a quantitative way.     

A top-down approach to integrating the building process

Many computer-aided tools have been developed to assist designers, engineers, and managers with specific well-defined functions, yet they are not well integrated. This paper develops the need for an information architecture to integrate the processes and subsequent software used throughout the life of a building. It then defines a process model of the functions required to provide a facility to the end user, namely, managing, planning, designing, constructing, and operating the facility.This process model implies that the proposed information architecture must support the life-cycle process, effectively capture knowledge, and act as an integrator of industry accepted decision-making tools. Finally, a knowledge-based approach to implementing the information architecture is propsed.     

Comparing the top-down and bottom-up approaches of function point analysis: a case study

Function point analysis is a widely cited method for estimating software project size, which is an important activity of project management. At the beginning stage of planning, the top-down approach can be applied. Having obtained more systems specifications at later stages, the bottom-up approach might also be used to improve the accuracy of the estimation. However, the bottom-up approach is not a conventional way of function point analysis. There was no empirical evidence showing the difference between the fully informed top-down approach and the bottom-up approach. Through the implementation of a function point analysis system in an in-house software development department, this paper compares the results of the two approaches. This comparison study shows that the bottom-up approach does not contribute a significant added value to a fully-informed top-down approach. Therefore, the fully-informed top down approach has been chosen as a method for building a software metric database in the organization. More important, the observations and experience gained from this project may help in-house development organizations to establish their own function point analysis systems.     

Supporting Community Emergency Management Planning through a Geocollaboration Software Architecture

Emergency management is more than just events occurring within an emergency situation. It encompasses a variety of persistent activities such as planning, training, assessment, and organizational change. We are studying emergency management planning practices in which geographic communities (towns and regions) prepare to respond efficiently to significant emergency events. Community emergency management planning is an extensive collaboration involving numerous stakeholders throughout the community and both reflecting and challenging the community’s structure and resources. Geocollaboration is one aspect of the effort. Emergency managers, public works directors, first responders, and local transportation managers need to exchange information relating to possible emergency event locations and their surrounding areas. They need to examine geospatial maps together and collaboratively develop emergency plans and procedures. Issues such as emergency vehicle traffic routes and staging areas for command posts, arriving media, and personal first responders’ vehicles must be agreed upon prior to an emergency event to ensure an efficient and effective response. This work presents a software architecture that facilitates the development of geocollaboration solutions. The architecture extends prior geocollaboration research and reuses existing geospatial information models. Emergency management planning is one application domain for the architecture. Geocollaboration tools can be developed that support community-wide emergency management planning and preparedness. This paper describes how the software architecture can be used for the geospatial, emergency management planning activities of one community.