Alejandro Salado

The Concept of Order of Conflict in Requirements Engineering

Conventional approaches to system design use requirements as boundary conditions against which the design activity occurs. Decisions at a given level of the architecture decomposition can result in the flowing down of conflicting requirements, which are easy to fulfill in isolation but extremely difficult when dealt with simultaneously. Designing against such sets of requirements considerably limits system affordability. Existing research on the evaluation of such conflicts primarily seek to determine the level of conflicts between pairs of requirements. We assert in this paper that these methods are incomplete and using traditional methodologies can result in missing significant conflicts between groups of requirements. We provide a mathematical proof for this assertion and present two case studies that support the mathematical proof. We present the concept of “order of conflict.” The objective of this paper is to prove why pairwise-based conflicting requirements identification and analysis methods based on pairwise comparisons are flawed.

A Categorization Model of Requirements Based on Max-Neef's Model of Human Needs

Requirements categorization is an inherent part of the requirements engineering activity. Conventional approaches use a designer perspective requirements organized according to design needs or attributes, a contractual perspective requirements organized according to procurement or acquisition needs, or a combination of both. Such models present several inconveniences that result in limitation of system affordability: facilitate the generation of overlapping requirements, of design-dependent requirements, and of a mix of requirements applicable to different levels of the architecture decomposition or to different products. The present research proposes a Need-based Categorization NbC model that is system-centric: Requirements are organized around the system. Inspired by Max-Neefs model of human needs, the proposed model supports requirement elicitation by defining only what the system does, how well, where, and what it uses to accomplish it. The model facilitates the identification of constraints that limit the solution tradespace without supporting the satisfaction of new needs, of overlapping requirements, and of requirements that are not applicable to the system. Finally, the proposed model defines requirements in subsets that are associated with value to stakeholders, thus reflecting the actual dependency nature of requirements at a given level of an architecture decomposition, which promotes holistic decisions instead of local optimizations.

Using Maslow's hierarchy of needs to define elegance in system architecture☆

Abstract Despite the rising interest in developing elegant systems an integral definition of elegance in system architecture and design is lacking. Current attempts have only been able to describe emergent properties of an elegant design or system. This descriptive approach has resulted in evolving definitions and in an inability to use elegance as criteria to evaluate various design candidates. The present research proposes a need-based definition of elegance that aims at being complete yet adaptable, quantifiable, and that allows comparison between different designs or systems. Using Maslows hierarchy of needs as a paradigm the present research proposes a structural definition that is grounded on the known and unknown needs an elegant system satisfies, rather than on its emergent properties. Specific emergent properties can then be categorized within the structural definition. The benefits of using such type of definition for elegance in system design are two-fold: it ensures completeness because the specific attributes can always be expanded without actually affecting the definition; and it is integral because it provides the necessary flexibility so that designers can tailor the attributes according to their specific environment.

Contextual- and Behavioral-Centric Stakeholder Identification

Proper identification of stakeholders is the first step to bound the system of interest and ultimately to correctly define the problem of concern. Research has traditionally addressed the process of identifying stakeholders using stakeholder-centric methods such as brainstorming (unstructured or with discipline-specific taxonomies). These approaches are grounded on the idea of listing entities that have a relation to the system and then analyze their mutual relationships so that their relative importance with respect to the system can be assessed. Yet, these methods do not provide any mechanism to ensure completeness and thus introduce a high level of uncertainty in the definition of the problem at the beginning of the system life-cycle. The present research proposes instead a contextual- and behavioral-centric approach for stakeholder identification. Using systems thinking the focus is put on understanding all the underlying relationships, be them complex or simple, of the system within its environment and during its existence by comprehensively modeling its socio-technical context and behavior. As a result stakeholders no longer need to be sought, but they comprehensively emerge out of the holistic understanding of the system.

The Concept of Problem Complexity

Abstract Recognizing the impact of system complexity on the success of a systems development has created significant research efforts towards measuring system complexity. In particular, the research community has proposed techniques to measure three types of system complexity: (1) structural complexity, which measures the complexity resulting from physical interconnection of components; (2) functional complexity, which measures the complexity resulting from interconnection of system functions; and (3) organizational complexity, which measures the contractual interconnection of the different organizations developing the system. The majority of these metrics focus on measuring aspects of the complexity of an existing system or design. However, a metric to anticipate the complexity induced by the problem itself on a systems development is lacking. We therefore present the concept of Problem Complexity as the complexity level that a set of requirements can impose to any system fulfilling them. In addition, we mathematically demonstrate using the concept of joint entropy how problem complexity defines the minimum level of complexity a system can achieve for a given set of requirements. The paper suggests an analytic formulation to measure the complexity induced by a set of requirements in a systems development that is based on a set of heuristics that facilitate identification of conflicts between requirements. The use of such analytical formulation is showcased on a notional case-study.

Erratum to: A contribution to the scientific foundations of systems engineering: Solution spaces and requirements

The article A Contribution to the Scientific Foundations of Systems Engineering: Solution Spaces and Requirements written by Alejandro Salado, Roshanak Nilchiani and Dinesh Verma, has been revised due to a missing part the authors forgot to add. The missing part goes at the end of Appendix B, Page 36.

The Tension Matrix and the Concept of Elemental Decomposition: Improving Identification of Conflicting Requirements

Conventional approaches to system design use requirements as boundary conditions against which the design activity occurs. Decisions at a given level of the architecture decomposition can result in a flowing down of conflicting requirements, which are easy to fulfill in isolation but extremely difficult when dealt with simultaneously. Designing against such sets of requirements considerably limits system affordability. Conventional approaches to identifying these conflicts are either time efficient, yet ineffective, or effective, but time consuming. This paper proposes a novel method that sits between those extremes. It enables quick identification of conflicts, while still maintaining a good level of effectiveness. The proposed method, which is called the tension matrix, is built on three pillars: 1) heuristics to identify conflicting requirements, aimed at reducing completeness uncertainty; 2) targeted modeling; and 3) elemental decomposition. The effectiveness of the method was validated with a case study, on which a combination of retrospective assessment with a prospective analysis was employed. The results confirmed that the proposed tension matrix and the concept of elemental decomposition provide higher levels of effectiveness in identifying conflicting requirements, before initiating architectural or design activities, than conventional approaches.

Defining Better Test Strategies with Tradespace Exploration Techniques and Pareto Fronts: Application in an Industrial Project

Test strategies are usually defined following a point-design like method. Starting with a set of verification requirements and programmatic constraints, and usually with a generic test sequence, a baseline test approach is defined. Then, the baseline is optimized until an acceptable strategy is found. Academia has consistently shown however the benefits of using tradespace exploration techniques instead of point-based designs. Some industrial applications seem to corroborate such findings. Yet, both academia and industry have limited the use of tradespace exploration techniques to selecting design concepts. This paper proposes that broadening the use of tradespace exploration techniques and Pareto frontiers to other activities in the field of systems engineering domain yields similar benefits. In particular, this paper presents the actual application of tradespace exploration techniques and Pareto frontiers in an industrial context to select a test strategy for a system. This paper provides thus three main contributions. First, the paper demonstrates that tradespace exploration and Pareto frontiers can be beneficial beyond concept selection. Second, the paper presents a process to use tradespace exploration techniques and Pareto frontiers for selecting test strategies. Finally, the paper showcases the application of the proposed technique and process in a real industrial setup, which yielded a number of lessons learnt.

Adaptive Requirements Prioritization ARP: Improving Decisions between Conflicting Requirements

Prioritization of requirements is a core activity of requirements engineering. Conventionally used to resolve conflicting requirements, it can be performed on a wide variety of attributes, reflecting, for example, stakeholder value, value to business, cost, connectivity, or risk. Its benefit in decision making is unquestionable, yet existing techniques are ineffective for realistic sets of requirements and consequently their adoption by practitioners is scarce, particularly in the fields of hardware-intensive systems. The present research proposes an Adaptive Requirements Prioritization ARP method that improves decision making between conflicting requirements due to its principles of multidimensionality and objective-base the right criteria are used for any particular decision, and its usability due its principles of openness it can be tailored according to specific project needs and structure requirements are grouped in subsets so that existing techniques become effective. The effectiveness of the proposed method is evaluated using Monte Carlo simulation for a variety of priority dimensions and priority levels.

Increasing the Probability of Developing Affordable Systems by Maximizing and Adapting the Solution Space

Abstract The present research suggests that the size of the solution space, which for a given set of stakeholder needs is delimited by system requirements, relates to the probability of finding affordable solutions. As a result, the effectiveness of tradespace exploration techniques is limited by its size and internal ordering. Therefore, we suggest that there exist models to elicit and use requirements that, for a given set older needs, could facilitate the maximization of the solutionof stakehspace so that the probability of finding more affordable solutions during tradespace exploration is also maximized.The present research proposes a mathematical model of the requirements elicitation process that facilitates defining performance objectives for the requirements elicitation process in striving for system affordability. The uniqueness of this research lays on two elements. First, the requirements elicitation process is mathematically modeled so that their objectives with respect to the effects on the solution space can be mathematically, and thus rigorously, described. Second, the system of interest focuses on the definition of the solutionspace as a driver for system affordability instead of on its actual exploration. The present research closes therefore the loop between stakeholder needs, system requirements, solutionspaces, and system affordability. The results of the present research are generalized to discrete requirements, fuzzy requirements, and continuous requirements or value functions.