Cocomo II as productivity measurement: a case study at KBC.

Software productivity is generally measured as the ratio of size over effort, whereby several techniques exist to measure the size. In this paper, we propose the innovative approach to use an estimation model as productivity measurement. This approach is applied in a case-study at the ICT-department of a bank and insurance company. The estimation model, in this case Cocomo II, is used as the norm to judge about productivity of application development projects. This research report describes on the one hand the set-up process of the measurement environment and on the other hand the measurement results. To gain insight in the measurement data, we developed a report which makes it possible to identify productivity improvement areas in the development process of the case-study company.

Enhancing Software Team Planning and Delivery Performance using Agile Driven Quality Measures: Approach, Results, and Recommendations

Implementing a performance-management program in an agile software-development organization is important to retain sight of software team performance as a whole as well as linking performance-management metrics to business value. The evaluation criteria for software engineers’ performance have been traditionally driven by metrics that don’t fit into agile-development principles. This research implements a measurement metric that aligns with agile-development core values and principles to evaluate engineers in a software engineering firm using the Scrum development method. The research focused on measuring and evaluating the productivity, development efficiency, social skills, team collaboration and breadth of knowledge. Observing the Productivity Index (PI), Actual Productivity for software Engineers (APSE), and Productivity Variance (PV) for individual software engineers and the development team at the end of each sprint helped the development team have a better understanding of its productivity levels in a matter that facilitated planning future sprints. In addition, this productivity measure helped early identification of productivity challenges encountered by several software engineers and productivity identification of productivity challenges encountered by several software engineers. Keywords: Agile development, software teams, process measurement, scrum, productivity, efficiency, software metrics, software project measuremen

Estimating Productivity of Software Development Using the Total Factor Productivity Approach

The design, control and optimization of software engineering processes generally require the determination of performance measures such as efficiency or productivity. However, the definition and measurement of productivity is often inaccurate and differs from one method to another. On the other hand, economic theory offers a well‐grounded tool of productivity measurement. In this article, we propose a model of process productivity measurement based on the total factor productivity (TFP) approach commonly used in economics. In the first part of the article, we define productivity and its measurement. We also discuss the major data issues which have to be taken into consideration. Consequently, we apply the TFP approach in the domain of software engineering and we propose a TFP model of productivity assessment

Quantifying Functional Reuse from Object Oriented Requirements Specifications

Software reuse is essential in improving efficiency and productivity in the software development process. This paper analyses reuse within requirements engineering phase by taking and adapting a standard functional size measurement method, COSMIC FFP. Our proposal attempts to quantify reusability from Object Oriented requirements specifications by identifying potential primitives with a high level of reusability and applying a reuse indicator. These requirements are specified using OO-Method, an automatic software production method based on transformation models. We illustrate the application of our proposal in a Car Rental real system

TRACKING THE 'LIFE CYCLE TRAJECTORY': METRICS AND MEASURES FOR CONTROLLING PRODUCTIVITY OF COMPUTER AIDED SOFTWARE ENGINEERING (CASE) DEVELOPMENT

This paper proposes a new vision for the measurement and management of development productivity related to computer aided software engineering (CASE) technology. We propose that productivity be monitored and controlled in each phase of software development life cycle, a measurement approach we have termed life cycle trajectory measurement. Recent advances in CASE technology that make low cost automated measurement possible have made it feasible to collect life cycle trajectory measures. We suggest that current approaches for productivity management involve the use of static metrics that are available only at the beginning and end of the project. Yet the depth of the insights needed to make proactive adjustments in the software development process requires monitoring the range of activities across the entire software development life cycle. This can only be accomplished with metrics that can measure performance parameters in each phase of the life cycle. We develop metrics that have the ability to measure and estimate software outputs from each intermediate phase of the development life cycle. These metrics are based on a count of the objects and modules that are used as building blocks for application development in repository object-based CASE environments. The viability of such object-based metrics for life cycle trajectory measurement has been empirically tested for the software construction phase using project data generated in Integrated CASE development environments.Information Systems Working Papers Serie

Deducing software process improvement areas from a Cocomo II-based productivity measurement.

At the SMEF2006 conference, we presented our experiences with the set-up of a measurement environment using the COCOMO II-model for software development projects in a company in the banking and insurance area. The set-up was part of a larger research project on managing efficiency aspects of software factory systems. One year of measurements later, a database of 22 projects is obtained. In this paper we will present our conclusions and findings after these first measurement results. The effort multipliers in the COCOMO II-model represent the factors that have a linear influence on the amount of effort needed for a project. As such, they are a management instrument that gives an indication which parameters need attention within the company in order to improve the productivity. In this paper, we discuss a new kind of report we constructed in order to visualise the influence of the different effort multipliers. The goal of the report is two folded. Firstly, one can check whether the factors identified by the COCOMO II-model as effort multipliers indeed have an influence on the effort and therefore on the productivity of a project in this company. And secondly, one can check whether the amount of influence identified by the COCOMO II-model is comparable with the influence we detect in the company. As we will show, even though there was only data available of one year of measurement, useful interpretations could already be given to the results as well as indications about which areas of the software development process need to be focused on in order to improve the productivity.

Estimation of Defect proneness Using Design complexity Measurements in Object- Oriented Software

Software engineering is continuously facing the challenges of growing complexity of software packages and increased level of data on defects and drawbacks from software production process. This makes a clarion call for inventions and methods which can enable a more reusable, reliable, easily maintainable and high quality software systems with deeper control on software generation process. Quality and productivity are indeed the two most important parameters for controlling any industrial process. Implementation of a successful control system requires some means of measurement. Software metrics play an important role in the management aspects of the software development process such as better planning, assessment of improvements, resource allocation and reduction of unpredictability. The process involving early detection of potential problems, productivity evaluation and evaluating external quality factors such as reusability, maintainability, defect proneness and complexity are of utmost importance. Here we discuss the application of CK metrics and estimation model to predict the external quality parameters for optimizing the design process and production process for desired levels of quality. Estimation of defect-proneness in object-oriented system at design level is developed using a novel methodology where models of relationship between CK metrics and defect-proneness index is achieved. A multifunctional estimation approach captures the correlation between CK metrics and defect proneness level of software modules.Comment: 5 pages, 1 figur

New Data and Output Concepts for Understanding Productivity Trends

The present study is the second is a series of three papers devoted to issues in the measurement of productivity and productivity growth. The contributions of the present paper are three. First, it introduces a new approach to measuring industrial productivity based on income-side data that are published by the Bureau of Economic Analysis (BEA). The data are internally consistent in that both inputs and outputs are income-side measures of value added, whereas the usual productivity measures combine expenditure-side output measures with income-side input measures. Second, because of interest in the "new economy," we have also constructed a set of new- economy accounts. For the purpose of this study, we define the new economy as machinery, electric equipment, telephone and telegraph, and software. Finally, because of concerns about poor deflation in the current output measures, this study constructs a new output concept called "well-measured output," which includes only those sectors for which output is relatively well measured. We present a brief summary of the behavior of the alternative measures.Productivity, new economy, price measurement, well-measured output