Introduction of Software Product Management at Wincor Nixdorf: Challenges and Lessons Learned

Incremental software process improvement deals with the challenges of step-wise process improvement in a time where resources are scarce and many organizations are struggling with the challenges of effective management of software products. Effective knowledge sharing and incremental approaches are essential for improving the success rate of process improvement efforts. Recently, the authors’ have worked on the development of a knowledge management system, the Online Method Engine, that enables incremental, situational process improvement in the field of software product management. This has resulted in an initial system design. The authors describe the findings from seven exploratory case studies on incremental process improvement. The lessons learned during these case studies are used to refine the design of the Online Method Engine.

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The Agile Requirements Refinery: Applying SCRUM Principles to Software Product Management

2009 Third International Workshop on Software Product Management ◽

10.1109/iwspm.2009.7 ◽

2009 ◽

Cited By ~ 8

Author(s):

Kevin Vlaanderen ◽

Sjaak Brinkkemper ◽

Slinger Jansen ◽

Erik Jaspers

Keyword(s):

Product Management ◽

Software Product ◽

Agile Requirements

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USING CLASSIFICATION TREES FOR SOFTWARE QUALITY MODELS: LESSONS LEARNED

International Journal of Software Engineering and Knowledge Engineering ◽

10.1142/s0218194099000140 ◽

1999 ◽

Vol 09 (02) ◽

pp. 217-231 ◽

Cited By ~ 14

Author(s):

TAGHI M. KHOSHGOFTAAR ◽

EDWARD B. ALLEN ◽

ARCHANA NAIK ◽

WENDELL D. JONES ◽

JOHN P. HUDEPOHL

Keyword(s):

Software Quality ◽

Classification Trees ◽

Lessons Learned ◽

Quality Models ◽

Model Based ◽

Software Product ◽

High Assurance ◽

Process Metrics ◽

Product And Process ◽

Software Quality Models

High software reliability is an important attribute of high-assurance systems. Software quality models yield timely predictions of quality indicators on a module-by-module basis, enabling one to focus on finding faults early in development. This paper introduces the Classification And Regression Trees (CART) a algorithm to practitioners in high-assurance systems engineering. This paper presents practical lessons learned on building classification trees for software quality modeling, including an innovative way to control the balance between misclassification rates. A case study of a very large telecommunications system used CART to build software quality models. The models predicted whether or not modules would have faults discovered by customers, based on various sets of software product and process metrics as independent variables. We found that a model based on two software product metrics had comparable accuracy to a model based on forty product and process metrics.

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