Reliability Attributes in Software Development

What is Reliability Attributes in Software Development:

Reliability attributes are the measure of software reliability. There may be many reliability requirements for different software but all the software have some common reliability measures. Reliability attributes for different categories of software products may be different. Therefore, it is necessary to specify the that the level of reliability required for a software product in the software requirements specification document. There are some attributes that are required to significantly express the reliability of a software product. A good reliability measure should be dependent of observer so that different people can agree on the degree of reliability that a system has. For example, there are various techniques for measuring performance which possibly would result in obtaining the same performance value irrespective of who is carrying out the performance measurement. But practically it is very difficult to formulate a precise reliability measurement technique. The next base case is to have measures that relate with reliability.

There are many reliability attributes which can be used to express the reliability of a software product. Some of them are:

• Rate of occurrence of failure (ROCOF) : ROCOF measures the frequency of occurrence of unexpected behavior of the software. It basically measures how many times the software product fails. ROCOF measure of a software product can be obtained by having the record of the behavior of a software product. ROCOF is basically the total number of failures occurring during the specified time interval.
• Mean Time To Failure (MTTF) : The average time between two successive failures is known as MTTF. It is obtained by observing numerous failures in the software product. To measure MTTF, failure data for n failures is recorded. If the failures occur at the time instants T1, T2, … Tn ,then MTTF can be calculated as: MTTF = ( (T2 – T1) + (T3 – T2) + … + (Tn+1 – Tn) ) / (n-1)
  It is notable that only run time is considered in the time measurements. The time for which the system is down to fix the error, the boot time and any other negligible time are neglected and are not included in the time measurements.
• Mean Time To Repair (MTTR) : When the software fails, it requires some time to fix the error. MTTR is the measure of the average time system takes to find the errors that cause the failure and to fix them.
• Mean Time Between Failure (MTBR) : MTBR attribute can be obtained by combining the MTTF and MTTR attributes.

MTBF = MTTF + MTTR 

Thus, MTBF indicates that once a failure occurs, the next failure is expected after same time. In this case, time measurements are real time and not the execution time like MTTF. 

• Probability of Failure on Demand (POFOD): This attribute does not involve time measurements like the other attributes. POFOD measures the behavior of the system failing when a service request is made. For example, if POFOD measures 0.001 then it means that out of every 1000 one time the service requests would result in a failure. 
• Availability: Availability of a system is a measure of possibility of availability of the system for use over a given period of time. It considers the number of failures occurring during a time interval. It also takes into measure the downtime of a system when a failure occurs. This attribute is important for systems which are supposed to be never down. This plays a vital role in telecommunication systems and operating systems. These systems need to run even during the repair time.
• Fault Tolerance: The ability of a system to function correctly in the event of unexpected events or component breakdowns is known as fault tolerance. The ability of these systems to carefully recover from faults keeps just one point of breakdown from creating significant interruptions.
• Resilience: The system’s resilience is its capacity to adjust to shifting circumstances and carry on operating even in the face of unexpected challenges. These systems are resilient enough to withstand disturbances like hardware failures, network problems or spikes in traffic without significantly affecting performance.
• Recoverability: Recoverability refers to a system’s ability to bounce back from a setback or unforeseen incident quickly and effectively. Recoverability of a system guarantees less downtime and loss of data, which improves overall dependability and user happiness.
• Redundancy: Redundancy is the process of duplicating essential system parts or operations to guarantee uninterrupted use in the event of a failure. It increases the overall reliability of the system, helps distribute the load and avoids a single point of failure.
• Scalability: Scalability is the capacity of a system to add nodes or resources to accommodate growing workloads or user loads. The performance and dependability of these systems can grow along with the user base or workload, due to their capacity to adapt.
• Consistency: Maintaining consistency makes a system operate in a predictable and dependable manner, giving consumers a consistent experience. Errors and confusion can result from inconsistent behavior.

Following points which strongly affects the software reliability.

• Complexity of Software: The high complexity of software is the major contributing factor of Software Reliability problems. This is a tough scenario for developers as the rising complexity of software is difficult to optimize. Complexity is directly related to software reliability, so representing complexity is important. Complexity-oriented metrics is a method of determining the complexity of a program’s control structure, by simplify the code into a graphical representation. A representative metric is McCabe’s Complexity Metric.
• Optimistic Nature: Many people would think that once after the software can run correctly, it will be correct forever. This leads to feeling of security, but actually we are going on a path of self-destruction if we believe like this. We need to fix issues as soon as they arise.
  Effect of Environment :Once perfectly working software may also break if the running environmental changes. For example. Let us talk the case of Ariane rocket. After the success of Ariane 4 rocket, the maiden flight of Ariane 5 ended up in flames while design defects in the control software were unveiled by faster horizontal drifting speed of the new rocket.
• Software failure: Software failures may be due to errors, ambiguities, oversights or misinterpretation of the specification that the software is supposed to satisfy, carelessness or incompetence in writing code, inadequate testing, incorrect or unexpected usage of the software or other unforeseen problems.
• Lack of effective Software Reliability Models: A proliferation of software reliability have emerged as people try to understand the characteristics of how and why software falls, and try to quantify software reliability. As many models as there are and many more emerging, none of the models can capture a satisfying amount of the complexity of software. Constraints and assumptions have to be made for the quantifying process. Therefore, there is o single model that can be used in all situations. No model is complete or even preventative. One model may work well for a set of certain software, but may be completely off track for other kinds of issues.

Advantages of focusing on reliability attributes in software development include:

1. Increased customer satisfaction: Reliable software systems that are available, fault-tolerant, and recoverable can enhance customer satisfaction by reducing downtime, minimizing errors, and improving overall system performance.
2. Enhanced brand reputation: A reliable software system can enhance the reputation of the brand and increase customer loyalty by demonstrating a commitment to quality and reliability.
3. Improved system performance: By focusing on reliability attributes, software developers can identify potential performance issues and address them before they become major problems.
4. Reduced maintenance costs: Maintainable software systems that are designed with reliability in mind can reduce the cost and effort associated with system maintenance and updates.

Disadvantages of focusing on reliability attributes in software development include:

1. Increased development time and cost: Focusing on reliability attributes requires additional time and resources during the software development lifecycle, which can increase development costs and delay time-to-market.
2. Difficulty in balancing reliability and functionality: Focusing too much on reliability attributes can sometimes result in sacrificing functionality or usability, which can negatively impact the end-user experience.
3. Difficulty in predicting and simulating real-world conditions: It can be difficult to accurately predict and simulate real-world conditions and usage patterns during the development and testing of software systems, which can limit the effectiveness of reliability testing.
4. Overall, the advantages of focusing on reliability attributes in software development typically outweigh the disadvantages, as they can result in more reliable and robust software systems that meet the needs and expectations of end-users.