Cost-benefit analysis for software process improvement

Justification of investments to improve software development processes and technol- ogy continues to be a significant challenge for software management. Managers interested in improving quality, cost, and cycle-time of their products have a large set of methods, tools, and techniques from which to choose. The implementation of one or more of these potential improvements can require considerable time and cost. Decision makers must be able to understand the benefits from each proposed improvement and decide which improvements to implement. While a variety of approaches exist for evaluating the costs and benefits of a few specific improvements such as inspections or systematic reuse, there is no general model for evaluating software process improvements. The result of this research is a practical, useful framework to assist practitioners in evaluating potential process improvements. This general framework can accommodate a variety of methods for estimating the cost-benefit effects of a process change. To illustrate this framework a set of cost-benefit templates for Emerald and Cleanroom technologies were developed and validated. Methods for evaluating effects range from constants and simple equations to bayesian decision models and dynamic process simulations. A prototype tool was developed to assist in performing cost-benefit analysis of software process improvements

A Cost-Benefit analysis model for technical debt management considering uncertainty and time

In the last few years, technical debt has been used as a useful means for making the intrinsic cost of the internal software quality weaknesses visible. This visibility is made possible by quantifying this cost. Specifically, technical debt is expressed in terms of two main concepts: principal and interest. The principal is the cost of eliminating or reducing the impact of a, so called, technical debt item in a software system; whereas the interest is the recurring cost, over a time period, of not eliminating a technical debt item. Previous works about technical debt are mainly focused on estimating principal and interest, and on performing a cost-benefit analysis. This cost-benefit analysis allows one to determine if to remove technical debt is profitable and to prioritize which items incurring in technical debt should be fixed first. Nevertheless, for these previous works technical debt is flat along the time. However the introduction of new factors to estimate technical debt may produce non flat models that allow us to produce more accurate predictions. These factors should be used to estimate principal and interest, and to perform cost-benefit analysis related to technical debt. In this paper, we take a step forward introducing the uncertainty about the interest, and the time frame factors so that it becomes possible to depict a number of possible future scenarios. Estimations obtained without considering the possible evolution of the interest over time may be less accurate as they consider simplistic scenarios without changes

Optimal utilization of historical data sets for the construction of software cost prediction models

The accurate prediction of software development cost at early stage of development life-cycle may have a vital economic impact and provide fundamental information for management decision making. However, it is not well understood in practice how to optimally utilize historical software project data for the construction of cost predictions. This is because the analysis of historical data sets for software cost estimation leads to many practical difficulties. In addition, there has been little research done to prove the benefits. To overcome these limitations, this research proposes a preliminary data analysis framework, which is an extension of Maxwell's study. The proposed framework is based on a set of statistical analysis methods such as correlation analysis, stepwise ANOVA, univariate analysis, etc. and provides a formal basis for the erection of cost prediction models from his¬torical data sets. The proposed framework is empirically evaluated against commonly used prediction methods, namely Ordinary Least-Square Regression (OLS), Robust Regression (RR), Classification and Regression Trees (CART), K-Nearest Neighbour (KNN), and is also applied to both heterogeneous and homogeneous data sets. Formal statistical significance testing was performed for the comparisons. The results from the comparative evaluation suggest that the proposed preliminary data analysis framework is capable to construct more accurate prediction models for all selected prediction techniques. The framework processed predictor variables are statistic significant, at 95% confidence level for both parametric techniques (OLS and RR) and one non-parametric technique (CART). Both the heterogeneous data set and homogenous data set benefit from the application of the proposed framework for improving project effort prediction accuracy. The homogeneous data set is more effective after being processed by the framework. Overall, the evaluation results demonstrate that the proposed framework has an excellent applicability. Further research could focus on two main purposes: First, improve the applicability by integrating missing data techniques such as listwise deletion (LD), mean imputation (MI), etc., for handling missing values in historical data sets. Second, apply benchmarking to enable comparisons, i.e. allowing companies to compare themselves with respect to their productivity or quality

Requirements Prioritization Based on Benefit and Cost Prediction: An Agenda for Future Research

In early phases of the software cycle, requirements prioritization necessarily relies on the specified requirements and on predictions of benefit and cost of individual requirements. This paper presents results of a systematic review of literature, which investigates how existing methods approach the problem of requirements prioritization based on benefit and cost. From this review, it derives a set of under-researched issues which warrant future efforts and sketches an agenda for future research in this area

Apprenticeship training in Italy: a cost-effective model for firms?

In times of rapid technological progress and increasing digitalisation in many areas of work and life, it is more important than ever to provide young people with the best possible skills for their entry into the world of work. It is certainly important to provide them with a solid theoretical knowledge base. However, it is also important to impart practical skills to ensure that they are able to adapt to the needs of the labour market. Post-school education in Italy, while providing good formal skills in this respect, is not sufficiently responsive to the needs of the labour market. With this in mind, dual training models have become politically more attractive in Italy and are already being implemented. But despite political support and the reforms in recent years, the popularity of dual training models has hardly increased. From an international point of view, this development is hardly surprising. On the one hand, interest in dual vocational training is increasing: learning a trade at two locations – in a company and at a part-time vocational school – means that apprentices gain valuable professional experience while they are still training, which enables a smoother transition to the labour market. As a result, there is less youth unemployment and a better supply of skilled labour for industry. On the other hand, reforms of this kind often encounter a major obstacle when it comes to practical implementation: a lack of commitment by the companies, especially in countries where an in-company apprenticeship tradition is absent. First and foremost, companies see training as an operational loss: why pay to train an apprentice when qualified employees can be recruited directly on the labour market? What businesses often fail to see is that in-house training does not merely incur costs, but that it also results in monetary benefits, and sometimes in net profits before training has even been completed. However, the question is: under which conditions? The costs and benefits of training are not invariables, they depend on a wide of variety of parameters such as the level of apprentices’ pay, the industry in question, the duration of training, recruiting costs for qualified skilled workers on the labour market – not to mention the quality of the training course. To examine the situation, this study uses simulations to investigate how these parameters would have to be designed in Italy in order to make dual training more attractive for Italian businesses. The conclusions derived in this report are intended to assist Italian policymakers and employers to make more evidence-based decisions, to ensure that Italy’s labour force investments are more likely to yield positive returns

Apprenticeship training in England: a cost-effective model for firms?

In England, the government plans to incentivise spending of billions of pounds over the next few years promoting apprenticeships, with most of the finance raised from the apprenticeship levy on employers. Promoting more apprenticeships is designed to improve England’s skill base – a government policy priority given the relatively low level of skills and educational qualifications amongst a large part of the country’s workforce. But does such a policy make sense in an English context, with a historically limited participation of many employers in work related formal training? Is additional spending on apprenticeships likely to lead to positive economic returns for employers, workers and for England itself? And how varied are the net economic returns by employer and by sector? What works for one category of employment may not bring positive gains where returns to training are much lower. To answer these questions the JPMorgan Chase Foundation, the Education Policy Institute and the Bertelsmann Stiftung have come together and partnered with the internationally acknowledged economist Prof. Dr. Stefan C. Wolter to explore the costs and benefits of apprenticeship training for companies in England. This report by Prof. Dr. Stefan C. Wolter and Eva Joho brings a much needed degree of rigour and quantification to a policy area which is too often characterised by assumption, hunch, and international experience which may not apply in a very different country context. The authors have used evidence from Germany, Switzerland and Austria to simulate the costs and benefits of an apprenticeship policy applied in an English context. They are aware of the limitations of this approach - not least given the different tradition of employer engagement in England - but the analysis in this report is important and could help guide employer and government policies in directions that maximise economic returns and limit low return scenarios. In particular, the return by occupations is shown to be highly varied based on the return and cost characteristics of each sector. The returns by employer within each sector also vary markedly. The key conclusions the authors have derived in the report could help steer English policymakers and employers in more evidence based directions, which should help ensure that England’s large investment in this area is properly informed by evidence and more likely to yield positive returns. In addition, the present study complements studies with a similar methodology in Spain (2016) and Italy (to be published 2018), which will enable learnings for successful implementation of apprenticeship models across countries

Evaluating Software Architectures: Development Stability and Evolution

We survey seminal work on software architecture evaluationmethods. We then look at an emerging class of methodsthat explicates evaluating software architectures forstability and evolution. We define architectural stabilityand formulate the problem of evaluating software architecturesfor stability and evolution. We draw the attention onthe use of Architectures Description Languages (ADLs) forsupporting the evaluation of software architectures in generaland for architectural stability in specific

A 5D Building Information Model (BIM) for Potential Cost-Benefit Housing: A Case of Kingdom of Saudi Arabia (KSA)

The Saudi construction industry is going through a process of acclimatizing to a shifting fiscal environment. Due to recent fluctuations in oil prices, the Saudi construction sector decided to adjust to current trade-market demands and rigorous constitutional regulations because of competitive pressures. This quantitative study assesses and compares existing flat design vs. mid-terrace housing through cost estimation and design criteria that takes family privacy into consideration and meets the needs of Saudi Arabian families (on average consisting of seven members). Five pilot surveys were undertaken to evaluate the property preference type of Saudi families. However, Existing models did not satisfy the medium range family needs and accordingly a 5D (3D + Time + Cost) Building Information Modelling (BIM) is proposed for cost benefiting houses. Research results revealed that mid-terrace housing was the best option, as it reduced land usage and construction costs. While, 5D BIM led to estimate accurate Bill of Quantities (BOQ) and the appraisal of construction cost

Relevance, benefits, and problems of software modelling and model driven techniques—A survey in the Italian industry

Context Claimed benefits of software modelling and model driven techniques are improvements in productivity, portability, maintainability and interoperability. However, little effort has been devoted at collecting evidence to evaluate their actual relevance, benefits and usage complications. Goal The main goals of this paper are: (1) assess the diffusion and relevance of software modelling and MD techniques in the Italian industry, (2) understand the expected and achieved benefits, and (3) identify which problems limit/prevent their diffusion. Method We conducted an exploratory personal opinion survey with a sample of 155 Italian software professionals by means of a Web-based questionnaire on-line from February to April 2011. Results Software modelling and MD techniques are very relevant in the Italian industry. The adoption of simple modelling brings common benefits (better design support, documentation improvement, better maintenance, and higher software quality), while MD techniques make it easier to achieve: improved standardization, higher productivity, and platform independence. We identified problems, some hindering adoption (too much effort required and limited usefulness) others preventing it (lack of competencies and supporting tools). Conclusions The relevance represents an important objective motivation for researchers in this area. The relationship between techniques and attainable benefits represents an instrument for practitioners planning the adoption of such techniques. In addition the findings may provide hints for companies and universitie