Evaluation of a process for architectural assumption management in software development

Abstract

Context:Architectural assumption management is critical to the success of software development projects. In this paper, we propose an Architectural Assumption Management (AAM) process, comprised of four AAM activities: Architectural Assumption Making, Description, Evaluation, and Maintenance. Objective: Evaluating the AAM process in architectural assumption management, regarding the ease of understanding and the effort of conducting the AAM process, as well as the effectiveness of using the AAM process to make architectural assumptions explicit and to identify and reduce invalid architectural assumptions. Method: An explanatory study with 88 first-year master students in software engineering, and an exploratory study with five practitioners from five companies. Results: (1) the ease of understanding the AAM process is moderate for first-year master students but easy for practitioners; (2) the effort of conducting the AAM process is moderate for first-year master students; (3) Making and Evaluation took the students more time than Description and Maintenance; (4) the practitioners considered Evaluation as the most time consuming activity; (5) the AAM process can help to make architectural assumptions explicit and to identify and reduce invalid architectural assumptions in projects. The majority of the students and practitioners agreed that Architectural Assumption Evaluation is the most helpful activity for all these three aspects. For other activities, there are different opinions about their helpfulness; and (6) there are various factors identified that can impact the aforementioned results. Being aware of and properly adjusting these factors can facilitate the application of the AAM process in projects. Conclusions: The AAM process aims at systematically managing architectural assumptions in software development. The results of the case studies provide preliminary empirical evidence for the evaluation of the AAM process.

Self-Claimed Assumptions in Deep Learning Frameworks: An Exploratory Study

“…Li et al [19] conducted an experiment to evaluate the performance of seven machine learning methods (e.g., Support Vector Machine, Logistic Regression, and Perceptron) in automatically classifying software development assumptions. We [33] proposed a general process for software architectural assumption management, and evaluated the process with two case studies regarding the ease of understanding and the effort of conducting the process, as well as the effectiveness of using the process to make architectural assumptions explicitly and to identify and reduce invalid architectural assumptions. There are also studies (e.g., [16], [24], and [29]) that treat assumptions as second-class entities in software development, for example, a kind of rationale for software design decisions, and include assumption management as part of a single step in software development.…”

An Assumption Network-Based Approach to Support Margin Allocation and Management

“…defining the functions to be performed by the system, plays a central role in system architecting (Umeda and Tomiyama, 1997). One approach to functional reasoning is the RFLP paradigm (Kleiner and Kramer, 2013), which is based on the VDI 2206 standard Design methodology for mechatronic systems (VDI, 2004). It considers that functional reasoning is distributed over four notional domains: Requirements, Functional, Logical and Physical, which can be defined as follows:…”

“…However, such definitions are incomplete as they do not capture some essential characteristics of assumptions. Some of these characteristics were defined by Yang et al (2018) in the context of software development, where assumptions are: (i) subjective, i.e. can be seen as assumptions by some stakeholders, or design decisions by others, (ii) related to other software artefacts, such as requirements or components, (iii) dynamic, i.e.…”

“…Although such a capability allows reducing the cost of managing assumptions, this framework is restricted to assumptions on software components, meaning that the dependencies between assumptions and other architectural elements (such as requirements) are not considered. Recently, Yang et al (2018) proposed another approach which includes a documentation framework that records dependencies both amongst assumptions, and between assumptions and other software artefacts. Such knowledge about dependency is crucial in assessing the impact of assumptions on the overall architecture, but the lack of support for capturing such dependencies highly increases the effort needed for systematic assumption management.…”

Preparation Process Orthogonal Optimization and Mechanical Properties of Microcellular Foam Polypropylene

“…[ 13 ] In order to improve its foaming performance, scholars have done many studies on it. [ 14–16 ] Zhao et al. [ 17 ] starting from the direction of increasing melt strength, using rubber reinforced PP melt viscosity to injecting PP foaming, then obtained highly refined and uniform foams, the prepared foamed material has higher ductility than neat PP foam.…”