The art and science of software release planning

Incremental development provides customers with parts of a system early, so they receive both a sense of value and an opportunity to provide feedback early in the process. Each system release is thus a collection of features that the customer values. Furthermore, each release serves to fix defects detected in former product variants. Release planning (RP) addresses decisions related to selecting and assigning features to create a sequence of consecutive product releases that satisfies important technical, resource, budget, and risk constraints.     

Optimized Resource Allocation for Software Release Planning

Release planning for incremental software development assigns features to releases such that technical, resource, risk and budget constraints are met. Planning of software releases and allocation of resources cannot be handled in isolation. A feature can be offered as part of a release only if all its necessary tasks are done before the given release date. We assume a given pool of human resources with different degrees of productivity to perform different types of tasks. To address the inherent difficulty of this process, we propose a two-phased optimization approach that combines the strength of two existing solution methods. The industrial applicability of the approach is primarily directed towards mature organizations having systematic development and measurement processes in place. The expected practical benefit of the planning method is to provide release plan solutions that achieve a better overall business value (e.g., expressed by the degree of stakeholder satisfaction) by better allocation of resources. Without ignoring the importance of the human expert in this process, the contributions of the paper are seen in making the overall process more objective and the resulting decisions more transparent.     

Fuzzy-set-based approach for concurrent constraint set-up planning

Material removal processes are integral parts of many manufacturing systems. They are either primary machining processes or an important part of preparing toolings for subsequent forming and moulding processes. Manufacturing process planning identifies the type of material removal processes and the machining parameters, cutting tools and fixtures needed to generate the features on a part. Previous research in manufacturing process planning has concentrated mainly on the role of features, in the derivation of the associated process and fixture plans. Many computer-aided process planning (CAPP) and computer-aided fixture planning (CAFP) systems derive process and fixture plans from the features on a part, on the basis that these features are context-free. However, manufacturing operations are interdependent processes. In the author's computer-aided set-up planning (CASP) system, a different perspective is adopted. Feature relations form the core of the conceptual structure. These features relations, which are often imprecise, are used in deriving set-up plans. The feature relations, which may be due to geometrical constraints, tolerance requirements, etc., are modelled using fuzzy sets and fuzzy relations. This paper presents the various feature relations considered in the present system and proposes a practical planning algorithm for set-up planning.     

Design and manufacturing of sheet-metal parts: Using features to aid process planning and resolve manufacturability problems

This paper describes an integrated system for the design and production of sheet-metal parts. We have identified some important features for the sheet-metal bending process. These features are automatically generated as the design progresses. After the designs are complete, our automatic process planning system uses the features and generates new ones to aid the production of plans with near-minimum manufacturing costs. Finally, these plans are used to produce parts on an automatic bending system.Once a plan is generated, it can be used to manufacture the part, and to provide feedback to design and other factory systems. The application of features and the potential feature interaction problems are discussed. Several key manufacturing problems are also considered and the result of planning is used to resolve these problems. By solving these feature interaction problems and often practical manufacturing issues, we are able to plan and manufacture the majority of the parts we have tested less than one hour after the flat patterns are prepared.     

A life-cycle cost viewpoint of software maintainability

The dynamic and ever-changing characteristics of software requirements make life-cycle costs for today's software very expensive. The cost of post-operational maintenance and modification often exceeds the original development cost. Software which is easily modifiable is not built naturally; it must be carefully contracted for and the development of modifiable software, its support tools and its documentation, must be judiciously managed and tested. However, without resorting to technological innovation of R&D investment, there is much that can be done well within today's state-of-the-art to accommodate significant life-cycle cost savings provided that the acquisition agencies understand the issues and are willing to spend the required time and effort (money) during the software development phase. In this paper we propose a procedure-based approach to software engineering of modifiability by discussing a number of important issues such as contracting for modifiability; techniques for building modifiability into software; planning for post-delivery test facilities and support tools; software maintenance documentation; planning and review to assure that the product evolved support modifiability.     

An intelligent multi-constraint finite capacity-based lot release system for semiconductor backend assembly environment

This paper presents an intelligent multi-constraint finite capacity-based lot release system which has been designed, developed and implemented to solve the lot release problems in a discrete manufacturing environment with huge product mix and multitude of capacity constraints. This system releases lots by firstly prioritising them according to a multi-attribute lot prioritization criteria, and then by applying predefined multiple capacity constraints to the sorted queue of lots. Finally the finite resource capacity is allocated to them sequentially. This system is designed to be adaptable and re-configurable in response to the dynamic changes in the manufacturing environment.The system can be configured to operate in both an automatic and manual lot release modes. When the system is triggered under the automatic lot release mode, it will perform lot releases automatically based on the latest lot orders information and the predefined configuration, parameters and capacity constraints. It facilitates the auto generation of lot release schedule during night shifts when the production control personnel is off duty, as the system can be triggered through scheduled task provided by the computer's operating system. The manual release mode is designed to cater for fine adaptation of the lot release schedule generated by the system through potential human intervention, through which, a user is allowed to adjust the lot release schedule, in response to some last minute urgent requests from the customers and unexpected events from the shop floor. Detailed reporting tools that provide a snapshot of the lot release results controlled by the various capacity constraints are available for analysis and further refinement of the lot release schedule.This system has been successfully implemented in a few Semiconductor Backend Assembly companies, and in most of these implementations, with direct integration to their existing manufacturing systems such as the Enterprise Resource Planning (ERP) and Manufacturing Execution System (MES).     

Group planning with time constraints

Embedding planning systems in real-world domains has led to the necessity of Distributed Continual Planning (DCP) systems where planning activities are distributed across multiple agents and plan generation may occur concurrently with plan execution. A key challenge in DCP systems is how to coordinate activities for a group of planning agents. This problem is compounded when these agents are situated in a real-world dynamic domain where the agents often encounter differing, incomplete, and possibly inconsistent views of their environment. To date, DCP systems have only focused on cases where agents’ behavior is designed to optimize a global plan. In contrast, this paper presents a temporal reasoning mechanism for self-interested planning agents. To do so, we model agents’ behavior based on the Belief-Desire-Intention (BDI) theoretical model of cooperation, while modeling dynamic joint plans with group time constraints through creating hierarchical abstraction plans integrated with temporal constraints network. The contribution of this paper is threefold: (i) the BDI model specifies a behavior for self interested agents working in a group, permitting an individual agent to schedule its activities in an autonomous fashion, while taking into consideration temporal constraints of its group members; (ii) abstract plans allow the group to plan a joint action without explicitly describing all possible states in advance, making it possible to reduce the number of states which need to be considered in a BDI-based approach; and (iii) a temporal constraints network enables each agent to reason by itself about the best time for scheduling activities, making it possible to reduce coordination messages among a group. The mechanism ensures temporal consistency of a cooperative plan, enables the interleaving of planning and execution at both individual and group levels. We report on how the mechanism was implemented within a commercial training and simulation application, and present empirical evidence of its effectiveness in real-life scenarios and in reducing communication to coordinate group members’ activities.     

The impact of rapid release cycles on the integration delay of fixed issues

The release frequency of software projects has increased in recent years. Adopters of so-called rapid releases—short release cycles, often on the order of weeks, days, or even hours—claim that they can deliver fixed issues (i.e., implemented bug fixes and new features) to users more quickly. However, there is little empirical evidence to support these claims. In fact, our prior work shows that code integration phases may introduce delays for rapidly releasing projects—98% of the fixed issues in the rapidly releasing Firefox project had their integration delayed by at least one release. To better understand the impact that rapid release cycles have on the integration delay of fixed issues, we perform a comparative study of traditional and rapid release cycles. Our comparative study has two parts: (i) a quantitative empirical analysis of 72,114 issue reports from the Firefox project, and a (ii) qualitative study involving 37 participants, who are contributors of the Firefox, Eclipse, and ArgoUML projects. Our study is divided into quantitative and qualitative analyses. Quantitative analyses reveal that, surprisingly, fixed issues take a median of 54% (57 days) longer to be integrated in rapid Firefox releases than the traditional ones. To investigate the factors that are related to integration delay in traditional and rapid release cycles, we train regression models that model whether a fixed issue will have its integration delayed or not. Our explanatory models achieve good discrimination (ROC areas of 0.80–0.84) and calibration scores (Brier scores of 0.05–0.16) for rapid and traditional releases. Our explanatory models indicate that (i) traditional releases prioritize the integration of backlog issues, while (ii) rapid releases prioritize issues that were fixed in the current release cycle. Complementary qualitative analyses reveal that participants’ perception about integration delay is tightly related to activities that involve decision making, risk management, and team collaboration. Moreover, the allure of shipping fixed issues faster is a main motivator for adopting rapid release cycles among participants (although this motivation is not supported by our quantitative analysis). Furthermore, to explain why traditional releases deliver fixed issues more quickly, our participants point out the rush for integration in traditional releases and the increased time that is invested on polishing issues in rapid releases. Our results suggest that rapid release cycles may not be a silver bullet for the rapid delivery of new content to users. Instead, our results suggest that the benefits of rapid releases are increased software stability and user feedback.     

Deterministic planning in the fifth international planning competition: PDDL3 and experimental evaluation of the planners

The international planning competition (IPC) is an important driver for planning research. The general goals of the IPC include pushing the state of the art in planning technology by posing new scientific challenges, encouraging direct comparison of planning systems and techniques, developing and improving a common planning domain definition language, and designing new planning domains and problems for the research community. This paper focuses on the deterministic part of the fifth international planning competition (IPC5), presenting the language and benchmark domains that we developed for the competition, as well as a detailed experimental evaluation of the deterministic planners that entered IPC5, which helps to understand the state of the art in the field.We present an extension of pddl, called pddl3, allowing the user to express strong and soft constraints about the structure of the desired plans, as well as strong and soft problem goals. We discuss the expressive power of the new language focusing on the restricted version that was used in IPC5, for which we give some basic results about its compilability into pddl2. Moreover, we study the relative performance of the IPC5 planners in terms of solved problems, CPU time, and plan quality; we analyse their behaviour with respect to the winners of the previous competition; and we evaluate them in terms of their capability of dealing with soft goals and constraints, and of finding good quality plans in general. Overall, the results indicate significant progress in the field, but they also reveal that some important issues remain open and require further research, such as dealing with strong constraints and computing high quality plans in metric-time domains and domains involving soft goals or constraints.     

Transmission planning for Indian power grid: a mixed integer programming approach

The paper presents a modeling framework to analyze some important issues associated with operation planning of a power system. Major activities involved in operations planning of large integrated power systems are considered simultaneously to ensure optimal utilization of generation and transmission capacity. The model also examines optimal transmission expansion plans vis-à-vis fuel supply issues. A mixed integer programming model is developed for this purpose and the Indian power system considered. Specific emphasis is on spatial transmission expansion plan for the existing Indian inter-state transmission grid and new transmission links, coordinated operation of the isolated regional grids and system benefits accruing from transmission expansion, enhanced fuel production and supply rescheduling to ensure efficient operation of various generating stations.     

An empirical study of software release notes

Release notes are an important source of information about a new software release. Such notes contain information regarding what is new, changed, and/or got fixed in a release. Despite the importance of release notes, they are rarely explored in the research literature. Little is known about the contained information, e.g., contents and structure, in release notes. To better understand the types of contained information in release notes, we manually analyzed 85 release notes across 15 different software systems. In our manual analysis, we identify six different types of information (e.g., caveats and addressed issues) that are contained in release notes. Addressed issues refer to new features, bugs, and improvements that were integrated in that particular release. We observe that most release notes list only a selected number of addressed issues (i.e., 6-26 % of all addressed issues in a release). We investigated nine different factors (e.g., issue priority and type) to better understand the likelihood of an issue being listed in release notes. The investigation is conducted on eight release notes of three software systems using four machine learning techniques. Results show that certain factors, e.g., issue type, have higher influence on the likelihood of an issue to be listed in release notes. We use machine learning techniques to automatically suggest the issues to be listed in release notes. Our results show that issues listed in all release notes can be automatically determined with an average precision of 84 % and an average recall of 90 %. To train and build the classification models, we also explored three scenarios: (a) having the user label some issues for a release and automatically suggest the remaining issues for that particular release, (b) using the previous release notes for the same software system, and (c) using prior releases for the current software system and the rest of the studied software systems. Our results show that the content of release notes vary between software systems and across the versions of the same software system. Nevertheless, automated techniques can provide reasonable support to the writers of such notes with little training data. Our study provides developers with empirically-supported advice about release notes instead of simply relying on adhoc advice from on-line inquiries.     

CTP: A New Constraint-Based Formalism for Conditional, Temporal Planning

Temporal constraints pose a challenge for conditional planning, because it is necessary for a conditional planner to determine whether a candidate plan will satisfy the specified temporal constraints. This can be difficult, because temporal assignments that satisfy the constraints associated with one conditional branch may fail to satisfy the constraints along a different branch. In this paper we address this challenge by developing the Conditional Temporal Problem (CTP) formalism, an extension of standard temporal constraint-satisfaction processing models used in non-conditional temporal planning. Specifically, we augment temporal CSP frameworks by (1) adding observation nodes, and (2) attaching labels to all nodes to indicate the situation(s) in which each will be executed. Our extended framework allows for the construction of conditional plans that are guaranteed to satisfy complex temporal constraints. Importantly, this can be achieved even while allowing for decisions about the precise timing of actions to be postponed until execution time, thereby adding flexibility and making it possible to dynamically adapt the plan in response to the observations made during execution. We also show that, even for plans without explicit quantitative temporal constraints, our approach fixes a problem in the earlier approaches to conditional planning, which resulted in their being incomplete.     

Formal design and implementation of constraints in software components

This paper deals with the modeling, automatic implementation and runtime verification of constraints in component-based applications. Constraints have been assuming an ever more relevant role in modeling distributed systems as long as business rules implementation, design-by-contract practice, and fault-tolerance requirements are concerned. Nevertheless, component developers are not sufficiently supported by existing tools to model and implement such features.In this paper, we propose a methodology and a set of tools that enable developers both to model component constraints and to generate automatically component skeletons that already implement such constraints. The methodology has been extended to support implementation even in case of legacy components.     

Object oriented concepts and mechanisms for feature-based computer integrated inspection

Computer vision can provide fast, accurate and reliable inspection. In this paper is described a knowledge-based vision inspection planning system for manufactured components based on their CAD design models. An object oriented methodology is developed to capture the knowledge such as the geometric entities, their relationships, sensors and plans. Reasoning mechanisms are developed to automatically determine various attributes of the different features of an object to be inspected, and to generate the alternative strategies for inspection of each attribute. Mechanisms for automated generation of sensor settings and optimization of the inspection plan are also developed. Sensor constraints are considered in determining the camera parameters. This inspection methodology is flexible, and it is easily integrated with the design and process planning aspects of an integrated manufacturing system.     

Optimisation of PM scheduling for multi-component systems – a simulated annealing approach

Proper planning of preventive maintenance (PM) is crucial in many industries such as oil transmission pipelines, automotive and food industries. A critical decision in the PM plans is to determine frequencies and types of maintenance actions in order to achieve a certain level of system availability with a minimum total cost. In this paper, we consider the problem of obtaining availability-based non-periodic optimal PM planning for systems with deteriorating components. The objective is to sustain a certain level of availability with the minimal total maintenance-related costs. In the proposed approach, the planning horizon is divided into some inspection periods of equal intervals. For any given interval, a decision must be made to perform one of the three actions on each component; inspection, preventive repair and preventive replacement. Any of these activities has different effects on the reliability of the components and the corresponding distinct costs based on the required recourses. The cost function includes the cost for repair, replacement, system downtime and random failures. System availability and PM resources are the main constraints considered. Since the proposed model is combinatorial in nature involving non-linear decision variables, a simulated annealing algorithm is employed to provide good solutions within a reasonable time.     

Multi-agent collaboration in time-constrained domains

Timeliness is usually an indispensable attribute of planning and problem solving for resource allocation in command, control and communication systems. The success of such a system is judged on its ability to respond to scheduled and unscheduled tasks within a permissible time period. The response is based on a plan that covers the following activities: resource allocation, plan execution and monitoring and dynamic plan mending, if necessary. Decision making for resource selection can become very time consuming when there are many resources and the number of constraints is large. In a changing environment of multiple agents, restrictive organizational structures and strict communication protocols may cause intolerable further delays.Traditional approaches to planning in deterministic environments require a predictable amount of time to produce and execute plans. However, given more time, such systems usually cannot improve on the plans. In this paper we describe a multi-agent resource scheduler which uses a prioritized rule base to model decision making under the constraints of time. We also discuss dynamic scoping as a negotiation technique for inter-agent cooperation and constrained lattice-like communications as an optimized message routing strategy. Finally, we present some empirical results from a sequence of experiments.     

基于伪谱法的双摆吊车时间最优消摆轨迹规划策略

在工业生产过程中,桥式吊车系统经常会体现出双摆系统的特性,导致更多欠驱动状态量的出现,增大控制难度.基于此,论文提出了一种针对双摆桥式吊车系统的时间最优轨迹规划方法,可以得到全局时间最优且具有消摆能力的轨迹.具体而言,为方便地构造以时间为代价函数的优化问题,首先对系统运动学模型进行相应的变换;在此基础上,考虑包括两级摆角及台车速度和加速度上限值在内的多种约束,构造出相应的优化问题;然后,利用高斯伪谱法(Gauss-pseudospectral method, GPM)将该带约束的优化问题转化为更易于求解的非线性规划问题,且在转化过程中,可以非常方便地考虑轨迹约束.求解该非线性规划问题,即可得到时间最优的台车轨迹.不同于已有的大多数方法,该方法可获得全局时间最优的结果.最后,通过仿真与实验结果验证了这种时间最优轨迹规划方法具有满意的控制性能.     

Applications of parallel processing technologies in heuristic search planning: methodologies and experiments

The goal of this paper is to investigate the application of parallel programming techniques to boost the performance of heuristic search‐based planning systems in various aspects. It shows that an appropriate parallelization of a sequential planning system often brings gain in performance and/or scalability. We start by describing general schemes for parallelizing the construction of a plan. We then discuss the applications of these techniques to two domain‐independent heuristic search‐based planners—a competitive conformant planner (CP A) and a state‐of‐the‐art classical planner (FF). We present experimental results—on both shared memory and distributed memory platforms—which show that the performance improvements and scalability are obtained in both cases. Finally, we discuss the issues that should be taken into consideration when designing a parallel planning system and relate our work to the existing literature. Copyright © 2009 John Wiley & Sons, Ltd.     

PLANNING IN REACTIVE ENVIRONMENTS

The diffusion of domotic and ambient intelligence systems have introduced a new vision in which autonomous deliberative agents operate in environments where reactive responses of devices can be cooperatively exploited to fulfill the agent's goals. In this article a model for automated planning in reactive environments, based on numerical planning, is introduced. A planner system, based on mixed integer linear programming techniques, which implements the model, is also presented. The planner is able to reason about the dynamic features of the environment and to produce solution plans, which take into account reactive devices and their causal relations with agent's goals by exploitation and avoidance techniques, to reach a given goal state. The introduction of reactive domains in planning poses some issues concerning reasoning patterns which are briefly depicted. Experiments of planning in reactive domains are also discussed.     

Understanding the role of licenses and evolution in open architecture software ecosystems

The role of software ecosystems in the development and evolution of open architecture systems whose components are subject to different licenses has received insufficient consideration. Such systems are composed of components potentially under two or more licenses, open source or proprietary or both, in an architecture in which evolution can occur by evolving existing components, replacing them, or refactoring. The software licenses of the components both facilitate and constrain the system's ecosystem and its evolution, and the licenses’ rights and obligations are crucial in producing an acceptable system. Consequently, software component licenses and the architectural composition of a system help to better define the software ecosystem niche in which a given system lies. Understanding and describing software ecosystem niches for open architecture systems is a key contribution of this work. An example open architecture software system that articulates different niches is employed to this end. We examine how the architecture and software component licenses of a composed system at design time, build time, and run time help determine the system's software ecosystem niche and provide insight and guidance for identifying and selecting potential evolutionary paths of system, architecture, and niches.