PSP PAIR: Automated Personal Software Process Performance Analysis and Improvement Recommendation

2012 ◽  
Author(s):  
Cesar Barbosa Duarte ◽  
Joao Pascoal Faria ◽  
Mushtaq Raza
Keyword(s):  
Performance Analysis ◽  
Software Process ◽  
Process Performance ◽  
Personal Software Process

Supporting software process performance analysis through a knowledge-based environment

2014 ◽  
Author(s):  
Natalia Chaves Lessa Schots ◽  
Taisa Guidini Goncalves ◽  
Rodrigo Figueiredo Magalhaes ◽  
Ana Regina Rocha ◽  
Gleison Santos ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Software Process ◽  
Process Performance ◽  
Knowledge Based

scholarly journals A Knowledge-based Environment for Software Process Performance Analysis

2015 ◽  
Author(s):  
Natália Chaves Lessa Schots ◽  
Rodrigo Figueiredo Magalhães ◽  
Taísa Guidini Gonçalves ◽  
Ricardo De Holanda Busquet ◽  
Ana Regina Rocha ◽  
...  
Keyword(s):  
Performance Analysis ◽  
Software Process ◽  
Systematic Mapping Study ◽  
Process Performance ◽  
Background Process ◽  
Knowledge Based ◽  
Body Of Knowledge ◽  
Literature Reviews ◽  
Specific Performance ◽  
The Individual

Background: Process performance analysis is a key step for implementing continuous improvement in software organizations. However, the knowledge to execute such analysis is not trivial and the person responsible to executing it must be provided with appropriate support. Aim: This paper presents a knowledge-based environment, named SPEAKER, proposed for supporting software organizations during the execution of process performance analysis. SPEAKER comprises a body of knowledge and a set of activities and tasks for software process performance analysis along with supporting tools to executing these activities and tasks. Method: We conducted an informal literature reviews and a systematic mapping study, which provided basic requirements for the proposed environment. We implemented the SPEAKER environment integrating supporting tools for the execution of activities and tasks of performance analysis and the knowledge necessary to execute them, in order to meet the variability presented by the characteristics of these activities. Results: In this paper, we describe each SPEAKER module and the individual evaluations of these modules, and also present an example of use comprising how the environment can guide the user through a specific performance analysis activity. Conclusion: Although we only conducted individual evaluations of SPEAKER’s modules, the example of use indicates the feasibility of the proposed environment. Therefore, the environment as a whole will be further evaluated to verify if it attains its goal of assisting in the execution of process performance analysis by non-specialist people.

Queueing Inference for Process Performance Analysis with Missing Life-Cycle Data

2020 ◽  
Author(s):  
Guy Berkenstadt ◽  
Avigdor Gal ◽  
Arik Senderovich ◽  
Roee Shraga ◽  
Matthias Weidlich
Keyword(s):  
Life Cycle ◽  
Performance Analysis ◽  
Process Performance

APPLYING EXPERT JUDGMENT TO IMPROVE AN INDIVIDUAL'S ABILITY TO PREDICT SOFTWARE DEVELOPMENT EFFORT

2012 ◽  
Vol 22 (04) ◽  
pp. 467-483 ◽  
Author(s):  
CUAUHTÉMOC LÓPEZ-MARTÍN ◽  
ALAIN ABRAN
Keyword(s):  
Software Development ◽  
Software Process ◽  
Development Effort ◽  
Academic Environment ◽  
Academic Institutions ◽  
Graduate Courses ◽  
Software Projects ◽  
Personal Software Process ◽  
Software Development Effort ◽  
Effort Prediction

Expert-based effort prediction in software projects can be taught, beginning with the practices learned in an academic environment in courses designed to encourage them. However, the length of such courses is a major concern for both industry and academia. Industry has to work without its employees while they are taking such a course, and academic institutions find it hard to fit the course into an already tight schedule. In this research, the set of Personal Software Process (PSP) practices is reordered and the practices are distributed among fewer assignments, in an attempt to address these concerns. This study involved 148 practitioners taking graduate courses who developed 1,036 software course assignments. The hypothesis on which it is based is the following: When the activities in the original PSP set are reordered into fewer assignments, the result is expert-based effort prediction that is statistically significantly better.

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