Effort Estimation Factors for Corrective Software Maintenance Projects: A Qualitative Analysis of Estimation Criteria

In this paper, we identify factors that impact software maintenance effort by exploring expert software maintenance estimators’ knowledge about corrective maintenance projects. We use a qualitative approach to identify the issues important to these experts to derive their effort estimates. We find seventeen factors (rated and rank ordered by importance) that affect corrective maintenance effort and include constructs related to developers, code, defects, and environment. Several of these factors that have a comparably strong influence on corrective maintenance estimation are unique to corrective maintenance and are not generally observed in established software estimation models. The results enhance organizations’ ability to effectively manage maintenance environments by focusing attention on the identified areas. For future research, these results represent an important step toward developing a comprehensive and accurate corrective maintenance effort estimation model

Identifying effort estimation factors for corrective maintenance in object-oriented systems

This research identifies factors that impact software maintenance effort by exploring the decision-making process of expert estimators of corrective maintenance projects by using qualitative methods to identify the factors that they use in deriving estimates. We implement a technique called causal mapping, which allows us to identify the cognitive links between the information that estimators use, and the estimates that they produce based on that information. Results suggest that a total of 17 factors may be relevant for corrective maintenance effort estimation, covering constructs related to developers, code, defects, and environment. When these factors are rank-ordered, they demonstrate that some of the factors that have greater influence on corrective maintenance estimation, as expressed by expert estimators, are very specific to corrective maintenance and not generally observed in popular software estimation or maintenance estimation models. This line of research aims at addressing the limitations of existing maintenance estimation models that do not incorporate a number of soft factors, thus, achieving less accurate estimates than human experts

O&M Models for Ocean Energy Converters: Calibrating through Real Sea Data

Of the cost centres that combine to result in Levelised Cost of Energy (LCOE), O&M costs play a significant part. Several developers have calculated component costs, demonstrating how they can become commercially competitive with other forms of renewable energy. However, there are uncertainties relating to the O&M figures that can only be reduced through lessons learned at sea. This work presents an O&M model calibrated with data from real sea experience of a wave energy device deployed at the Biscay Marine energy Platform (BiMEP): the OPERA O&M Model. Two additional case studies, utilising two other O&M calculation methodologies, are presented for comparison with the OPERA O&M Model. The second case study assumes the inexistence of an O&M model, utilising a Simplified Approach. The third case study applies DTOcean’s (a design tool for ocean energy arrays) O&M module. The results illustrate the potential advantages of utilising real sea data for the calibration and development of an O&M model. The Simplified Approach was observed to overestimate LCOE when compared to the OPERA O&M Model. This work also shows that O&M models can be used for the definition of optimal maintenance plans to assist with OPEX reduction.The authors are grateful to the European commission for funding the OPERA and EnFAIT projects as part of the Horizon 2020 framework. The authors also thankful to Oceantec-Idom for providing feedback to OPERA model’s inputs. A special thanks to Shona Pennock and Donald Noble for their diligent proofreading of this paper

Managers Handbook for Software Development

Methods and aids for the management of software development projects are presented. The recommendations are based on analyses and experiences with flight dynamics software development. The management aspects of organizing the project, producing a development plan, estimation costs, scheduling, staffing, preparing deliverable documents, using management tools, monitoring the project, conducting reviews, auditing, testing, and certifying are described

Predictive Maintenance on the Machining Process and Machine Tool

This paper presents the process required to implement a data driven Predictive Maintenance (PdM) not only in the machine decision making, but also in data acquisition and processing. A short review of the different approaches and techniques in maintenance is given. The main contribution of this paper is a solution for the predictive maintenance problem in a real machining process. Several steps are needed to reach the solution, which are carefully explained. The obtained results show that the Preventive Maintenance (PM), which was carried out in a real machining process, could be changed into a PdM approach. A decision making application was developed to provide a visual analysis of the Remaining Useful Life (RUL) of the machining tool. This work is a proof of concept of the methodology presented in one process, but replicable for most of the process for serial productions of pieces

Identifying Effort Estimation Factors for Corrective Maintenance in Object-Oriented Systems

This research explores the decision-making process of expert estimators of corrective maintenance projects by usingqualitative methods to identify the factors that they use in deriving estimates. We implement a technique called causalmapping, which allows us to identify the cognitive links between the information that estimators use, and the estimates thatthey produce based on that information. Results suggest that a total of 17 factors may be relevant for corrective maintenanceeffort estimation, covering constructs related to developers, code, defects, and environment. This line of research aims ataddressing the limitations of existing maintenance estimation models that do not incorporate a number of soft factors, thus,achieving less accurate estimates than human experts

Requirements Changes Rework Effects: A Case Study

Although software managers are generally good at estimation, their experience of scheduling reworks is poor. Inconsistent or incorrect effort estimation in turn increases the risk that the completion time for a project will ultimately become problematic. To continually alter software maintenance schedules while maintaining software projects is, in fact, a daunting task. Our proposed framework, validated in a case study, confirms that variables in requirements change suffer from weaknesses in coding, user involvement and user documentation. Our results clearly show that there is significant impact on rework as a result of unexpected errors found to correlate to 1) weak characteristics and attributes as described in the source lines of code, especially in data declaration and data statement, 2) lack of communication between developers and users on a change effect, and 3) unavailability of user documentation. To keep rework under control, new criteria in change request forms are proposed. These criteria are shown in the framework to need refining; thus, the more case studies that are validated, the more reliable the result will be in determining outcomes of effort rework effects

Recommended approach to sofware development

A set of guideline for an organized, disciplined approach to software development, based on data collected and studied for 46 flight dynamics software development projects. Methods and practices for each phase of a software development life cycle that starts with requirements analysis and ends with acceptance testing are described; maintenance and operation is not addressed. For each defined life cycle phase, guidelines for the development process and its management, and the products produced and their reviews are presented

Estimating development effort in free/open source software projects by mining software repositories: A case study of OpenStack

Because of the distributed and collaborative nature of free/open source software (FOSS) projects, the development effort invested in a project is usually unknown, even after the software has been released. However, this information is becoming of major interest, especially-but not only-because of the growth in the number of companies for which FOSS has become relevant for their business strategy. In this paper we present a novel approach to estimate effort by considering data from source code management repositories. We apply our model to the OpenStack project, a FOSS project with more than 1,000 authors, in which several tens of companies cooperate. Based on data from its repositories and together with the input from a survey answered by more than 100 developers, we show that the model offers a simple, but sound way of obtaining software development estimations with bounded margins of error.Gregorio Robles, Carlos Cervig on and Jes us M. Gonz alez-Barahona, project SobreSale (TIN2011-28110). and The work of Daniel Izquierdo has been funded in part by the Torres Quevedo program (PTQ-12-05577