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Requirement prioritization (RP) is a crucial task in managing requirements as it determines the order of implementation and, thus, the delivery of a software system. Improper RP may cause software project failures due to over budget and schedule as well as a low-quality product. Several factors influence RP. One of which is requirements dependency. Handling inappropriate handling of requirements dependencies can lead to software development failures. If a requirement that serves as a prerequisite for other requirements is given low priority, it affects the overall project completion time. Despite its importance, little is known about requirements dependency in RP, particularly its impacts, types, and techniques. This study, therefore, aims to understand the phenomenon by analyzing the existing literature. It addresses three objectives, namely, to investigate the impacts of requirements dependency on RP, to identify different types of requirements dependency, and to discover the techniques used for requirements dependency problems in RP. To fulfill the objectives, this study adopts the Systematic Literature Review (SLR) method. Applying the SLR protocol, this study selected forty primary articles, which comprise 58% journal papers, 32% conference proceedings, and 10% book sections. The results of data synthesis indicate that requirements dependency has significant impacts on RP, and there are a number of requirements dependency types as well as techniques for addressing requirements dependency problems in RP. This research discovered various techniques employed, including the use of Graphs for RD visualization, Machine Learning for handling large-scale RP, decision making for multi-criteria handling, and optimization techniques utilizing evolutionary algorithms. The study also reveals that the existing techniques have encountered serious limitations in terms of scalability, time consumption, interdependencies of requirements, and limited types of requirement dependencies.

The potentially many software system input combinations make exhaustive testing practically impossible. To address this issue, combinatorial t-way testing (where t indicates the interaction strength, i.e. the number of interacting parameters (input)) was adopted to minimize the number of cases for testing. Complimentary to existing testing techniques (e.g. boundary value, equivalence partitioning, cause and effect graphing), combinatorial testing helps to detect faults caused by the faulty interaction between input parameters. In the last 15 years, applications of meta-heuristics as the backbone of t-way test suite generation have shown promising results (e.g. Particle Swarm Optimization, Cuckoo Search, Flower Pollination Algorithm, and Hyper-Heuristics (HHH), to name a few). Supporting the No Free Lunch theorem, as well as potentially offering new insights into the whole process of t-way generation, this article proposes a new strategy with constraint support based on the Whale Optimization Algorithm (WOA). Our work is the first attempt to adopt the WOA as part of a search-based software engineering (SBSE) initiative for t-way test suite generation with constraint support. The experimental results of the test-suite generation indicate that WOA produces competitive outcomes compared to some selected single-based and population-based meta-heuristic algorithms.

Software requirement changes are inevitable due to the dynamic needs of business process and environment. Such changes in requirement need to be managed accordingly by determining the influencing factors as well as assessing their impacts on the current environment through impact analysis. The analysis is accomplished by a dedicated team, namely Change Control Board (CCB). In essence, an impact analysis helps CCB to understand the potential impacts of change towards organization before implementing them. This is vital because an improper analysis may not only affect project but also organization’s sustainability. Previous studies have identified several technical and non-technical factors that should be considered during impact analysis. The factors however are isolated and disintegrated, which causes a holistic impact analysis to be difficult. Thisstudy therefore aimed to identify and integrate those factors as an integrated impact analysis model for software requirements changes. This study is qualitative in nature where the data were collacted through a focus group interview. The collected data were analysed by using content anaysis approach. The findings indicate that there are four categories of factor, namely People, Process, Technology(existing) and Organisation. Each category consists of several factors and elements, which are linked to indicate their interrelationships. The model can be used by CCB as a guide to decide the way forward for a particular requirement change request

Formal notations employ mathematical symbols and interpretation to illustrate system elements. The formality imposed by the notations allows the accuracy and consistency of a system model to be confirmed by verification tools. Formal notations on the other hand are difficult to understand and use by most users. As supporting instruments, verification tools are expected to be as usable as possible to overcome this limitation. This study presents a survey conducted on two instances of verification tools that support formal notations, namely ProB and B-Toolkit. The focus of the survey was to identify the important features that are necessary for verification tools to become usable to users. The survey assessed the tools’ usability based on the Cognitive Dimensions of Notations (CD) framework and several criteria suggested by the International Organization for Standardization (ISO). Sixty-three participants responded to the survey. The data were analyzed by using the Grounded Theory. The analysis enabled the identification of abstract features and properties that formed a design guideline for usable verification tools. The 38guideline includes three main categories of feature; Interface, Utilities and Resources Management. The features are further elaborated through the specification of specific properties and dimensions for implementation. The guideline could act as a roadmap for tool designers to design verification tools that promote the use of formal notations.

Conceptual models communicate the important aspects of a problem domain to stakeholders. The quality of the models is highly dependent on the usability of the modeling method used. This paper presents a survey conducted on a method that integrates the use of a semiformal notation, namely the Unified Modeling Language (UML) and a formal notation, namely B. The survey assessed the usability of the method by using the grounded theory, the Cognitive Dimensions of Notations (CD) framework, and several criteria suggested by the International Organization for Standardization (ISO). Ten participants responded to the survey. The results suggest that the method is accessible to users when the principles and roles of each notation are obvious and well understood, and when there is strong support from the environment. Supported by the findings, a usability profile based on CD for designing a method that integrates semiformal and formal notations is proposed.