Browsing by Author "Hamza, Haitham S."
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Item 2nd International Workshop on Knowledge-Oriented Product Line Engineering(2011) Hamza, Haitham S.; Martinez, Jabier; Rummler, Andreas; SWTSoftware Product Line Engineering (PLE) exploits systematic reuse by identifying and methodically reusing software artifacts to develop different but related software systems. Developing Product Lines requires analysis skills to identify, model, and encode domain and product knowledge into artifacts that can be systematically reused across the development life-cycle. As such, Knowledge plays a paramount role in the success of the various activities of PLE. The objective of KOPLE is to bring together SPL researchers and practitioners from academia and industry to investigate the role of Knowledge in PLE. Knowledge is usually encapsulated in PL architectures in a tacit or implicit way, and this may appear to be sufficient for industry to implement successful product lines. Nevertheless, KOPLE also aims to become a discussion forum about techniques and methods to convert from tacit to explicit Knowledge in PLE and to process and use this Knowledge for optimizing and innovating PLE processes.Item Introducing product line architectures in the erp industry: Challenges and lessons learned(Lancaster University, 2010) Hamza, Haitham S.; Martinez, Jabier; Alonso, Carmen; Botterweck, Goetz; Jarzabek, Stan; Kishi, Tomoji; Lee, Jaejoon; Livengood, Steve; SWT; IAReturn on Investment (ROI) for companies involved in Enterprise Resource Planning (ERP) system development depends on their flexibility to evolve, maintain, customize and configure their ERP product to respond to new business needs, deployment models and emerging market segments. In this particular aspect, ERP systems can get benefit from commonality and variability management concepts in order to improve evolution and maintainability. Moreover, Product Line Engineering (PLE) methods and practices can substantially reduce time and effort regarding the current complex and tedious configuration procedures that are not only resource-intensive, but also error-prone. This paper introduces practical experiences from the application of product line architectures (PLAs) in four companies of the ERP systems domain.Item KOPLE - Knowledge-oriented product line engineering(Association for Computing Machinery, 2010) Hamza, Haitham S.; Martínez, Jabier; Mugartza, Joseba Laka; SWT; SGThe maturity of Knowledge Engineering (KE) theory and practice presents a real opportunity for advancing the state-of-the-art and state-of-the-practice in software Product-line Engineering (PLE). Several challenges that face the adoption and implementation of PLE in practice can be addressed by exploiting advanced techniques from KE. This paper introduces the concept of KOPLE and describes the related one-day workshop that will be held in conjunction with SPLASH 2010.Item Third international workshop on knowledge-oriented product line engineering (KOPLE 2012)(2012) Hamza, Haitham S.; Martinez, Jabier; Thurimella, Anil Kumar; Deogun, Jitender S.; SWTSoftware Product Line Engineering (PLE) exploits systematic reuse by identifying and methodically reusing software artifacts to develop different but related software systems. Developing Product Lines requires analysis skills to identify, model, and encode domain and product knowledge into artifacts that can be systematically reused across the development life-cycle. As such, Knowledge plays a paramount role in the success of the various activities of PLE. The objective of the KOPLE workshop series is to bring together SPL researchers and practitioners from academia and industry to investigate the role of Knowledge in PLE. Knowledge is usually encapsulated in PL architectures in a tacit or implicit way, and this may appear to be sufficient for industry to implement successful product lines. Nevertheless, KOPLE also aims to become a discussion forum about techniques and methods to convert from tacit to explicit Knowledge in PLE and to process and use this Knowledge for optimizing and innovating PLE processes.