Playing Planning Poker in Crowds: Human Computation of Software Effort Estimates

Reliable cost effective effort estimation remains a considerable challenge for software projects. Recent work has demonstrated that the popular Planning Poker practice can produce reliable estimates when undertaken within a software team of knowledgeable domain experts. However, the process depends on the availability of experts and can be time-consuming to perform, making it impractical for large scale or open source projects that may curate many thousands of outstanding tasks. This paper reports on a full study to investigate the feasibility of using crowd workers supplied with limited information about a task to provide comparably accurate estimates using Planning Poker. We describe the design of a Crowd Planning Poker (CPP) process implemented on Amazon Mechanical Turk and the results of a substantial set of trials, involving more than 5000 crowd workers and 39 diverse software tasks. Our results show that a carefully organised and selected crowd of workers can produce effort estimates that are of similar accuracy to those of a single expert

An Empirical Study of Meta- and Hyper-Heuristic Search for Multi-Objective Release Planning

A variety of meta-heuristic search algorithms have been introduced for optimising software release planning. However, there has been no comprehensive empirical study of different search algorithms across multiple different real-world datasets. In this article, we present an empirical study of global, local, and hybrid meta- and hyper-heuristic search-based algorithms on 10 real-world datasets. We find that the hyper-heuristics are particularly effective. For example, the hyper-heuristic genetic algorithm significantly outperformed the other six approaches (and with high effect size) for solution quality 85% of the time, and was also faster than all others 70% of the time. Furthermore, correlation analysis reveals that it scales well as the number of requirements increases

Search based software engineering: Trends, techniques and applications

© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

Relationship between mature software engineering practices and agility practices

This paper reports on research work on Argentinean software development organizations. The analysis pro-vides insights on the profile of the companies regarding the usage of agile methods and software engineering practices trends, their motivations, and drivers. The conclusions can be used to understand what drivers facilitate the understanding of bonds between both in order to increase their competitiveness in domestic and off-shore markets.Sociedad Argentina de Informática e Investigación Operativ

Web Framework Points: an Effort Estimation Methodology for Web Application Development

Software effort estimation is one of the most critical components of a successful software project: completing the project on time and within budget is the classic challenge for all project managers. However, predictions made by project managers about their project are often inexact: software projects need, on average, 30-40% more effort than estimated. Research on software development effort and cost estimation has been abundant and diversified since the end of the Seventies. The topic is still very much alive, as shown by the numerous works existing in the literature. During these three years of research activity, I had the opportunity to go into the knowledge and to experiment some of the main software effort estimation methodologies existing in literature. In particular, I focused my research on Web effort estimation. As stated by many authors, the existing models for classic software applications are not well suited to measure the effort of Web applications, that unfortunately are not exempt from cost and time overruns, as traditional software projects. Initially, I compared the effectiveness of Albrecht's classic Function Points (FP) and Reifer's Web Objects (WO) metrics in estimating development effort for Web applications, in the context of an Italian software company. I tested these metrics on a dataset made of 24 projects provided by the software company between 2003 and 2010. I compared the estimate data with the real effort of each project completely developed, using the MRE (Magnitude of Relative Error) method. The experimental results showed a high error in estimates when using WO metric, which proved to be more effective than the FP metric in only two occurrences. In the context of this first work, it appeared evident that effort estimation depends not only on functional size measures, but other factors had to be considered, such as model accuracy and other challenges specific to Web applications; though the former represent the input that influences most the final results. For this reason, I revised the WO methodology, creating the RWO methodology. I applied this methodology to the same dataset of projects, comparing the results to those gathered by applying the FP and WO methods. The experimental results showed that the RWO method reached effort prediction results that are comparable to – and in 4 cases even better than – the FP method. Motivated by the dominant use of Content Management Framework (CMF) in Web application development and the inadequacy of the RWO method when used with the latest Web application development tools, I finally chose to focus my research on the study of a new Web effort estimation methodology for Web applications developed with a CMF. I proposed a new methodology for effort estimation: the Web CMF Objects one. In this methodology, new key elements for analysis and planning were identified; they allow to define every important step in the development of a Web application using a CMF. Following the RWO method approach, the estimated effort of a Web project stems from the sum of all elements, each of them weighted with its own complexity. I tested the whole methodology on 9 projects provided by three different Italian software companies, comparing the value of the effort estimate to the actual, final effort of each project, in man-days. I then compared the effort estimate both with values obtained from the Web CMF Objects methodology and with those obtained from the respective effort estimation methodologies of the three companies, getting excellent results: a value of Pred(0.25) equal to 100% for the Web CMF Objects methodology. Recently, I completed the presentation and assessment of Web CMF Objects methodology, upgrading the cost model for the calculation of effort estimation. I named it again Web Framework Points methodology. I tested the updated methodology on 19 projects provided by three software companies, getting good results: a value of Pred(0.25) equal to 79%. The aim of my research is to contribute to reducing the estimation error in software development projects developed through Content Management Frameworks, with the purpose to make the Web Framework Points methodology a useful tool for software companies

Un Procedimiento de Medición de Tamaño Funcional para Modelos Conceptuales en entornos MDA

Esta tesis presenta el diseño, la aplicación y la automatización de un procedimiento de medición de tamaño funcional basado en el método COSMIC, que permite medir el tamaño funcional de aplicaciones generadas en entornos MDA en sus modelos conceptuales.Marín Campusano, BM. (2008). Un Procedimiento de Medición de Tamaño Funcional para Modelos Conceptuales en entornos MDA. http://hdl.handle.net/10251/12305Archivo delegad

Towards making functional size measurement easily usable in practice

Functional Size Measurement methods \u2013like the IFPUG Function Point Analysis and COSMIC methods\u2013 are widely used to quantify the size of applications. However, the measurement process is often too long or too expensive, or it requires more knowledge than available when development effort estimates are due. To overcome these problems, simplified measurement methods have been proposed. This research explores easily usable functional size measurement method, aiming to improve efficiency, reduce difficulty and cost, and make functional size measurement widely adopted in practice. The first stage of the research involved the study of functional size measurement methods (in particular Function Point Analysis and COSMIC), simplified methods, and measurement based on measurement-oriented models. Then, we modeled a set of applications in a measurement-oriented way, and obtained UML models suitable for functional size measurement. From these UML models we derived both functional size measures and object-oriented measures. Using these measures it was possible to: 1) Evaluate existing simplified functional size measurement methods and derive our own simplified model. 2) Explore whether simplified method can be used in various stages of modeling and evaluate their accuracy. 3) Analyze the relationship between functional size measures and object oriented measures. In addition, the conversion between FPA and COSMIC was studied as an alternative simplified functional size measurement process. Our research revealed that: 1) In general it is possible to size software via simplified measurement processes with acceptable accuracy. In particular, the simplification of the measurement process allows the measurer to skip the function weighting phases, which are usually expensive, since they require a thorough analysis of the details of both data and operations. The models obtained from out dataset yielded results that are similar to those reported in the literature. All simplified measurement methods that use predefined weights for all the transaction and data types identified in Function Point Analysis provided similar results, characterized by acceptable accuracy. On the contrary, methods that rely on just one of the elements that contribute to functional size tend to be quite inaccurate. In general, different methods showed different accuracy for Real-Time and non Real-Time applications. 2) It is possible to write progressively more detailed and complete UML models of user requirements that provide the data required by the simplified COSMIC methods. These models yield progressively more accurate measures of the modeled software. Initial measures are based on simple models and are obtained quickly and with little effort. As V models grow in completeness and detail, the measures increase their accuracy. Developers that use UML for requirements modeling can obtain early estimates of the applications\u2018 sizes at the beginning of the development process, when only very simple UML models have been built for the applications, and can obtain increasingly more accurate size estimates while the knowledge of the products increases and UML models are refined accordingly. 3) Both Function Point Analysis and COSMIC functional size measures appear correlated to object-oriented measures. In particular, associations with basic object- oriented measures were found: Function Points appear associated with the number of classes, the number of attributes and the number of methods; CFP appear associated with the number of attributes. This result suggests that even a very basic UML model, like a class diagram, can support size measures that appear equivalent to functional size measures (which are much harder to obtain). Actually, object-oriented measures can be obtained automatically from models, thus dramatically decreasing the measurement effort, in comparison with functional size measurement. In addition, we proposed conversion method between Function Points and COSMIC based on analytical criteria. Our research has expanded the knowledge on how to simplify the methods for measuring the functional size of the software, i.e., the measure of functional user requirements. Basides providing information immediately usable by developers, the researchalso presents examples of analysis that can be replicated by other researchers, to increase the reliability and generality of the results

Identifying and Addressing Critical Issues in the Indian Construction Industry: Perspectives of Large Building Construction Clients

The Indian construction industry faces increasing challenges amidst serious performance shortfalls. Confronting similar issues in past decades, other countries such as the UK, USA, and Singapore commissioned high-powered studies and set up industry development bodies to address their own priorities. Initiatives in other countries are briefly reviewed before outlining the launch of the “Construction Industry Improvement Initiative India” (Ci3 India) that aims to address our own challenges. This paper focuses on identifying and launching a platform to address the current and imminent critical issues in the Indian Construction Industry. Nineteen critical issues were identifed, verifed, and validated through four focus group sessions at two Regional Roundtables with 54 high calibre large building construction clients, academicians, and other invited experts. The identifed issues were consolidated to 10 Action Items. Seven Action Teams were then mobilized to work on the 10 Action Items. Having consolidated a base consensus of clients on the way forward, it was also proposed to develop a “Construction Clients’ Charter” that will set out basic principles, protocols, and targeted good practices by lead clients, who by voluntarily agreeing and implementing these together, could catalyse signifcant industry improvement

Impact estimation: IT priority decisions

Given resource constraints, prioritization is a fundamental process within systems engineering to decide what to implement. However, there is little guidance about this process and existing IT prioritization methods have several problems, including failing to adequately cater for stakeholder value. In response to these issues, this research proposes an extension to an existing prioritization method, Impact Estimation (IE) to create Value Impact Estimation (VIE). VIE extends IE to cater for multiple stakeholder viewpoints and to move towards better capture of explicit stakeholder value. The use of metrics offers VIE the means of expressing stakeholder value that relates directly to real world data and so is informative to stakeholders and decision makers. Having been derived from prioritization factors found in the literature, stakeholder value has been developed into a multi-dimensional, composite concept, associated with other fundamental system concepts: objectives, requirements, designs, increment plans, increment deliverables and system contexts. VIE supports the prioritization process by showing where the stakeholder value resides for the proposed system changes. The prioritization method was proven to work by exposing it to three live projects, which served as case studies to this research. The use of the extended prioritization method was seen as very beneficial. Based on the three case studies, it is possible to say that the method produces two major benefits: the calculation of the stakeholder value to cost ratios (a form of ROI) and the system understanding gained through creating the VIE table

Towards making functional size measurement easily usable in practice

Functional Size Measurement methods –like the IFPUG Function Point Analysis and COSMIC methods– are widely used to quantify the size of applications. However, the measurement process is often too long or too expensive, or it requires more knowledge than available when development effort estimates are due. To overcome these problems, simplified measurement methods have been proposed. This research explores easily usable functional size measurement method, aiming to improve efficiency, reduce difficulty and cost, and make functional size measurement widely adopted in practice. The first stage of the research involved the study of functional size measurement methods (in particular Function Point Analysis and COSMIC), simplified methods, and measurement based on measurement-oriented models. Then, we modeled a set of applications in a measurement-oriented way, and obtained UML models suitable for functional size measurement. From these UML models we derived both functional size measures and object-oriented measures. Using these measures it was possible to: 1) Evaluate existing simplified functional size measurement methods and derive our own simplified model. 2) Explore whether simplified method can be used in various stages of modeling and evaluate their accuracy. 3) Analyze the relationship between functional size measures and object oriented measures. In addition, the conversion between FPA and COSMIC was studied as an alternative simplified functional size measurement process. Our research revealed that: 1) In general it is possible to size software via simplified measurement processes with acceptable accuracy. In particular, the simplification of the measurement process allows the measurer to skip the function weighting phases, which are usually expensive, since they require a thorough analysis of the details of both data and operations. The models obtained from out dataset yielded results that are similar to those reported in the literature. All simplified measurement methods that use predefined weights for all the transaction and data types identified in Function Point Analysis provided similar results, characterized by acceptable accuracy. On the contrary, methods that rely on just one of the elements that contribute to functional size tend to be quite inaccurate. In general, different methods showed different accuracy for Real-Time and non Real-Time applications. 2) It is possible to write progressively more detailed and complete UML models of user requirements that provide the data required by the simplified COSMIC methods. These models yield progressively more accurate measures of the modeled software. Initial measures are based on simple models and are obtained quickly and with little effort. As V models grow in completeness and detail, the measures increase their accuracy. Developers that use UML for requirements modeling can obtain early estimates of the applications‘ sizes at the beginning of the development process, when only very simple UML models have been built for the applications, and can obtain increasingly more accurate size estimates while the knowledge of the products increases and UML models are refined accordingly. 3) Both Function Point Analysis and COSMIC functional size measures appear correlated to object-oriented measures. In particular, associations with basic object- oriented measures were found: Function Points appear associated with the number of classes, the number of attributes and the number of methods; CFP appear associated with the number of attributes. This result suggests that even a very basic UML model, like a class diagram, can support size measures that appear equivalent to functional size measures (which are much harder to obtain). Actually, object-oriented measures can be obtained automatically from models, thus dramatically decreasing the measurement effort, in comparison with functional size measurement. In addition, we proposed conversion method between Function Points and COSMIC based on analytical criteria. Our research has expanded the knowledge on how to simplify the methods for measuring the functional size of the software, i.e., the measure of functional user requirements. Basides providing information immediately usable by developers, the researchalso presents examples of analysis that can be replicated by other researchers, to increase the reliability and generality of the results