Effort estimation and prediction of object-oriented systems

Nesi, Paolo; Querci, Tommaso

doi:10.1016/s0164-1212(97)10021-8

Cited by 64 publications

(75 citation statements)

References 17 publications

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“…All these methods use some form of software complexity and size metrics in order to predict effort. Some studies like [58] and [32], try to develop better metrics which either relate to effort more closely or represent the complexity of software more accurately.…”

Section: Effort Prediction Methodsmentioning

confidence: 99%

An effort prediction framework for software defect correction

Hassouna¹,

Tahvildari²

2010

Information and Software Technology

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Developers apply changes and updates to software systems to adapt to emerging environments and address new requirements. In turn, these changes introduce additional software defects, usually caused by our inability to comprehend the full scope of the modified code. As a result, software practitioners have developed tools to aid in the detection and prediction of imminent software defects, in addition to the effort required to correct them. Although software development effort prediction has been in use for many years, research into defect-correction effort prediction is relatively new. The increasing complexity, integration and ubiquitous nature of current software systems has sparked renewed interest in this field. Effort prediction now plays a critical role in the planning activities of managers. Accurate predictions help corporations budget, plan and distribute available resources effectively and efficiently. In particular, early defect-correction effort predictions could be used by testers to set schedules, and by managers to plan costs and provide earlier feedback to customers about future releases.In this work, we address the problem of predicting the effort needed to resolve a software defect. More specifically, our study is concerned with defects or issues that are reported on an Issue Tracking System or any other defect repository. Current approaches use one prediction method or technique to produce effort predictions. This approach usually suffers from the weaknesses of the chosen prediction method, and consequently the accuracy of the predictions are affected. To address this problem, we present a composite prediction framework. Rather than using one prediction approach for all defects, we propose the use of multiple integrated methods which complement the weaknesses of one another. Our framework is divided into two sub-categories, Similarity-Score Dependent and Similarity-Score Independent. The Similarity-Score Dependent method utilizes the power of Case-Based Reasoning, also known as Instance-Based Reasoning, to compute predictions. It relies on matching target issues to similar historical cases, then combines their known effort for an informed estimate. On the other hand, the Similarity-Score Independent method makes use of other defect-related information with some statistical manipulation to produce the required estimate. To measure similarity between defects, some method of distance calculation must be used. In some cases, this method might produce misleading results due to observed inconsistencies in history, and the fact that current similarity-scoring techniques cannot account for all the variability in the data. In this case, the Similarity-Score Independent method can be used to estimate the effort, where the effect of such inconsistencies can be reduced.We have performed a number of experimental studies on the proposed framework to assess the effectiveness of the presented techniques. We extracted the data sets from an operational Issue Tracking System in order to test the validity...

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Section: Effort Prediction Methodsmentioning

confidence: 99%

An effort prediction framework for software defect correction

Hassouna¹,

Tahvildari²

2010

Information and Software Technology

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“…However, 3D Function Points require a greater degree of detail in order to determine size and consequently make early counting more difficult. Object point measure is another adaption of function point, used in the improved COCOMO2.0 effort estimation technique [13]. Object Point count is very similar to Function Point, but objects are taken as the basis of the counting process.…”

Section: Related Workmentioning

confidence: 99%

“…It is widely accepted that system size is strongly correlated with development effort [13], [18], [19], [20]. The Class Point approach provides a system-level size measure by suitably combining well known OO measures, which consider specific aspects of a single class.…”

Section: Validation and Conclusionmentioning

confidence: 99%

Size Estimation of OLAP Systems

Bhan¹,

T²,

Rajanikanth³

2013

Computer Science &Amp; Information Technology ( CS &Amp; IT )

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“…Other studies validated a set of polymorphism metrics (Benlarbi and Melo, 1999), a coupling dependency metric (Binkley and Schach, 1998), a set of metrics defined on Shlaer-Mellor designs (Cartwright and Shepperd, 2000), another metrics suite (F. Brito e Abreu and Melo, 1996), and a set of coupling metrics (R. Harrison, Counsell, and Nithi, 1998). Other external measures of interest that have been studied are productivity (Chidamber et al, 1998), maintenance effort (Li and Henry, 1993), and development effort (Chidamber et al, 1998;Misic and Tesic, 1998;Nesi and Querci, 1998). However, here we will focus on the fault-proneness external measure.…”

Section: Empirical Evidencementioning

confidence: 99%

Object-Oriented Metrics: A Review of Theory and Practice

El-Emam¹

2002

Advances in Software Engineering

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Effort estimation and prediction of object-oriented systems

Cited by 64 publications

References 17 publications

An effort prediction framework for software defect correction

An effort prediction framework for software defect correction

Size Estimation of OLAP Systems

Object-Oriented Metrics: A Review of Theory and Practice

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